REGAINING CONTROL – DRUM-BUFFER-ROPE IN MADE-TO- ORDER APPAREL MANUFACTURING ARUSH DIXIT & VASHISTHA IYER \ Department of Fashion Technology National Institute of Fashion Technology, Gandhinagar May, 2010
May 27, 2015
REGAINING CONTROL – DRUM-BUFFER-ROPE IN MADE-TO-
ORDER APPAREL MANUFACTURING
ARUSH DIXIT & VASHISTHA IYER \
Department of Fashion Technology National Institute of Fashion Technology, Gandhinagar
May, 2010
REGAINING CONTROL – DRUM-BUFFER-ROPE IN MADE-TO-
ORDER APPAREL MANUFACTURING
A dissertation submitted in partial Fulfillment of the requirement for the award of Degree
in
Bachelor of Fashion Technology (Apparel Production)
Submitted By
ARUSH DIXIT & VASHISTHA IYER
Under the Guidance of
MR. MANOJ TIWARI
Department of Fashion Technology National Institute of Fashion Technology, Gandhinagar
May, 2010
Index
Abstract ............................................................................................................................................ i
Certificate ........................................................................................................................................ ii
Acknowledgements ........................................................................................................................ iii
List of Tables ................................................................................................................................. iv
List of Figures ................................................................................................................................. v
01. Introduction ............................................................................................................................... 1
1.1. Objectives ............................................................................................................................. 4
02. Review of Literature ................................................................................................................. 5
2.1 Production Concepts & Applications .................................................................................... 6
2.2. Theory of Constraints ......................................................................................................... 18
2.3. V/A/T Analysis & Synchronous Manufacturing ................................................................ 20
2.4. Drum-Buffer-Rope Scheduling .......................................................................................... 23
2.2 List of References................................................................................................................ 28
03. Methodology ........................................................................................................................... 29
3.1. Scope of Research .............................................................................................................. 30
3.2. Assumptions ....................................................................................................................... 30
3.3. Constraints .......................................................................................................................... 30
3.3.1. Identifying the Constraint ............................................................................................ 31
3.3.2. V/A/T and 5 Why Analysis ......................................................................................... 31
3.3.3. Design of Constraint .................................................................................................... 32
3.4. Applying Drum-Buffer-Rope ............................................................................................. 33
3.4.1. Establishing Time Buffers ........................................................................................... 34
3.4.2. Creating a Drum Schedule ........................................................................................... 34
3.4.3. Buffer Management ..................................................................................................... 35
3.4.4. Comparison of Existing & Proposed Systems ............................................................. 35
04. Constraints .............................................................................................................................. 37
4.1. Identifying the System’s Constraint ................................................................................... 40
4.2. Designing the System’s Constraint .................................................................................... 45
4.3. Exploiting the System’s Constraint .................................................................................... 46
05. Drum-Buffer-Rope .................................................................................................................. 50
5.1. The Drum ........................................................................................................................... 51
5.2. The Buffer .......................................................................................................................... 52
5.3. The Rope ............................................................................................................................ 55
5.4. Drum-Buffer-Rope Schedule ............................................................................................. 56
5.5. Buffer Management............................................................................................................ 61
5.5.1 Local Control – Buffer status ....................................................................................... 63
5.5.2. Global Feedback - Buffer Hole ................................................................................... 64
5.5.3. Global Feedback –Reason code analysis ..................................................................... 65
5.5.4 Local Measurements ..................................................................................................... 66
06. Results ..................................................................................................................................... 69
6.1. Planned v/s Actual .............................................................................................................. 70
6.2. The Drum-Buffer-Rope Schedule ...................................................................................... 72
6.3. New v/s Old ........................................................................................................................ 74
07. Limitations and Scope of Further Study ................................................................................. 75
7.1. Limitations ......................................................................................................................... 76
7.2. Scope for Further Study ..................................................................................................... 77
08. Conclusion .............................................................................................................................. 79
8.1. Recommendations .............................................................................................................. 82
09. Bibliography ........................................................................................................................... 84
Mabin J. Victoria & Steven J. Balderstone “The world of the theory of constraints: a review of the international literature” CRC Press (2000) ............................................................................. 85
Appendices .................................................................................................................................... 87
Appendix A ................................................................................................................................ vi
Appendix B ............................................................................................................................... vii
Appendix C.1 ........................................................................................................................... viii
Appendix C.2 ............................................................................................................................. ix
Appendix C.3 .............................................................................................................................. x
Appendix C.4 ............................................................................................................................. xi
Appendix D ............................................................................................................................... xii
Appendix E ............................................................................................................................... xiii
Appendix F ............................................................................................................................... xiv
Appendix G.1 ............................................................................................................................ xv
Appendix G.2 ........................................................................................................................... xvi
Appendix G.3 .......................................................................................................................... xvii
Appendix G.4 ......................................................................................................................... xviii
Appendix G.5 ........................................................................................................................... xix
Appendix G.6 ............................................................................................................................ xx
Appendix G.7 ........................................................................................................................... xxi
Appendix G.8 .......................................................................................................................... xxii
Appendix G.9 ......................................................................................................................... xxiii
Appendix H ............................................................................................................................ xxiv
Appendix I ............................................................................................................................... xxv
Appendix J.1........................................................................................................................... xxvi
Appendix J.2.......................................................................................................................... xxvii
Appendix K .......................................................................................................................... xxviii
Annexures .................................................................................................................................. xxix
Annexure 1 ................................................................................................................................ xxx
i
Abstract
Apparel companies are continuously exploring different philosophies to improve their
operations. Amongst others, Theory of Constraints provides the simplest solution for production
in the form of Drum-Buffer-Rope scheduling, an application which does not require large sets of
data, extensive worker training or lower level buy-in. This paper illustrates how a drum-buffer-
rope application can be designed and implemented in a high-mix/low-volume made-to-order
apparel manufacturing environment. It addresses the various issues that apparel manufacturers
could face when beginning to implement a Theory of Constraints application. The
implementation was carried out in an apparel export house in Jaipur, Rajasthan and showed
that drum-buffer-rope can be successfully applied to even small and medium sized companies
enabling them to achieve dramatic improvements in due-date performance and substantial
reduction in lead times and inventories. Of the various benefits that Drum-Buffer-Rope can
provide, the most immediate one is a production schedule which actually works despite the
common culprits such as unreliable vendors, absenteeism, machine breakdowns, absence of
accurate data, unreliable processes and quality problems. Such a high performing schedule
leads to a high performing and stable system. This stability must be used as the cornerstone to
kick start a process of ongoing improvement in the pursuit of operational excellence.
ii
Certificate
“This is to certify that this Project Report titled “Regaining Control – Drum-Buffer-Rope in
Made-to-Order Apparel Manufacturing” is based on our, Arush Dixit’s & Vashishtha Iyer’s
original research work, conducted under the guidance of Mr. Manoj Tiwari towards partial
fulfillment of the requirement for award of the Bachelor’s Degree in Fashion Technology
(Apparel Production), of the National Institute of Fashion Technology, Gandhinagar.
No part of this work has been copied from any other source. Material, wherever borrowed
has been duly acknowledged.
Arush Dixit
Vashistha Iyer
iii
Acknowledgements
We are extremely grateful to National Institute of Fashion Technology for making this
exercise in effect with the curriculum. The project would not have been completed without the
timely efforts and involvement of our mentor Mr. Manoj Tiwari (Asst. Professor, DFT) and Ms.
Amisha Mehta (CC-DFT). Their guidance is an indispensable part of this research work.
We express our heartfelt gratitude to Mr.Rajiv Dewan (CEO) and Mr. Rakesh Dewan
(Director), Ma’Am Arts, Jaipur for their candid didactics on the apparel export business and for
allowing us to pursue our graduation project with their company.
Mr. Varun Mishra (General Manager - Production) deserves a special mention for providing
the required support during the implementation phase of the project and for those endless
debates about the project and related concepts. We are also thankful to the staff of Ma’Am Arts
for their support and coordination.
Last but not the least we thank our parents and friends for being a constant source of support
and inspiration.
iv
List of Tables
Table 4.1 - Style Produced between 8th March, 2010 and 7th April, 2010 .................................... 42
Table 4.2 - Types of Packing ........................................................................................................ 48
Table 4.3 - Illustration of production within the drum ................................................................ 49
Table 5.1 A - Lead time from Material Release to Sewing for Dyed Products ............................ 53
Table 5.1 B - Lead time from Material Release to Sewing for Printed Products ......................... 53
Table 5.2 - Production Buffer Size ............................................................................................... 54
Table 5.3 A - Details of orders executed on the Drum ................................................................. 56
Table 5.3 B - Due dates of orders executed on the Drum ............................................................. 56
Table 5.4 - Estimating Work Content ........................................................................................... 57
Table 5.5 - Detail plan for Sheet No. 1732 A and 1732 B fed to Drum I consecutively .............. 59
Table 5.6 - Drum Schedule ........................................................................................................... 60
Table 5.7 - Material Release Schedule ......................................................................................... 61
Table 5.8 - Reason Code Analysis ................................................................................................ 66
Table 5.9 - Severity ....................................................................................................................... 67
Table 5.10 - Daily Severity Chart ................................................................................................. 68
Table 6.1 - Planned v/s Actual at Drum 1 on 15th April ............................................................... 70
Table 6.2 - Planned vs Actual comparison for packed output at Drum 1 ..................................... 71
Table 6.3 - Planned vs Actual comparison for packed output at Drum 2 ..................................... 72
Table 6.4 - Progress of Order scheduled by Drum-Buffer-Rope (Sundays are excluded) ........... 73
Table 6.5 - Performance Comparison ............................................................................................ 74
v
List of Figures
Figure 2.1 - Relationship between management time required and the time buffer size.............. 17
Figure 4.1 - Flowchart of Processes at MA’AM Arts, Jaipur ....................................................... 41
Figure 4.2 - Shifting Bottlenecks .................................................................................................. 43
Figure 5.1 - Drum and Buffer ....................................................................................................... 54
Figure 5.2 - Effects of Choking Material Release ....................................................................... 55
Figure 5.3 - Determining Drum Start and Material Release ......................................................... 58
Figure 5.4 - Zoning of Buffers ...................................................................................................... 62
Figure 5.5A - Buffer holes in production buffer for dyed products .............................................. 64
Figure 5.5B - Buffer holes in production buffer for printed products .......................................... 65
Figure 5.6 - Buffer Exhaustion ..................................................................................................... 66
1
01. Introduction
2
“A truly prosperous time is when the largest numbers of people are getting all they can
legitimately eat and wear, and are in every sense of the word comfortable. It is the degree of the
comfort of the people at large--not the size of the manufacturer's bank balance--that evidences
prosperity. The function of the manufacturer is to contribute to this comfort. He is an instrument
of society and he can serve society only as he manages his enterprises so as to turn over to the
public an increasingly better product at an ever-decreasing price, and at the same time to pay to
all those who have a hand in his business an ever-increasing wage, based upon the work they do.
In this way and in this way alone can a manufacturer or any one in business justify his
existence.” – Henry Ford, My Life and Work
The business of fashion in the 21st century has evolved into a complex web with the advent
of globalization transcending it beyond physical barriers between markets and manufacturers.
Increased fashion cycles have led to buyers demanding shorter lead times and exceptional due
date performance from their suppliers. While certain mass producers of apparel in India operate
world class manufacturing plants with some manufacturers even successfully running Lean and
Six Sigma philosophies, the majority of apparel manufacturers remain small to medium scale
industries with not enough management talent to execute advanced production systems. Plagued
with seasonal demand, high labor turnover and arcane systems, it seems they thrive only on low
labor costs. With even labor costs going up and the increasing availability of higher paying
alternative low skill jobs, these manufacturers must find a way to manage their operations
without heaps of inventory, uncontrollable overtime, quality problems and low due date
performance.
Solutions to these problems have been available since many decades. Taiichi Ohno presented
his Toyota Production Systems based on Just-in-Time concepts in as early as 1988. This has
3
evolved into a management philosophy called Lean Manufacturing and is being actively pursued
by competent apparel manufacturers today. Lean represents a utopian system where no wastes
should exist. From an operational point of view, it’s the ultimate objective. But consider the
plight of small and medium scale made-to-order apparel manufacturers. A lean implementation
requires stability in the system, buy-in at the floor level and a culture of continuous
improvement. Trying to implement Lean concepts in such volatile environments where each and
every order is hot, red-hot or drop-everything-else-and-make-this-urgently hot is certainly not a
pragmatic solution. What is required is a system which can provide this necessary condition of
stability – An operating mechanism which can shorten lead time, reduce inventory and deliver
exceptional due-date performance. In fact, such a mechanism does exist. It is the Theory of
Constraints Drum-Buffer-Rope Scheduling system. This paper explores the applicability of this
system a high-mix/low-volume made-to-order apparel manufacturing environment.
Theory of Constraints, introduced by Dr. Eliyhu M. Goldratt in his book “The Goal” in 1984,
is a management philosophy which advocates a systemic view of the business. It considers the
system as a chain whose strength is governed by its weakest link, the constraint. It implores the
elimination of decision making based on local efficiencies and encourages improving the global
optimum by exploiting the constraint. Drum-Buffer-Rope is the logistical application of Theory
of Constraints – a scheduling system providing planning and controlling methods. Drum-Buffer-
Rope is a relatively simple system and one of its biggest advantages is that it does not require
buy-in at the floor level. Only a higher level buy-in is required for successful implementation.
Enough literature also exist which showcase documented evidence of successful Theory of
Constraints implementation with fast and significant positive results.
4
This paper explores the applicability of Drum-Buffer-Rope to objectively conclude if it is in
fact a practical solution which can deliver high due-date performance even in volatile
environments. It is limited to products which do not require any processing between sewing,
finishing & packing of garments.
1.1. Objectives
Identify the system constraint & develop an exploitation strategy with minimal
changes in current working.
Implement drum-buffer-rope scheduling
Design a constructive control mechanism to monitor drum-buffer-rope
The stability that the system described in this paper can deliver should be used as a
cornerstone to drive a process of ongoing improvement which not only aims to create more
money for the manufacturer but also to develop and evolve production systems while providing
employees with better working conditions and higher wages. Operational stability is the first
hurdle stopping manufacturers from looking beyond seasonal profits and must be addressed
immediately.
5
02. Review of Literature
6
The manufacturing of apparel has evolved to include the application of various production
systems depending on the nature of business and type of product. In the pursuit of running
excellent operations, organizations have implemented various production systems and adapted
different philosophies with varying levels of success and failure. Most of such efforts have been
driven by a primary focus on reducing costs through an emphasis on increasing local
improvements. However, a global focus on improving the overall system is required based on a
logical operating principle with supporting mechanisms to govern local improvements. Before
local improvements can be effectively made, the system must be stabilized on a reliable
operating mechanism. The Theory of Constraints Drum-Buffer-Rope Scheduling applied as the
operating principle to design the overall production system can provide such a system along with
the power of focus. Instead of improving many areas simultaneously, improvement efforts can be
logically directed to the problem areas that affect the system the most. Once the area of focus is
identified, local improvements based on Lean tools and principles can lead to effective and
meaningful results. The following review illustrates the evolution of assembly lines and pull-
systems highlighting their underlying principles and examines literature on the Theory of
Constraints, Drum-Buffer-Rope scheduling, V-A-T plant analysis and the fundamentals of Lean
manufacturing.
2.1 Production Concepts & Applications
The perception of apparel manufacturing is often limited to its certain functions such as
Merchandising, Cutting, Sewing and Finishing. Within this context, the larger picture is often
missed. Made-to-Order apparel manufacturing must be seen as a whole system and not just a
collection of individual departments and it’s most important measure should be Due-Date
Performance. The following excerpts highlight the principles governing manufacturing systems
7
and lead to the rationale of why a Theory of Constraints Drum-Buffer-Rope application can be
very effective in improving the Due-Date Performance of such systems.
“The manufacturing industry has been shaped by two great thinkers, Henry Ford and Taiichi
Ohno. Ford revolutionized mass production by introducing the flow lines. Ohno took Ford’s
ideas to the next level in his Toyota Production System (TPS), a system that forced the entire
industry to change its grasp of inventory from an asset to a liability. Ford’s starting point was
that the key for effective production is to concentrate on improving the overall flow of products
through the operations. If transportation were perfect and an even flow of materials could be
assured, it would not be necessary to carry any stock whatsoever. The carloads of raw materials
would arrive on schedule and in the planned order and amounts, and go from the railway cars
into production. That would save a great deal of money, for it would give a very rapid turnover
and thus decrease the amount of money tied up in materials.”
“Ford’s efforts to improve flow were so successful that, by 1926, the lead time from
mining the iron ore to having a completed car, composed of more than 5,000 parts on the train
ready for delivery, was 81 hours. Eighty years later, no car manufacturer in the world has been
able to achieve, or even come close, to such a short lead time.”
“Flow means that inventories in the operation are moving. When inventory is not
moving, inventory accumulates. Accumulation of inventory takes up space. Therefore, an
intuitive way to achieve better flow is to limit the space allowed for inventory to accumulate. To
achieve better flow, Ford limited the space allotted for work-in-process between each two work
centers. That is the essence of the flow lines, as can be verified by the fact that the first flow lines
8
didn’t have any mechanical means, like conveyers, to move inventory from one work center to
another.”
“The daring nature of Ford’s method is revealed when one realizes that a direct
consequence of limiting the space is that when the allotted space is full, the workers feeding it
must stop producing. Therefore, in order to achieve flow, Ford had to abolish local efficiencies.
In other words, flow lines are flying in the face of conventional wisdom; the convention that, to
be effective, every worker and every work center have to be busy 100% of the time. One might
think that preventing resources from working continuously will decrease throughput (output) of
the operation. That undesirable effect might have been the result if Ford would have been
satisfied with just limiting the space. But, there is another effect that stems from restricting the
accumulation of inventory. It makes it very visible to spot the real problems that jeopardize the
flow – when one work center in a line stops producing for more than a short while, soon the
whole line stops. Ford took advantage of the resulting clear visibility to better balance the flow
by addressing and eliminating the apparent stoppages. The end result of abolishing local
efficiencies and balancing the flow is a substantial increase in throughput. Henry Ford achieved
the highest throughput per worker of any car manufacturing company of his time.” 01.A
Like Ford, Ohno’s primary objective was improving flow – decreasing lead time – as
indicated in his response to the question about what Toyota is doing:
“All we are doing is looking at the time line from the moment the customer gives us an order
to the point when we collect the cash. And we are reducing that time line…”
Ohno established the Toyota Production System to achieve flow by focusing on removing
wastes. In his works, Ohno gives full credit for the underlying concepts to Ford. The original
9
emphasis on the importance of identifying and removing wastes was stated by Ford in a chapter
titled “Learning from Waste” 02 –
“Conserving our natural resources by withdrawing them from use is not a service to the
community. That is holding to the old theory that a thing is more important than a man. Our
natural resources are ample for all our present needs. We do not have to bother about them as
resources. What we do have to bother about is the waste of human labor.”
“Take a vein of coal in a mine. As long as it remains in the mine, it’s of no importance,
but when a chunk of that coal has been mined and set down in Detroit, it becomes a thing of
importance, because then it represents a certain amount of the labor of men used in its mining
and transportation. If we waste that bit of coal - which is another way of saying if we do not put
it to its full value — then we waste the time and energy of men. A man cannot be paid much for
producing something which is to be wasted.”
“My theory of waste goes back of the thing itself into the labor of producing it. We want to
get full value out of labor so that we may be able to pay it full value. It is use — not conservation
— that interests us. We want to use material to its utmost in order that the time of men may not
be lost. Material costs mean nothing. It is of no account until it comes into the hands of
management.”
“Saving material because it is material, and saving material because it represents labor might
seem to amount to the same thing. But the approach makes a deal of difference. We will use
material more carefully if we think of it as labor. For instance, we will not so lightly waste
material simply because we can reclaim it — for salvage involves labor. The ideal situation is to
have nothing to salvage.”
10
“We have a large salvage department, which apparently earns for us twenty or more million
dollars a year. But as that department grew and became more important and more strikingly
valuable, we began to ask ourselves: Why should we have so much to salvage? Are we not
giving more attention to reclaiming than to not wasting?”
“And with that thought in mind, we set out to examine all our processes. A little of what we
do in the way of saving manpower by extending machinery has already been told, and what we
are doing with coal, wood, power and transportation will be told in later chapters. This has to do
only with what was waste. Our studies and investigations up to date have resulted in the saving
of 80,000,000 pounds of steel a year that formerly went into scrap and had to be reworked with
the expenditure of labor. This amounts to about three million dollars a year, or, to put it in a
better way, to the unnecessary labor on our scale of wages of upward of two thousand men. And
all of that saving was accomplished so simply that our present wonder is why we did not do it
before.”
Ohno expanded this understanding to modern manufacturing and identified seven wastes,
whose elimination forms the backbone of Lean thinking. Ohno introduced these wastes in the
section titled “Complete Analysis of Waste” 03-
“Modem industry seems stuck in this way of thinking. A person in business may feel uneasy
about survival in this competitive society without keeping some inventories of raw materials,
work-in-process, and products.”
“This type of hoarding, however, is no longer practical. Industrial society must develop the
courage, or rather the common sense, to procure only what is needed when it is needed and in the
amount needed.”
11
“This requires what I call a revolution in consciousness, a change of attitude and viewpoint
by business people. In a period of slow growth, holding a large inventory causes the waste of
overproduction. It also leads to an inventory of defectives, which is a serious business loss. We
must understand these situations in-depth before we can achieve a revolution in consciousness.”
“When thinking about the absolute elimination of waste, keep the following two points in
mind”:
1. Improving efficiency makes sense only when it is tied to cost reduction. To achieve
this, we have to start producing only the things we need using minimum manpower.
2. Look at the efficiency of each operator and of each line. Then look at the operators as
a group, and then at the efficiency of the entire plant (all the lines). Efficiency must
be improved at each step and1 at the same time, for the plant as a whole.
“Let’s say, for instance, one production line has 10 workers and makes 100 products per day.
This means the line capacity is 100 pieces per day and the productivity per person is 10 pieces
per day. Observing the line and workers in further detail, however, we notice overproduction,
workers waiting, and other unnecessary movements depending on the time of day.”
“Suppose we improved the situation and reduced manpower by two workers. The fact that 8
workers could produce 100 pieces daily suggests that we can make 125 pieces a day, increasing
efficiency without reducing manpower. Actually, however, the capacity to make 125 pieces a
day existed before but it was being wasted in the form of unnecessary work and overproduction.”
12
“This means that if we regard only work that is needed as real work and define the rest as
waste, the following equation holds true whether considering individual workers or the entire
line: Present Capacity = Work + Waste”
“True efficiency improvement comes when we produce zero waste and bring the percentage
of work to 100 percent. Since, in the Toyota production system, we must make only the amount
needed, manpower must be reduced to trim excess capacity and match the needed quantity.”
“The preliminary step toward application of the Toyota production system is to identify
wastes completely”:
1. Waste of overproduction
2. Waste of time on hand (waiting)
3. Waste in transportation
4. Waste of processing itself
5. Waste of stock on hand (inventory)
6. Waste of movement
7. Waste of making defective products
“Eliminating these wastes completely can improve the operating efficiency by a large
margin. To do this, we must make only the quantity needed, thereby releasing extra manpower.
The Toyota production system clearly reveals excess manpower. Because of this, some labor
union people have been suspicious of it as a means of laying off workers. But that is not the
idea.”
13
“Management’s responsibility is to identify excess manpower and utilize it effectively.
Hiring people when business is good and production is high just to lay them off or recruiting
early retirees when recession hits are bad practices. Managers should use them with care. On the
other hand, eliminating wasteful and meaningless jobs enhances the value of work for workers.”
“Ohno was fully aware that there were too many things that can be improved, that without a
way to focus the process improvement efforts it would take too long to balance the flow. The
Kanban system provided him such a way. Between each two work centers and for each
component separately, the accumulation of inventory is limited by setting a certain number of
containers and the number of units per container. These containers, like every container in every
industry, also contain the relevant paperwork. But, one page of the paperwork – usually a card
(kanban in Japanese) – a page that specifies only the component code name and the number of
units per container, is treated in an unconventional way. When the succeeding work center
withdraws a container for further processing that card is not moved with the container, rather it is
passed back to the preceding work center. This is the notification to that work center that a
container was withdrawn, that the allotted inventory is not full. Only in that case is the preceding
work center allowed to produce (one container of parts specified by the card). In essence the
Kanban system directs each work center when and what to produce but, more importantly, it
directs when not to produce. No card – no production. The Kanban system is the practical
mechanism that guides the operation when not to produce prevents overproduction. Ohno
succeeded to expand Ford’s concepts by changing the base of the mechanism from space to
inventory.” 01.B
The underlying concepts adopted by Ford and Ohno stated as the concepts of supply chains -
14
1. Improving flow (or equivalently lead time) is a primary objective of operations.
2. This primary objective should be translated into a practical mechanism that guides the
operation when not to produce (prevents overproduction). Ford used space; Ohno
used inventory.
3. Local efficiencies must be abolished.
4. A focusing process to balance flow must be in place. Ford used direct observation.
Ohno used the gradual reduction of the number of containers and then gradual
reduction of parts per container.
The Limitations of TPS -
1. TPS is restricted to relatively stable environments,
2. Most environments suffer from instability, and
3. Relatively unstable environments have much more to gain from better flow than even
stable environments.
“The most intuitive base for the mechanism to restrict over-production is not space or
inventory but time – if one wants to prevent production ahead of time one should not release the
material ahead of time. Using time as the base is not only more intuitive and, therefore, more
easily accepted by the shop floor, it has an advantage that makes it suitable for unstable
environments – it is much less sensitive to disruptions in flow. The robustness of the time-based
mechanism stems from the fact that it directly restricts the overall amount of work in the system
rather than doing it through restricting the amount of work between each two work centers. In
flow lines or Kanban-based systems the allotted inventories between work centers is restricted to
the bare minimum (usually corresponding to much less than one hour of work). Therefore, when
15
a work center is down for more than a short while the succeeding work centers are almost
immediately starved for work and the preceding work centers are “blocked” from working.
When, for any of the work centers, the accumulated time consumed by starvation and blockage is
more than the excess capacity of that work center, the throughput of the company is reduced. The
sensitivity of flow lines and Kanban-based systems stems from the fact that a disruption that
occurs in one work center consumes capacity also from the upstream and downstream work
centers – a phenomenon that (almost) doesn’t exist for the time-based systems since the work,
once released to the floor is not artificially restrained. The time based application of the supply
chains concept is the Theory of Constraints Drum-Buffer-Rope system.” 01.C
“Many claims were made regarding the benefits of TOC. These included: increased
Throughput (i.e., Revenue—Totally Variable Costs), reduced inventories, and reduced lead-
times, which in turn would lead to higher sales, and improvements in profits, quality, and
customer satisfaction. We felt it would be useful to collect together and analyze the actual
reported data on the benefits of TOC, to verify or disprove these claims. The literature search
identified over 100 case studies or vignettes that contained information on the results of
applications of TOC. Not all of these provided quantitative data on the results of applying TOC.
In total, we were able to collect quantitative data on the application of TOC to 82 different
companies. The types of organizations covered by these cases varied from giant multi-national
corporations and industry leaders like Boeing and General Motors, to military organizations like
the U.S. Air Force to small town bakeries.” 04
The results of the analysis of reported changes in operational and financial performance,
resulting from the application of TOC, are summarized below:
16
Lead Time Mean Reduction – 70%
Inventory Level Mean Reduction – 49%
Revenue/Throughput/Profit Mean Increase – 76%
The export oriented apparel manufacturing industry works in a make-to-order environment.
A classical measure of the performance of systems in such an environment is due-date
performance. Previous literature has demonstrated that due-date performance can be improved
by effective management of order release, working priorities, and bottlenecks.
“Our experimental study examined why high due-date performance is difficult to achieve.
Thirty teams participated in the first experiment and five teams in the second experiment
(involving a total of 245 people). Our results support the notion that in most cases, variability is
not the root cause of poor due-date performance. Poor due-date performance is caused by the
mode of managing operations, including the following phenomena” 05:
1. Over-promising, or setting order due dates that fail to consider the planned load of the
constraint;
2. Not choking the order release, which results in too many orders on the shop floor due
to excessively early release, a situation that masks priorities, promotes local optimal
behavior, prolongs lead time, and significantly disrupts due-date performance;
3. Failure to manage priorities, resulting in hectic priorities that create chaos on the floor
and lead to late orders.
“Based on our findings, due-date performance improvement programs should first focus on
improving the management of production planning and execution, instead of reducing
variability.” 05
17
Drum-Buffer-Rope, a Theory of Constraints planning & scheduling solution is a time-based
application of the supply chains concept. The fundamental assumption is that within any plant
there is one or a limited number of scarce resources which control the overall output of that
plant. This is the “drum” which sets the pace of all other resources. In order to maximize the
output of the system, planning and execution behaviors are focused on exploiting the drum,
protecting it against disruption through the use of “time buffers” and synchronizing or
subordinating all other resources and decisions to the activity of the drum through a mechanism
that is akin to a “rope”. 06
Figure 2.1 Relationship between management time required and the time buffer size. 01.D
18
2.2. Theory of Constraints
It has been said;; “Tell me how you will measure me, and I will tell you how I will behave”
07.A The whole internal business performance measurement system is based upon local
optimization, either in the form of departmental utilization/efficiency measures or as
departmental cost/profit performance measures - or both. It takes some conscious effort to
realize that the formalization of local efficiency measures through the activities of scientific
management is only about 100 years old. 08 Its assumed that the total performance of the system
is the sum of all the local performances. In fact it is so common that it is not even given much
thought. This approach then is the reductionist/local optima approach; departmental cost or
efficiency is just a symptom or an output of this method. 09
“Living systems have integrity. Their character depends on the whole. The same is true for
organizations; to understand the most challenging managerial issues require seeing the whole
system that generates issues.” 10 It should be known what the system is that one is dealing with,
where does it start, and where does it end. It should be known what the system exists for, and
how to measure progress towards the reason for its existence. Scheinkopf expresses this as 11:
1. Define the system and its purpose.
2. Determine the system’s fundamental measurements.
The organization in fact defines the measurements rather than the other way around – the
measurements define the organization. Margaret Wheatley is more articulate. She argues that in
too many organizations “… the measures define what is meaningful rather than letting the
greater meaning of the work define the measures. As the focus narrows, people disconnect from
any larger purpose and only do what is required of them.” 10
19
The fundamental measures for a system must be determined and then ensured that
performance measures are subordinated to these fundamental measures. “Not just any
measurements, but measurements that will enable us to judge the impact of a local decision on
the global goal.” 07.B
“Measurements are a direct result of the chosen goal. There is no way that we can select a
set of measurements before the goal is defined.” The measurements should enable the judgment
whether a local decision has an impact on the global goal. 07.C
In a commercial organization the fundamental measures are defined by the following
questions 07.D:
1. How much money is generated by the company?
2. How much money is captured by the company?
3. How much money is spent to operate it?
Goldratt calls these 3 measures; Throughput, Inventory, and Operating Expense. These are
often shortened to T, I, and OE and are defined as follows 07.E:
1. Throughput is the rate at which the system generates money through sales.
2. Inventory is all the money that the system invests in purchasing things which it intends to
sell.
3. Operating expense is all the money the system spends in order to turn inventory into
throughput.
20
2.3. V/A/T Analysis & Synchronous Manufacturing
Serial processes where there are dependencies between one step and another are a relatively
new phenomenon. Prior to the industrial revolution such organizations did not exist. Since the
beginning of industrial revolution many have done little more than become larger and more
complicated as they take advantage of economies of scale and economies of scope. 08
In a process where similar machines, or people who are doing similar operations, are grouped
together, work moves in a sequence between these specialist areas, sometimes flowing back the
way it came to a previous area before continuing on in the process. This layout is known as a
“job shop.” A simple example might be a small engineering firm. Each job in the process could
be unique or it could be a repetition of a standard design. Each job could consist of single unit or
a batch of many units. 09
At the other end of the scale from the job shop is a “flow shop.” Here machinery or people
are sequenced throughout the plant in the order that most work will require. Again the work
might be unique or a repetition of a standard design. Each job could consist of a single unit or a
batch of many units. 09
Furniture companies that produce for the retail trade are usually a flow shop. Tool bit
manufacturers are another example. So too are electronics and automotive, however, as the
diversity of products decreases and the batch size increases the flow in parts of these flow shops
becomes more and more continuous. Ultimately these parts may become a dedicated flow shop
– one flow or process for one product or product family. 09
So, why can’t these flow shops become truly continuous, like a pulp and paper plant, or a
petrochemical process? The answer is that the items in the process are discrete, made of
21
individual parts, rather than non-discrete like a liquid or a crushed ore. In fact many of the truly
continuous industries are in the primary or extractive industries – pulp and paper, petrochemical,
and dairy. Most of these industries benefit from economies of scale and are capital intensive
with a concomitant reduction or replacement of labor. 09
Within the discrete product job shop and flow shops there are 3 basic topologies which
describe the flow of material within the process. V/A/T plant classification was developed
primarily by Eli Goldratt. Around 1980, while running a consulting organization called Creative
Output, Goldratt noticed that manufacturing plants in very different industries seemed to have
similar characteristics and problems. From this experience he developed the V/A/T classification
system. 12
Product flow diagrams are used to determine the structure of a plant. Three specific
categories of points are of special interest in product flow diagrams: divergence points,
convergent assembly points, and divergent assembly points. Divergence points are steps in the
product flow at which material may be transformed into two or more distinctly different
materials. Convergent assembly points are points at which two or more component parts are
assembled to form a single parent item. Divergent assembly points occur when a number of
common component parts may be combined or assembled in a variety of ways to form a large
number of possible parent items. The product flow diagram of a specific manufacturing
environment may include divergence points, convergent assembly points, and divergent
assembly points. However, one of these three categories will usually dominate. This observation
led to the development of three basic plant classification categories: V-plants, A-plants and T-
plants. 13
22
Product flow diagrams for V-plants are characterized by divergence points throughout the
production process. In such plants, a single piece of material can be increasingly transformed at
each divergence point into a very large number of distinctly different end items. The general
shape of the product flow diagram resembles the letter "V," hence the designation V-plant. 13
A-plants are characterized by convergent assembly points throughout the process. In such
plants, a large number of purchased or fabricated component parts and materials are combined to
form subassemblies that are used to build unique end products. Several levels of subassemblies
are typically necessary before final assembly can be performed. The typical product flow
diagram for a plant exhibiting this basic convergence process resembles a pyramid. Hence, the
designation A-plant. 13
T-plants are dominated by a major divergent assembly point at final assembly, where many
different end items are assembled from a relatively limited number of component parts, many of
which are common to numerous end items. In T-plants, the critical resource and product
interactions take place at final assembly, where the product structure expands to yield a large
variety of assembled products. The narrow component base, coupled with the very expansive top
portion representing the end item configurations, give rise to a product flow diagram that
resembles the letter "T." 13
Both the Ford production system and the Toyota production have a commonality in their
implicit treatment of the constraint or slowest step. Both systems seek to synchronize the
remainder of the system to the slowest step, either by a physical moving line or by kanban
cards. The constraint, in-turn, can be synchronized to the external market demand.
23
Exploitation of these systems occurs via “line balancing” and also by inventory reduction in
just-in-time.
The Theory of Constraints production solution, drum-buffer-rope, in contrast is explicit in its
recognition of the existence of constraints. As such, only the key control points of raw material
release, points of convergence or divergence, the constraint, and shipping need to be “tied”
together by the logistical system. The mechanism to tie the points together is a time-phased
schedule.
Because drum-buffer-rope explicitly recognizes the constraint and exploits it’s capability to
the full, drum-buffer-rope is able to operate at any product volume or level of diversity.
Umble and Srikanth recognize the similarities of the Ford production system, Toyota
production system and drum-buffer-rope under the term synchronous manufacturing. In this
classification, the Ford production system and the Toyota production system can be viewed as
partial implementations, or sub-sets, of synchronous manufacturing and drum-buffer-rope as a
full set of the capabilities. 14
2.4. Drum-Buffer-Rope Scheduling
Senge described the “where we are now” as the current reality, and the “where we want to be
in the future” as the vision. 15 He noted that if there was no gap between the current reality and
the vision, then there would be no need to move toward the vision. The gap between the two
becomes a source of creative energy which he termed “creative tension.”
But that doesn’t actually help to move forward. In fact Senge notes that “creative tension
often leads to feelings or emotions associated with anxiety, such as sadness, discouragement,
24
hopelessness, or worry.” Senge described this as “emotional tension.” The key point is not to
confuse creative tension with emotional tension, otherwise we predispose ourselves to lowering
our vision. 15 We need a process of change to ensure that we move from where we are now to
where we want to be in the near future.
Goldratt briefly outlined a process of change in 1990. 16 He characterized it as follows;
1. What to change.
2. What to change to.
3. How to cause the change.
Goldratt furnished a focusing process in the earliest versions of The Goal, however, it was
implicit. In later editions it was made explicit as the five focusing steps. The five focusing
steps, exactly as in the original verbalization, are as follows 17:
1. Identify the system’s constraints.
2. Decide how to exploit the system’s constraints.
3. Subordinate everything else to the above decision.
4. Elevate the system’s constraints.
5. If in the previous steps a constraint has been broken, Go back to step 1, but do not allow
inertia to cause a system constraint.
Proper subordination is the key to effective implementation of Theory of Constraints. Proper
subordination means that the non-constraints only do what is required to ensure maximum
exploitation of the constraint. It needs to be ensured that the parts are subordinated to the whole,
or more correctly in larger-scale enterprises, that the subsystems are subordinated to the system.
25
Once an exploitation plan has been decided upon, there are two ways to deviate from this
plan. 13 Deviating from the plan means improper subordination and consequently less than fully
effective exploitation. Deviation from the plan results from:
1. Not doing what was supposed to be done.
2. Doing what was not supposed to be done.
Drum-buffer-rope is the Theory of Constraints production application. It is named after the 3
essential elements of the solution; the drum or constraint or weakest link, the buffer or material
release duration, and the rope or release timing. The aim of the solution is to protect the weakest
link in the system, and therefore the system as a whole, against process dependency and variation
and thus maximize the systems’ overall effectiveness. The outcome is a robust and dependable
process that allows more production with fewer inventories, less rework/defects, and better on-
time delivery.
Drum-buffer-rope however is really just one part of a two part act. If drum-buffer-rope is the
motor for production, then buffer management is the monitor. Buffer management guides the
way in which the motor is tuned for peak performance.
In determining the buffer, the rule of thumb to apply is to halve the existing lead time. 18 To
this buffer, a second rule of thumb is applied. The buffer is divided into zones of one third each.
19 Most work is expected to be completed in the first 2 thirds and be waiting in front of the
constraint for the last third of the buffer time.
For all practical purposes the “time buffer” is the time interval by which the release of work
is predated, relative to the date at which the corresponding constraint’s consumption is
26
scheduled. 7.8 The zones equate to time allocated in the plant to protecting an operation whose
position and function is critical to the timeliness and output of the whole process. The zones do
not equate to the position of work in the plant.
“The reason buffers are defined as the whole lead time and not just the safety portion is that
in most manufacturing environments there is a huge difference between the sum of the net
processing times and the total lead time. When we review the net processing time of most
products, we find it takes between several minutes and an hour per unit. But the lead time may
be several weeks, and even in the best environments several days. Consequently, each unit of
product waits for attention somewhere on the shop floor for a much longer time than it actually
takes to work on it.” “So it makes sense not to isolate the net processing time, but to treat the
whole lead time as a buffer – the time the shop floor needs to handle all the orders it must
process.” 21.A
The above paragraphs describe the operations system in Drum-Buffer-Rope. To ensure its
stability, a monitoring system is also required. This is done through buffer management. Buffers
and their purpose have already been discussed, however a mechanism is required to interpret and
utilize the information that they can provide. And in order to do that, their impact must be
divided into two distinct functions. They are as follows;
1. Local Control - the day-to-day exception reporting that indicates when there may be a
potential due date violation.
2. Global Feedback - longer term trend-reporting that suggests a particular buffer needs to
be resized to be fully effective.
27
Buffer management is crucial; it filters important signals from the day-to-day noise of the
system thereby alerting the potential problems before they become real problems and it provides
a self-diagnosis that neither too much and nor too little protection is made available for each
case. The self-diagnosis feeds back into our configuration and guides improvements in the
overall dynamics of the implementation.
Thus, control is also implemented along with planning, but it is local and within the context
of the overall design of the implementation. Schragenheim & Dettmer have an important
definition of control 21.B:
“A reactive mechanism that handles uncertainty by monitoring information that indicates a
threatening situation and taking appropriate corrective action before the threat is realized.”
Consider the rock and water analogy. The water level corresponds to the inventory level,
while the rocks are the problems disturbing the flow. There are many rocks at the bottom of the
river and it takes time and effort to remove them. The question is which rocks are important to
remove. The answer is given by reducing the water level; those rocks which emerge above the
water are the ones that should be removed. The drum-buffer-rope operating model controls the
inventory level through time buffers while Buffer management provides a constructive control
mechanism which makes it possible to focus on areas which cause problems in the productivity
of the system. This Theory of Constraints application can provide operating stability with high
due-date performance in made-to-order apparel manufacturing firms. This stability is the most
basic requirement to drive any further improvements which add to the bottom line and are
sustainable.
28
2.2 List of References
1. Goldratt (2009), 334, 335, 341, 339 2. Ford (1926), 89 3. Ohno (1988), 18-20 4. Mabin & Balderstone (2000), 10-12 5. Lee, Hwang, Wang & Lee (2009), 42 6. Woeppel (2000), 1 7. Goldratt (1990), 26, 10, 14, 19, 23 8. Johnson & Kaplan (1987), 217, 49-57 9. Youngman (2005) 10. Wheatley & Kellner-Rogers (1999) 11. Scheinkopf (1999), 23-24 12. Cox & Spencer (1998), 101-128 13. Umble & Umble (1999) 14. Umble & Srikanth (1995), 211-255 15. Senge (1990), 150-151 16. Goldratt, E.M (1990), 3-21 17. Goldratt & Cox (1986), 307 18. Goldratt (1997), 149 19. Stein (1996), 143 20. Schragenheim & Dettmer (2000), 123-135, 176
* Citations for the above mentioned authorities are provided in chapter 09: Bibliography
29
03. Methodology
30
This paper explores the applicability of a Theory of Constraints Drum-Buffer-Rope operating
mechanism for production in a low-volume/high-mix made-to-order apparel manufacturing
environment to establish a proactive planning & constructive control system that ensures high
due-date performance along with higher throughput, lower inventory and lower operating
expense.
3.1. Scope of Research
The research is limited to scheduling only production processes after the purchase of raw
material; grey fabric in this particular case. Purchase of trims & accessories is not explicitly
handled and is limited to monitoring with respect to deadlines for getting materials in-house.
3.2. Assumptions
Purchase of raw materials is still largely based on the archaic1 notion of buying stocks when
prices are low and buying restrictively when prices are high. Due to this sporadic nature of raw
material purchases, it has not been included in the planning & control system described in this
paper. It has been assumed that raw material i.e. Grey Fabric is readily available whenever it is
required for further processing. Trims & accessories are also assumed to be available for
production as and when required.
3.3. Constraints
Theory of Constraints advocates that each system is a chain of dependent processes. The
strength of this chain is governed by the weakest link, the bottleneck or constraint. As discussed
1 “We have carefully figured, over the years, that buying ahead of requirements does not pay--that the gains on one purchase will be offset
by the losses on another, and in the end we have gone to a great deal of trouble without any corresponding benefit. Therefore in our buying we
simply get the best price we can for the quantity that we require. We do not buy less if the price be high and we do not buy more if the price be
low.” – Henry Ford in “My Life & Work”, 1922
31
earlier in section 2.4, identifying this constraint is the first step to any Theory of Constraints
application.
3.3.1. Identifying the Constraint
A cursory glance at the various departments to identify any potential bottlenecks revealed
that few processes had much more capacity than certain others. Four departments/processes in
particular emerged as potential constraints and were studied to find if any one of them could be
conclusively considered as the constraint.
The daily outputs of these four processes were recorded for a period of 26 days. During this
period, 85% of the output constituted of three different styles with shipment dates varying within
a week from one another. All three styles were floated on the floor considerably simultaneously.
However, to ease out any slight fluctuations in the output of the processes due to variation in
styles a 3 day moving average was used for comparing them. This comparison is illustrated in
appendix A.
The above comparison revealed that a single constraint does not exist. Instead, all of the four
processes exhibited close to equal probability of becoming the bottleneck which over a period of
time led to travelling constraints i.e. the constraint laid at a different process every day. Since an
application of Drum-Buffer-Rope scheduling necessitates the existence of a definite constraint,
this dilemma prompted the need to design a constraint.
3.3.2. V/A/T and 5 Why Analysis
V/A/T analysis has been discussed earlier in section 2.3. In the pursuit of designing the
constraint, a V/A/T analysis was conducted to figure out the logical structure of the plant. The
32
divergence and convergent points of materials were plotted and the entire structure is presented
in appendix B. This analysis revealed that there were complex dependencies in the four
processes causing travelling constraints as discussed in section 3.3.
A 5-Why analysis was conducted on these four processes to highlight the existence of
wastes2 and to determine the root causes of problems through cause and effect logic. The
tabulation of the analysis along with a Pareto analysis of the root causes are presented in
appendices C.1 to C.5.
The above analysis suggested that the departmental barriers within the four processes should
be broken and instead of a serial structure, the four processes should be combined into a
continuous process. Creating such a continuous process of consolidated functions could also
disentangle the logical structure of the plant by creating parallel assembly processes thus creating
a definitive T plant as shown in appendix D. Essentially, the 4 serial processes causing travelling
constraints were broken down into smaller consolidated parallel processes creating manageable
independent constraints which would act as drums3 to base the drum-buffer-rope scheduling
system on.
3.3.3. Design of Constraint
Once established that the constraint must be designed by creating consolidated processes, the
feasibility of such an environment was studied. The four processes considered for consolidation
were sewing, thread cutting, finishing and packing.
2 Production Wastes as described in section 2.1
3 A Drum is a constraint in the system which determined the pace of the overall system.
33
Thread cutting was considered to be a wholly non-value adding process. Operators in sewing
stage should cut the threads after finishing each operation from the root so as to eliminate the
need for a separate thread cutting process. To test its feasibility, a time study was conducted on
different operations of a style to identify the average increase in operation time due to this added
responsibility (appendix E). The two approaches – incorporated thread cutting & separate thread
cutting were compared on 3 measurements to conclusively determine if eliminating thread
cutting as a separate process was truly beneficial (appendix F).
With the thread cutting process eliminated, sewing, finishing & packing remained to be
consolidated. Lean production has the potential to create a high velocity cell but the environment
of the plant which involves high labor turnover, seasonal demand and very diverse product mix
limited4 its application. However, a virtual consolidation was still possible. This did not require
any major spatial rearrangement, only a reconfiguration of how material was moved between
these processes. This was achieved by creating two assembly lines in the finishing floor which
could handle finishing & packing on a continuous basis. Each such line was dedicated to work
which it received from a particular sewing line on an hourly basis.
Two such virtually consolidated drums were created and six orders were executed on them
from the point of grey material release to shipment. These pilot runs were considered as the basis
for creating a case for the superiority of drum-buffer-rope scheduling.
3.4. Applying Drum-Buffer-Rope
Drum-Buffer-Rope has been discussed in section 2.4. It is the operating principle, the motor
which drives production. It was applied through the steps described in the following sections.
4 Limitation of TPS as discussed in section 2.1
34
3.4.1. Establishing Time Buffers
The buffer is the time from the release of material to the time it is due at the drum. As a rule
of thumb, this time is established by halving the present lead time between these two points. The
lead times were determined for various product routings in order to arrive at the time buffer for
drum-buffer-rope scheduling. These times were determined by tracking certain orders as they
progressed through production (appendix G.1 to G.9) and finding the median lead time for
outsourced processes through analysis of historical data.
This time buffer protects against variation in the processes before the drum. To protect
against any variations inside the drum, another buffer called the shipping buffer was used. This
time buffer was the time from the end of the drum to shipping.
3.4.2. Creating a Drum Schedule
For each of the two drums, specific schedules for executing the six orders were created. In
order to create the schedule, the work content of the product was required. In order to determine
the robustness of new system, two approaches were applied to derive the work content:
1. Time study was employed to arrive at a scientific estimate of the work content.
2. Intuition of line masters was used to arrive at average hourly output estimates.
This drum schedule determined the material release for these orders by deducting the time
buffers from the due date at the drum. This link between material release and drum schedule is
known as the rope which prevents excess inventory in the factory.
35
3.4.3. Buffer Management
Buffer management is the monitoring arm of drum-buffer-rope. It is the throttle which keeps
the drum-buffer-rope motor running, tweaking it whenever necessary. It is executed by dividing
the time buffer into three equal zones and monitoring released orders accordingly. It has been
described in section 2.4.
The orders which reach the red zone are assessed. The problem for their lateness is identified
and recorded. At the end of the pilot runs, a Pareto analysis of these occurrences was done to
identify problem areas. Such analysis provides focus to direct any improvement efforts at non-
constraints.
An analysis on the buffer status of all the orders was also done to check if the time buffers
established were less, sufficient or too generous. This allows scientific base gradual reduction of
work-in-process.
3.4.4. Comparison of Existing & Proposed Systems
An objective comparison was made between the existing and proposed systems. This
comparison, amongst others consists of the following Theory of Constraints measurements:
1. Throughput - Throughput is the rate at which the system generates money through sales.
2. Inventory - Inventory is all the money that the system invests in purchasing things which
it intends to sell.
3. Operating Expense - Operating expense is all the money the system spends in order to
turn inventory into throughput.
36
These measures were would be valid when the entire operation is run on drum-buffer-rope.
Since the implementation presented in this paper was limited to pilot runs on two drums, it could
not be compared to the ongoing system on these measures. Thus the comparison was made on
lead times and on-time-in-full deliveries.
The methodology is largely based on generic principles but had to be configured to a certain
degree in order to be valid in the environment of the system of implementation. Overall, the
methods described above can easily be replicated at any other made-to-order apparel
manufacturing firm.
37
04. Constraints
38
Businesses are run by entrepreneurs. Entrepreneurs are driven by a sense of purpose. In the
realm of small and medium scale apparel manufacturers in the country who export to almost all
major markets in the world, this purpose is limited to making monetary gains. With cheap labor
available, operational practices have rarely evolved to reflect the technology and knowledge
available in the new century. A survey of garment factories conducted in the NCR region
presents a sorry state of factories in one of the more mature readymade garment manufacturing
hubs in the country (Annexure A). It might be the certitude of cheap labor that prevents business
owners to look beyond profits and invest on people, but this condition might not exist after ten
years. The cost of labor is increasing yet systems in garment factories are not keeping pace.
SMEs in the sector might well be on the verge of obsolescence by the end of the next decade.
This myopia must be eliminated; to keep the business profitable and preserve the economic
benefits this industry services the country.
Ford described the true industrial idea as not to make money but to express a serviceable
idea, to duplicate a useful idea, by as many thousands as there are people who need it. The
industrial idea exists to spread prosperity. As Ford puts it, prosperity is not measured by the bank
balance of the manufacturer but by the comfort of the people at large. Businesses execute this
industrial idea and the ultimate goal of any business, as Goldratt puts it, is to make money in the
present as well as in the future. A truly sustainable business will only exist when it continues to
make money while contributing to increasing the comfort of its people.
What then is stopping apparel SMEs from becoming truly excellent? - The ubiquitous
obsession with costs. This emphasis that management puts on cost leads to management thriving
to improve local efficiencies. The underlying assumption being that improvement in local
efficiencies adds up to increase the global performance of the business. It is this assumption that
39
must be challenged. Goldratt argues that every business is a system and every system has at least
one constraint which determines the overall performance of the system. Consider the system to
be a chain. The local optima approach measures the performance of this chain by its weight.
Increasing the weight of each link increases the overall weight. But this measure is wrong. The
performance of the chain should be determined by its strength, not weight. This strength is
determined by the strength of the weakest link. Thus in a system of dependent processes, its
performance is determined by the weakest process, the constraint. Theory of Constraints works
on this principle and advocates that systems must be managed by their constraints. The following
example illustrates this concept:
Product X is manufactured by starting with Raw Material X and then processing it sequentially through 5
operations using machines A to E respectively. This is the only use that the five machines are put to. The hourly rates for each machine are given in the table.
Operation 1 2 3 4 5
Machine M/C A M/C B M/C C M/C D M/C E Hourly Unit Output Rate 100 80 40 60 90
This begs a number of questions to help answer, "Why manage by constraints?”
Question Answer What is limiting the System?
What is the maximum output per hour of Product X? 40 M/C C
By how much would the output be improved if B was increased to 90? No Improvement M/C C
By how much would the output be improved if C was increased to 50? By 10 M/C C
By how much would the output be improved if C was increased to 70? By 20 M/C D
What effect on the system if M/C A can only manage an output of 90 in one hour? None M/C C
What effect on the system if M/C C can only manage an output of 30 in one hour?
We lose 10 Product X M/C C
What effect on the system if M/C B is allowed to drop to an output of 30 in one hour?
We lose 10 Product X
M/C B for that hour. Note also that the loss cannot be recovered.
40
This paper explores the practical applicability of the Theory of Constraints in a high-
mix/low-volume made-to-order apparel manufacturing environment through its logistical
solution known as Drum-Buffer-Rope Scheduling to deliver high due-date performance with
increased throughput and lower inventories. The first step to execute this Theory of Constraints
application was to identify the system’s constraint.
4.1. Identifying the System’s Constraint
A typical garment manufacturer’s system comprises of the following processes –
Procurement
Cutting
Sewing
Thread Cutting
Finishing
Packing
Dispatch
In addition to the above processes, the plant at which the research was carried out housed a
process of smocking. This plant manufactures women’s dresses, skirts, tops and blouses across a
wide range of printed and dyed fabrics. Grey fabric is purchased in bulk and large stocks are
maintained. This serves the dual purpose of ensuring quality of the raw material as well as
making cost gains due to bulk purchasing at lower prices. They grey fabric is issued to various
printers in nearby districts and to dyers within the city. After the receipt of fabric, it is checked in
the printed fabric warehouse. Checked and approved fabric is issued to cutting which is carried
out on piece rate by contractors. A bird’s eye view of how the company works is shown below.
41
Trims & Accessories
Purchase
Grey Fabric Purchase
Supplier
Reject
Accept
Issue to Printing Printer
Reject
Accept
Trims & Accessories Store Cutting Smocking
Sewing
Finishing
Packing
Dispatch
Figure 4.1 Flowchart of Processes at MA’AM Arts, Jaipur
Check
Check
42
Printing, cutting and smocking are all outsourced processes and do not present a capacity
constraint on the system. Thus, the remaining four departments of sewing, thread cutting,
finishing and packing were examined to find which one of them was the constraint.
The daily outputs of all the four departments were recorded for a period of 26 days from 8th
March to 7th April, 2010. During this period of study, the following orders were produced.
Style No. Description Quantity
UU76786 Women’s Top 42000 AT91007-3 Women’s Top 23500
8R465 8 Tier Skirt 38000 8P520 Women’s Dress 4000 8P255 Women’s Dress 3200 8P264 5 Tier Skirt 2800 8N288 Maxi Dress 2000 Total 115500
Table 4.1 Style Produced between 8th March, 2010 and 7th April, 2010
Source: MA’AM Arts, Jaipur
The above table shows that almost 85% of the total quantity produced in this period
comprised of only 3 styles – UU76786, AT91007-3 and 8R465. To compensate for any
fluctuations in daily outputs, a 3 day moving average was considered to compare the outputs
(appendix A). This revealed the frequency of each department becoming the bottleneck (Figure
4.2). This led to the conclusion that each of the four departments is a potential constraint.
However, a clear constraint does not emerge. This travelling of bottlenecks creates a lot of
variation. To offset this variation, inventory is accumulated leading to longer lead times and
quality problems.
43
Figure 4.2 Shifting Bottlenecks
A 5-Why analysis of the most immediate problems faced in these departments pointed
towards to following aspects -
High Work in Process Inventory
Absence of a Material Release Mechanism
Focus on Improving Local Efficiencies
Quality and Productivity Treated as separate functions
A closer look at these processes through the lens of value5 reveals that these processes should
be carried out continuously. A value-adding ratio of these four processes was calculated to be
1.29% from a value stream map (appendix H). Such a low ratio can be directly attributed to the
5 “Value can only be defined by the ultimate customer. And it's only meaningful when expressed in terms of a specific product, which
meets the customer's needs at a specific price at a specific time." - Womack & Jones, Lean Thinking. For this case, value is considered as any
activity for which the customer is willing to pay for.
0123456789
Sewing Thread Cutting Finishing Packing
Bottleneck Frequency
44
long queue and wait times. This can be eliminated if these four processes were consolidated into
a single process.
These four departments were analyzed through another lens – That of V/A/T analysis.
Goldratt introduced the concepts of V, A & T Plants. He analyzed various manufacturing plants
and concluded that there are essentially 3 plant structures resembling the letters V, A and T.
These structures are created by analyzing divergence and convergence points of products &
processes.
The plant under consideration, MA’AM Arts was analyzed on these lines. The structure is
presented in Appendix B. The plant distributes is processes in the following way –
Cutting is carried out through contractors as already mentioned previously.
9 Sewing lines
Thread Cutting through two contractors with varying capacities as per the plant’s
requirements
2 floors for Finishing and Packing
Although the structure did not reveal a distinct shape, the plant exhibited much of the
characteristics of a T-Plant –
“T-plants are dominated by a major divergent assembly point at final assembly, where many
different end items are assembled from a relatively limited number of component parts, many of
which are common to numerous end items. In T-plants, the critical resource and product
45
interactions take place at final assembly, where the product structure expands to yield a large
variety of assembled products.” 6
4.2. Designing the System’s Constraint
The consolidation of these processes need not be physical. Physical consolidation of these
processes could have employed the principles of lean manufacturing. Although preferable under
stable conditions, physical consolidation was not practicable under the volatile conditions of the
plant under consideration. At this time, the following challenges lay ahead –
A constraint was required to design the Drum-Buffer-Rope application
The four travelling bottlenecks could not have been physically consolidated
A logical consolidation was however very easily possible. This consolidation is explained
later in the next section.
This logical consolidation provides a solution to both the challenges stated above. It
eliminates the problem of travelling constraints by creating truly parallel processes thus revealing
a clear T-Plant structure (Appendix D). Each of these branches creates a set of parallel
constraints. The throughput of these constraints determines the overall throughput of the plant.
Since these constraints set the pace of the plant, they become the drum in the Drum-Buffer-Rope
mechanism as explained in the next chapter.
Wherever the processes required by a garment are broken down and carried out by separate
departments, work-in-process increases and the problem of travelling bottleneck arises. This
arises from the notion of balancing capacities. Balancing capacities can never deliver output as
6 Umble & Umble, 1999
46
per plans due to two important factors – statistical fluctuations and dependent processes. Instead,
the flow of production must be balanced7. This balancing of flow is only possible when the
subsequent processes are not displaced too much from each other. Even if they are not put
physically together, their distance may be reduced on a scale of time. The constraint, in such
fragmented conditions need not be identified but rather designed. The design should arise from
the environmental limitations. This design can be developed by –
1. Measuring the distance between subsequent processes on a scale of time
2. Minimizing this distance to as low as practically possible
The constraint must be designed to be located at the system’s end. Eventually, the constraint
will move into the market. When that happens, demand will become the constraint and the closer
the previously designed constraint is placed to this demand i.e. the shipping schedule, the more
productive the system will become as this configuration would implicate a pull system by its
very nature thus reducing inventory and improving throughput.
4.3. Exploiting the System’s Constraint
Once the constraint has been designed, an exploitation strategy must be devised to extract the
highest throughput from it. In the following paragraphs, the exploitation strategy applied at
MA’AM Arts, Jaipur is described. This strategy is based on the following generic points –
1. Improve the throughput rate of the ultimate output of the consolidated processes.
2. The time between point of inspection and point of operation should be reduced to as
low as possible.
7 Refer the dice game as illustrated in the book “The Goal” by Eliyahu M. Goldratt.
47
3. Any unnecessary steps must be eliminated.
The first irritable observation was a separate thread cutting department. Operators in their
regular course of sewing have to cut thread after each operation. The operator should cut the
threads from the root themselves, thus eliminating the need for separate thread cutting at a later
stage. A time study was performed on a particular style where operators were instructed to cut
the thread themselves (Appendix E). This increased the work content of the garment by only
2.05 minutes, reducing the average hourly output in sewing from 41 to 39 but reducing the lead
time from sewing to finishing from 30 hours to just 10 hours. A cost analysis of thread cutting by
separate department versus thread cutting at source clearly shows that it is more profitable when
the threads are cut by the operators themselves (Appendix F).
Since thread cutting was included as a part of sewing operations, the remaining three distinct
processes of finishing and packing remained to be consolidated. This was achieved by linking a
sewing line with a finishing cell8. The finishing cell was expanded to include packing activities
such as tagging, folding, adding hangers and packing garments into polybags (Appendix I). This
link was logical rather than physical. The sewing line and finishing cell were on different floors.
An inventory of 1 hour’s work was fixed between them. This translated to the hourly output from
the sewing line being fed to the finishing & packing cell.
The finishing & packing cells were much more robust than the sewing lines. Manpower
could easily be added or removed from a cell to balance the flow of units. The only job of the
supervisor was to make sure that the finishing & packing cell was sufficiently manned to
complete one hour’s worth of output from the sewing lines every hour. The hourly target of the
8 Dewan & Sihmar (2010)
48
cell was to produce tagged and folded garments (or hanger, as the case may be) stored size-wise
on racks.
The ultimate output of the designed constraint was to produce packed goods. Garments are
packed in polybags as per customer specifications. It may be any one of the following
configurations.
Packing Polybag (Sizes) Carton (Colorways) Solid Assorted
Solid 1 2 Assorted 3 4
Table 4.2 Types of Packing
1. Solid-Solid – Each carton contains polybags in the same colorway with each polybag
containing a specified number of pieces of the same size.
2. Assorted-Solid – Each carton contains polybags in a specified ratio of colorways with
each polybag containing a specified number of pieces of the same size.
3. Solid-Assorted – Each carton contains polybags in the same colorway with each
polybag containing pieces in a specified size ratio.
4. Assorted-Assorted – Each carton contains polybags in a specified ratio of colorways
with each polybag containing pieces in a specified size ratio.
Thus, the aim of the constraint is to produce items in such a way that they can be packed at
the end of the day. The most common type of packing is type 3. This can be achieved if each line
is fed in batches containing all sizes in ratio. This batch size is subjective and would wary from
product to product. The following rule of thumb was applied to arrive at a batch size –
49
𝐵𝑎𝑡𝑐ℎ 𝑆𝑖𝑧𝑒 = 𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑒 𝑜𝑓 𝑆𝑖𝑧𝑒 𝑅𝑎𝑡𝑖𝑜 𝑐𝑙𝑜𝑠𝑒𝑠𝑡 𝑡𝑜 𝐸𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝐷𝑎𝑖𝑙𝑦 𝑂𝑢𝑡𝑝𝑢𝑡2
Thus, by the end of the day, all sizes would be available for packing in two cycles. An
illustration of this system in explained in greater detail in the table below. The robustness of the
finishing & packing cell was used to keep the bottleneck in the constraint within the sewing line.
This prevented any overproduction downstream of sewing. The timing of the workers in the
finishing and sewing cells was offset by an hour so that the day’s sewing output could be
finished and packed.
Avg. Hourly Output 50 Pieces Feed S M L Feed for Day 400 1 2 3
No. of Lots 2 x 200 A 50 100 50 Size Ratio S:M:L = 1:2:1 B 50 100 50
Time Sewing Finishing/Packing Polybag S M L S M L
09:30 - 10:30 50 - - - - 10:30 - 11:30 50 50 11:30 - 12:30 50 50 12:30 - 01:30 50 50 02:30 - 03:30 50 50 50 03:30 - 04:30 50 50 04:30 - 05:30 50 50 05:30 - 06:30 50 50
6:30 – 07:30 50 50
Table 4.3 – Illustration of production within the drum
A supervisor was made responsible for this entire consolidated constraint. It was his
responsibility to maintain a regular flow of goods through it. This system of working allowed
the constraint to work with lesser inventory and shorter lead times. Much of the queue and
waiting times were eliminated to result in a more robust overall system.
50
05. Drum-Buffer-Rope
51
Manufacturing is at the heart of our industrialized economies. Productivity, thus, is an
indispensible measure. It is the consequence of the production system – the mechanics that turn
the wheels of any manufacturer. Drum-Buffer-Rope is the motor which can drive this production
system and Buffer Management is the throttle to control this motor. How these two Theory of
Constraints logistical solutions are applicable to made-to-order apparel manufacturing is
described in this chapter.
5.1. The Drum
The drum is the constraint in a system. It sets the pace at which the entire system works. The
constraints have been described in the previous chapter. This chapter deals with how these
constraints can be used as drums to run the production system.
Each of the designed constraints is a drum. The system cannot produce any more than what
these drums can produce. Since the drums constitute the throughput of the system, they must
work as best as they can. How these drums were exploited for performance has already been
described in the previous chapter. The focus now is on a broader view of the system.
In a series of dependent processes, statistical fluctuations always occur. These fluctuations
cause variability. In order for the drums to operate continuously without ever being exhausted in
supply from upstream processes, they must be shunned from any variability. This protection is
provided by maintaining buffers before the drums. Traditionally, each process is protected by
maintaining buffers in front of them. However, in drum-buffer-rope, buffers are measured on a
52
scale of time instead of physical count. The entire time from material release to the start of
operation at the drum is considered as the buffer.9
5.2. The Buffer
Goldratt suggests that the time buffers must be established by applying a simple rule of
thumb, without getting into data collection and complex calculations.
𝑇𝑖𝑚𝑒 𝐵𝑢𝑓𝑓𝑒𝑟 = 𝐿𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 𝑓𝑟𝑜𝑚 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑟𝑒𝑙𝑒𝑎𝑠𝑒 𝑡𝑜 𝑑𝑟𝑢𝑚2
To arrive at this time buffer, the lead time from release of grey material to beginning of
sewing was required to be calculated. In general two kinds of processing is required by the grey
fabric – Printing and Dyeing. This time was calculated by tracking 9 running orders from grey
issue to dispatch. The tracking of these orders is presented in appendix G.1 to G.9. However, all
of these orders required dyed fabric. Orders requiring printed fabric were scheduled for sewing at
a time beyond the duration of this phase of the research. Thus, only historical lead times for
printing could be collected. The lead time from receipt of material to start of sewing was
determined from the 9 orders which were actually tracked. This time was added to the lead time
for printing to arrive at the time buffer for orders requiring printed fabric. The orders were
tracked by “Sheet Numbers” – the plant’s term for uniquely identifying each product.
The lead times and time buffers derived from them are described in Table 5.1 A and 5.1 B
below. These time buffers in front of the drum are called production buffers. Their purpose is to
protect the drum against variation in upstream processes. The production was tracked by
9 This concept has been explained by Schragenheim and Dettmer. See 21.A in the Review of Literature.
53
recording the daily output for each Sheet Number. Since sewing lines required up to six hours to
generate an output, the start of sewing is considered to be one day before the output is recorded.
Sheet No. Grey Issue Start
Receive Start
Receive End
Sewing Start Lead Time Lead Time
A B C D E F = C to E G = B to E
1664 A 22/2 8/3 18/3 17/3 10 24 1664 B 18/2 26/2 28/2 10/3 13 21 1664 C 18/2 26/2 28/2 15/3 18 26 1664 D 16/2 13/3 16/3 18/3 6 31 1664 E 10/2 20/2 22/3 7/3 16 26 1664 F 16/2 20/2 3/3 14/3 21 27 1660 A 20/3 22/3 22/3 5/4 15 17 1660 B 6/3 13/3 13/3 2/4 21 28 1660 C 10/3 27/3 27/3 6/4 11 28
Median Lead Time 15.5 ~ 15 26
Table 5.1 A - Lead time from Material Release to Sewing for Dyed Products
Sheet No. Grey Issue Start Receive Start Receive End Lead Time Lead Time
H I J K L = I to J M = Median of F + L
1545 A 21/1 14/2 3/3 25 40 1598 A 2/1 22/1 27/1 21 36 1598 B 26/12 17/1 17/1 23 38 1598 C 4/1 30/1 30/1 27 42 1598 D 6/1 19/1 23/1 14 29 1531 A 17/1 9/2 12/2 24 39 1531 B 23/1 3/2 6/2 12 27 1531 C 22/1 3/2 19/2 13 28
Median Lead Time 37
Table 5.1 B – Lead time from Material Release to Sewing for Printed Products
The production buffer was calculated by applying the rule of thumb to the above lead times.
The median lead times were considered for this purpose as they represent the most likely
54
situation. The buffers for dyed and printed products were calculated as 13 and 18.5 days
respectively. However, these times need not be strictly followed. If one strongly feels to increase
or decrease this time within reasonable limits, it should be done.
Since solid dyeing is outsourced to dyers within the city of the plant, 13 days seemed too
long. It was reduced to 10 days. Printing is carried out by suppliers in another district. Since
there is lower control over them, the buffer was increased from 18.5 to 20 days.
Thus, the production buffer size for dyed and printed products were determined to be
Product Type Production Buffer Size Dyed 10 Days
Printed 10 Days
Table 5.2 – Production Buffer Size
This production buffer protects the drum against variation in upstream processes. But another
kind of variation must also be considered, the variation within the drum itself. This variation is
protected by a shipping buffer, the time from the end of the drum to shipping. A similar process
to that followed for determining the production buffer can be used to calculate the shipping
buffer. In this case, the drum was at the end of the system. A one day shipping buffer should
have been sufficient but to add more safety, a two day shipping buffer was used. The drum and
buffers are shown in the figure below.
Dyed Printed Production Buffer Drum Shipping Buffer
Figure 5.1 – Drum and Buffer
55
5.3. The Rope
The output of the system is determined by the output of the constraint. Hence, releasing more
material than the constraint can use will only increase inventory without affecting the system.
The release of material should be choked. It must be linked to the schedule of the drum. The
figure below shows the effect of choking material release on due date performance.
Figure 5.2 - Real life example of the effect of choking the release on the due date performance Source: Goldratt, 2009
It clearly shows that choking material release by linking it to the drum schedule has
immediate positive impact on a plant’s due date performance.
56
5.4. Drum-Buffer-Rope Schedule
The above concepts were applied to execute three production orders comprising nine sheet
numbers. The plant approved the use of two sewing lines, thus two drums, to run these orders.
The details of these orders in presented in tables 5.3 A and 5.3 B below.
Style # Sheet # Description Quantity Size Ratio S M L XL
U-9881 1738 F Dyed 5 Tier Skirt 3200 800 1600 800 1738 G Dyed 5 Tier Skirt 3200 800 1600 800 1738 H Dyed 5 Tier Skirt 4800 1200 2400 1200
DM-10-32 1732 A M&M Printed 5 Tier Skirt 600 100 200 200 100 DM-10-41 1732 B M&M Printed 5 Tier Skirt 600 100 200 200 100 DM-10-31 1732 C M&M Printed 5 Tier Skirt 600 100 200 200 100 DM-10-37 1732 D M&M Printed 5 Tier Skirt 600 100 200 200 100
UU76771 1714 A Women’s Top /w Lace 504 84 168 168 84 1714 B Women’s Top /w Lace 432 72 144 144 72
Table 5.3 A – Details of orders executed on the Drum
Sheet # Due Date
1738 F 17 April, 2010 1738 G
1738 H 1732 A
22 April, 2010 1732 B 1732 C 1732 D 1714 A 25 April, 2010 1714 B
Table 5.3 B – Due dates of orders executed on the Drum
57
These due dates represent the shipping schedule. Subtracting the shipping buffer from this
shipping schedule would determine the end date of the order at the drum. To determine the start
date at the drum to create the drum schedule, the estimate of the lead time at the drum is
required. This may be achieved by in two ways –
1. Conducting time study to determine the work content of the garment
2. Using estimates provided by sewing & finishing line supervisors
Time estimate determined by time study was used for four sheets. For the remaining five
sheets, the estimates provided by the supervisors were used. An estimate of the learning curve
was also required. This learning curve was considered in the form of percentage of the estimated
hourly output as expected on a particular day from the start of production on a style. The hourly
output from sewing and learning curve estimates for each style is shown below. Each sewing line
consisted of 36 machines.
Sheet # SAM Learning Curve (%) Average Hourly Output I II III
U-9881 - 45% 80% 100% 48 DM-10-XX 32.5 45% 80% 100% 45 UU76771 - 45% 80% 100% 50
Table 5.4 – Estimating Work Content
Now, three essential data were available to create the schedule.
1. Shipping Schedule
2. Time Buffers
3. Work Content at Drum
58
With this information, the date of start at drum and material release can be determined. The
process is illustrated in the table below.
Ex-Factory Date A Date Shipping Buffer B Days Work Content at Drum C Days Start Date at Drum D Date Production Buffer E Days Material Release F Date
D = A – B – C and F = D – E For Example, if A = 17th April, B = 2 Days, C = 10 Days and D = 10 Days Thus,
D = 17th April – 12 Days = 3rd April and F = 3rd April – 10 Days = 22nd March
(While calculating, only working days are considered)
Figure 5.3 – Determining Drum Start and Material Release
The above stated method was used to determine the drum schedule of two drums. Estimates
of the work content were used to determine the due dates at the drum. For sake of control and
checking the validity of the drum, each was explicitly planned. One plan is shown in the table
below. Plans for each sheet are shown in appendices J.1 & J.2.
59
Average Hourly Output 44 Cumulative
Feed Batch Size 180 Day Output S M L XL S M L XL
1 280 60 120 70 30 60 120 70 30 2 350 55 86 136 73 115 206 206 103 3 350 48 120 120 60 163 326 326 163 4 350 43 86 86 43 206 412 412 206
Day Status at End of Day
Packed Ratio - 1:2:2:1
S M L XL S M L XL Total 1 60 120 70 30 30 60 60 30 180 2 85 146 146 73 73 146 146 73 438 3 60 120 120 60 60 120 120 60 360 4 43 86 86 43 43 86 86 43 258
Table 5.5 – Detail plan for Sheet No. 1732 A and 1732 B fed to Drum I consecutively
Such detailed planning at the drum allows for better estimates of the work duration at the
drum. Once these durations are calculated, the drum schedule must be prepared. The drum
schedules for both drums used for the application are given below. These drum schedules must
be strictly followed as any deviation in these drums directly impacts the system’s throughput.
The drum schedule is a simple list of work orders. The supervisor of a drum is made
responsible for making sure that each work order is started precisely as per the schedule. The
drum supervisor must ascertain the availability of cut parts, trims and accessories from upstream
processes. In case of any problem, the buffer manager is intimidated for resolution of the matter.
60
Sheet #
Date Drum I Drum II
27/3 1738 H N/A 28/3 Sunday 29/3 1738 H 1738 F 30/3 1738 H 1738 F 31/3 1738 H 1738 F 1/4 1738 H 1738 F 2/4 1738 H 1738 F 3/4 1738 H 1738 F 4/4 Sunday 5/4 1738 H 1738 F 6/4 1738 H 1738 F 7/4 1738 H 1738 F 8/4 1738 H 1738 F; 1738 G 9/4 1738 H 1738 G 10/4 1738 H 1738 G 11/4 Sunday 12/4 1738 H;1738 G 1738 G 13/4 1738 G 1738 G 14/4 1738 G; 1732 A 1738 G; 1732 C 15/4 1732 A 1732 C 16/4 1732 A; 1732 B 1732 C; 1732 D 17/4 1732 B 1732 D 18/4 Sunday 19/4 1732-B & 1714 A 1732 D 20/4 1714 A N/A 21/4 1714 A; 1714 B N/A 22/4 1714 B N/A
Table 5.6 – Drum Schedule
The material release schedule was created with respect to this drum schedule. This
synchronization between material release and the drum schedule is the most essential step of a
Theory of Constraints application. It subordinates all activities to the constraint. The material
release schedule is also called the gating schedule. It is shown in the table below.
61
Date Sheet # Upper Lining (Meters) (Meters)
16/3 1738 H 8100 3180 17/3 1738 F 5380 2150 22/3 1732 A 1125 22/3 1732 C 1125 24/3 1732 B 1125 24/3 1732 D 1125 27/3 1738 G 5380 2150 2/4 1732 A 400 2/4 1732 C 400 5/4 1732 B 400 5/4 1732 D 400 7/4 1714 A 490 125 8/4 1714 B 410 110
Table 5.7 – Material Release Schedule
5.5. Buffer Management
So far the concept of DBR has been discussed; however there is a second part of this act
which is equally important and imperative for successful implementation of DBR. This second
part is Buffer management; it is the control system that allows us to keep a running check on the
system’s effectiveness. The drum-buffer-rope model, once established, needs a monitoring
system to keep it in control which is achieved by buffer management. Buffer management
surfaces the important signals from the system warning us against the potential problems and
also acts as a litmus test to check whether too much and or too little protection is being given for
any order. Before understanding the role of buffer management, the role of buffers must me
clearly understood.
62
In a make-to-order environment, timeliness is of utmost importance. Buffers protect the
timeliness of the system by subordinating the raw material release and all other steps up to the
drum origin so that materials arrive in good time to be processed as planned and finished goods
can be shipped at the planned time. This is the role of buffers.
Buffer management begins by dividing the time buffers in to three equal/unequal zones.
Suppose the production buffer is of nine day; the first zone (green zone) would span for the first
three days, the second zone (yellow zone) would span the next three day and the third buffer (red
zone) would span the last three days. We expect most work to be completed in the first two
thirds and be waiting in front of the constraint for the last third of the buffer time. Thus in the
above mentioned example, one expects the work to take about 6 days of processing and waiting-
in-process, and then sitting in front of the drum for 3 days. If the materials are not ready for the
drum by the start of the third zone, the work order must be expedited to make sure that drum
schedule is not disturbed. The figure shown below illustrates zoning of the production buffer.
9 Day Production Buffer I II III
1 2 3 4 5 6 7 8 9 Green Zone Yellow Zone Red Zone
Figure 5.4 – Zoning of Buffers
In the case of implementation, the following zones were used
1. Production Buffer for Printed – 20 Days
a. Zone I - Day 1 to Day 8 - 8
b. Zone II - Day 9 to Day 14 - 6
c. Zone III - Day 15 to Day 20 - 6
63
2. Production Buffer for Dyed – 10 Days
a. Zone I - Day 1 to Day 4 - 4
b. Zone II - Day 5 to Day 7 - 3
c. Zone III - Day 8 to Day 10 - 3
Buffer management can be used for local control in order to avoid deviation from the drum
schedule or global feedbacks to address any buffer related issues for effective implementation of
drum-buffer-rope.
5.5.1 Local Control – Buffer status
Buffer status tells the status of an order that has already been released into the system.
Schragenheim defines buffer status as
𝐵𝑢𝑓𝑓𝑒𝑟 𝑆𝑡𝑎𝑡𝑢𝑠 (%) = 𝐵𝑢𝑓𝑓𝑒𝑟 𝐷𝑢𝑟𝑎𝑡𝑖𝑜𝑛 − 𝑅𝑒𝑚𝑎𝑖𝑛𝑖𝑛𝑔 𝐷𝑢𝑟𝑎𝑡𝑖𝑜𝑛𝐵𝑢𝑓𝑓𝑒𝑟 𝐷𝑢𝑟𝑎𝑡𝑖𝑜𝑛 𝑥 100
In other words buffer status indicates how much part of the total buffer has been exhausted.
For example, the production buffer for printed products was taken as 20 days. On the 7th day the
buffer status would be or 35%. A buffer status chart which has all the orders released into
the system helps to know the orders which might deviate from the planned schedule. If the buffer
status of any order is above 70% it indicates that the order has entered the red zone of the buffer
and needs to be expedited in order to prevent due date violation. Thus a daily buffer status chart
for all the released orders would indicate which orders require management attention to avoid
any divergence from the schedule.
64
A similar chart was maintained for all the released orders. In certain cases, it helped in
insinuating the necessary actions to avoid deviation from schedule. The buffer status report is
presented in Appendix K.
5.5.2. Global Feedback - Buffer Hole
A buffer hole is the depth or the duration by which the red zone has been penetrated. It is a
measure of the system’s stability and suggests whether the current buffer duration is apt or not. If
most of the orders lie in the green zone it implies that the buffer is more and unnecessary excess
inventory is being put into the system. Similarly if most of the orders are in the red zone it
implies that the buffer is small and should be increased to avoid any deviation from the schedule.
Buffer holes for the orders run using the drum-buffer-rope model are shown in the figures
below.
Figure 5.5A – Buffer holes in production buffer for dyed products
0
0.5
1
1.5
2
2.5
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10
65
Figure 5.5B Buffer holes in production buffer for printed products
In case of dyed products the incidences of buffer holes were less. However, in case of printed
products, the incidences of buffer holes were very high and thus called for improvements.
5.5.3. Global Feedback –Reason code analysis
The data obtained from buffer management can be used to direct improvements. An analysis
of all the orders gives a trend of receiving various orders in various buffer zones. The cause for
occurrence of red zone and frequency for each cause can be recorded. Necessary actions can then
be taken so that these causes are not repeated in the future or at least their frequency is reduced.
The following figure shows the different zones in which the production buffers for the work
orders were exhausted. It is followed by a table listing the causes for penetration of the red zone
with their frequency.
0
0.5
1
1.5
2
2.5
Day
1
Day
2
Day
3
Day
4
Day
5
Day
6
Day
7
Day
8
Day
9
Day
10
Day
11
Day
12
Day
13
Day
14
Day
15
Day
16
Day
17
Day
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20
66
Figure 5.6 – Buffer Exhaustion
Reason Code Analysis (Red Zone ) Reason Frequency
Late arrival of Print/Dye fabric 6 Cutting 1 Total 7 Recommended Action Increase the buffer duration for printed materials.
Table 5.8 – Reason Code Analysis
5.5.4 Local Measurements
Apart from local controls and global feedbacks, buffer management is also helpful in
measuring two important aspects of a system - Throughput & Inventory. Whenever an order is
late and needs to be measured there is always confusion whether it should be measured in terms
of late days or sales value. Measuring in terms of just one criterion might result in under
estimation of the magnitude of a large order late by just 1 day or a small order late by several
Green Yellow Red0
1
2
3
4
5
6
7
8
67
days but of a low sales value. Buffer management addresses this old problem by taking a product
of the two factors. It is called throughput dollar days.
Goldratt suggests that in order to avoid late deliveries, the lateness should be tied to buffer
holes. Whenever a task does not arrive at its buffer-origin even though enough time has elapsed
since its release, it is likely to cause due date variation. Thus, we might start to count the days
from the point in time when the task penetrated into the red zone, rather than from the order
due-date. This delay is called Lateness.
𝐿𝑎𝑡𝑒𝑛𝑒𝑠𝑠 = 𝐴𝑐𝑡𝑢𝑎𝑙 𝐷𝑢𝑟𝑎𝑡𝑖𝑜𝑛 − 𝐵𝑢𝑓𝑓𝑒𝑟 𝐿𝑒𝑛𝑔𝑡ℎ − 𝐿𝑎𝑠𝑡 𝑍𝑜𝑛𝑒 𝐿𝑒𝑛𝑔𝑡ℎ
Using buffer management this way provides the probable location of the problem and its
frequency;; however from the system’s point of view it is more plausible to have some measure
of severity. More the throughput is at stake, and more the days are late; more severe is the
problem. Stein advocates that using this measure of severity in buffer hole Pareto analysis gives
a more clear and reliable picture of the system.
𝑆𝑒𝑣𝑒𝑟𝑖𝑡𝑦 = 𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑥 𝐿𝑎𝑡𝑒𝑛𝑒𝑠𝑠
Sheet No. Throughput Lateness Severity 1732 A 88800 3 266400
1732 B 88800 4 355200 1738 C 88800 2 177600 1738 D 88800 2 177600 1738 F 280160 2 560320 1738 H 420240 3 1260720 1738 B 34344 1 34344
Table 5.9 – Severity
68
A daily location wise severity chart assigns the resulting measure to the unit where the
process is stuck and might cause a due date variation. Sometimes it might give a false picture as
that department might not be responsible for the lateness - but the result to the system is the
ultimate goal. The centre that inherits the problem will, in effect, expedite the resource with a
severity tied to it and try to move it out of the department as soon as possible. The quality control
department however should make it sure that the work done is not sloppy in this case.
Such daily location wise measure of severity was done for the implemented orders to make
sure that an order with severity tied to it has a higher priority at the non-constraint resources. The
table below gives the magnitude of severity on a particular day and the department to which it
belongs.
Department 24-Mar 25-Mar 07-Apr 08-Apr 09-Apr 10-Apr 12-Apr
Printing/Dying Receive 420240 88800 177600 88800
Print Checking 177600 266400
Cutting 1120640 88800 88800
Smoking
Table 5.10 – Daily Severity Chart
69
06. Results
70
6.1. Planned v/s Actual
The planned orders were fed into the system and the actual performance was measured to
gauge the effectiveness of scheduling. When the orders were planned daily estimates of the
drum’s output, total number of pieces packed, status at the end of day and number of unpacked
pieces were estimated. These factors were then compared with actual data collected from the
implementation. One such comparison is shown in the table below.
Date 15/4 Status at Drum Output S M L XL Total
Sewing Expected 60 120 70 30 280 Actual 60 120 80 30 290
Available for Pack at End of Day Expected 60 120 70 30 280 Actual 60 120 80 30 290
Packing Expected 30 60 60 30 180 Actual 30 60 60 30 180
Un-Packed (Waiting for Size Ratio) Expected 30 60 10 0 100 Actual 30 60 20 0 110
Table 6.1 – Planned v/s Actual at Drum 1 on 15th April
In most cases, the actual output did not exactly match the planned output but most of them
were completed in the planned drum duration. The daily packed output as planned and as it
occurred in reality were compared for both the drums. It revealed that although there were
deviations within an order’s schedule, it largely evened out to be completed on time. It shows
that keeping the bottleneck in the drum within sewing allows greater control and better accuracy
of planning.
71
DRUM 1 Date Sheet No. Planned Actual Cumulative
Planned Actual Deviation 27/3 1738 H 40 0 40 0 100.0 29/3 1738 H 360 400 400 400 0.0 30/3 1738 H 400 400 800 800 0.0 31/3 1738 H 400 360 1200 1160 3.3 01/4 1738 H 400 360 1600 1520 5.0 02/4 1738 H 320 280 1920 1800 6.3 03/4 1738 H 320 400 2240 2200 1.8 05/4 1738 H 360 400 2600 2600 0.0 06/4 1738 H 400 400 3000 3000 0.0 07/4 1738 H 400 400 3400 3400 0.0 08/4 1738 H 400 400 3800 3800 0.0 09/4 1738 H 400 400 4200 4200 0.0 10/4 1738 H 400 400 4600 4600 0.0 12/4 1738 H; 1738 G 400 400 5000 5000 0.0 13/4 1738 G 400 400 5400 5400 0.0 14/4 1738 G; 1732 A 520 520 5920 5920 0.0 15/4 1732 A 180 180 6100 6100 0.0 16/4 1732 A; 1732 B 438 438 6538 6538 0.0 17/4 1732 B 360 360 6898 6898 0.0 19/4 1732 B; 1714 A 258 258 7156 7156 0.0 20/4 1714 A 180 0 7336 7156 2.5 21/4 1714 A 342 120 7678 7276 5.2 22/4 1714 A; 1714 B 444 330 8122 7606 6.4 23/4 1714 B 0 516 8122 8122 0.0
Table 6.2 – Planned vs Actual comparison for packed output at Drum 1
72
DRUM 2 Date Sheet No. Planned Actual Cumulative
Planned Actual Deviation 29/3 1738 F 40 0 40 0 100.0 30/3 1738 F 360 400 400 400 0.0 31/3 1738 F 400 400 800 800 0.0 01/4 1738 F 400 400 1200 1200 0.0 02/4 1738 F 400 360 1600 1560 2.5 03/4 1738 F 320 440 1920 2000 4.2 05/4 1738 F 320 400 2240 2400 7.1 06/4 1738 F 360 400 2600 2800 7.7 07/4 1738 F 400 400 3000 3200 6.7 08/4 1738 F; 1738 G 400 400 3400 3600 5.9 09/4 1738 G 400 400 3800 4000 5.3 10/4 1738 G 400 400 4200 4400 4.8 12/4 1738 G 400 400 4600 4800 4.3 13/4 1738 G 400 560 5000 5360 7.2 14/4 1738 G; 1732 C 520 160 5520 5520 0.0 15/4 1732 C 180 360 5700 5880 3.2 16/4 1732 C; 1732 D 438 438 6138 6318 2.9 17/4 1732 D 360 438 6498 6756 4.0 19/4 1732 D 258 0 6756 6756 0.0
Table 6.3 – Planned vs Actual comparison for packed output at Drum 2
6.2. The Drum-Buffer-Rope Schedule
The orders which were run on the developed scheduling model were tracked to record their
performance against the planning. Their progress is presented in a calendar form below. The
chart shows the progress of each sheet number through the various processes along which it was
routed.
73
Date March, 2010 April, 2010
16 17 18 19 20 22 23 24 25 26 27 29 30 31 01 02 03 05 06 07 08 09 10 12 13 14 15 16 17 19 20 21 22 23 24 25
1738 F
1738 G
1738 H
1732 A
1732 B
1732 C
1732 D
1714 A
1714 B
Table 6.4 – Progress of Order scheduled by Drum-Buffer-Rope (Sundays are excluded)
74
6.3. New v/s Old
The orders executed using the drum-buffer-rope model is compared to orders that were run as
the on the plant’s conventional method. The comparison is shown in the table below.
Sheet No. Printed/Dyed Qty. Due date Actual
date Due date variation
On Time In Full
Lead time - Grey issue to Sewing
Start Conventional Planning
1664 A Dyed 3904 17/3 24/3 8 No 24 1664 B Dyed 3680 17/3 24/3 8 No 20 1664 C Dyed 4144 17/3 24/3 8 No 26 1664 D Dyed 3456 17/3 24/3 8 No 30 1664 E Dyed 4144 17/3 24/3 8 No 26 1664 F Dyed 3680 17/3 24/3 8 No 27 1660 A Dyed 1200 27/3 12/3 17 No 17 1660 B Dyed 1150 27/3 12/3 17 No 28 1660 C Dyed 1150 27/3 12/3 17 No 28
Drum-Buffer-Rope 1732 A Printed 600 22/4 22/4 0 Yes 20 1732 B Printed 600 22/4 22/4 0 Yes 20 1732 C Printed 600 22/4 22/4 0 Yes 20 1732 D Printed 600 22/4 22/4 0 Yes 20 1738 F Dyed 3200 17/4 17/4 0 Yes 10 1738 G Dyed 300 17/4 17/4 0 Yes 10 1738 H Dyed 4800 17/4 17/4 0 Yes 10 1714 A Dyed 504 25/4 25/4 0 Yes 10 1714 B Dyed 432 25/4 25/4 0 Yes 10
Table 6.5 – Performance Comparison
75
07. Limitations and Scope of Further Study
76
In this paper, the applicability of Theory of Constraints Drum-Buffer-Rope as a planning and
controlling system was illustrated. Although the concepts are generic in nature, their application
will be different in different environments. The case of implementation presented herein is only
one instance of this application. The implications however, can be generalized. Reducing
inventory will always lead to shortened lead times. Drum-Buffer-Rope provides a mechanism to
measure inventory on a scale of time and keep it to as low as the plant can afford it. In a make-
to-order environment, buffers protect the crucial timeliness of the system. It is evident from
results of the application; accurate due date performance is possible with shorter lead times and
less inventory.
7.1. Limitations
The major limitation is that the model developed herein cannot be, in fact, should not be
replicated in a different environment. Each environment must be analyzed to identify its
constraint and the drum-buffer-rope model should be applied accordingly. This case however
presents a case which is common to most made-to-order apparel manufacturing environments i.e.
the T plant structure where a host of products are made in different assembly lines. Any such
environment may apply the model described in this paper if its constraint lies in sewing.
Another limitation is that the instance of outsourced processes after sewing was not
considered. It was omitted as at the time of conduction the research since testing a model that
included outsourced processes such as garment wash or tie & dye was not possible due to the
limitations of the plant.
77
7.2. Scope for Further Study
The limitations described above present an opportunity for further research. The drum-
buffer-rope model can be designed to include those instances which require any extra processing
other than sewing, finishing and packing. In such a case, the continuity between sewing and
finishing would be broken and a different buffer management strategy would be required.
Theory of Constraints provides the power of focus. This enables improvement efforts to be
directed on those areas which would impact the bottom line most. By itself, theory of constraints
is a very high performing system. However, it can pull in elements of Lean, Six Sigma, and SPC
etc. in a highly focused and leveraged manner to improve itself. These improvement
philosophies should be applied to the constraint to increase its throughput thus impacting the
entire system.
A process of ongoing improvement based on theory of constraints might eventually lead to
the constraint shifting into the market. In such a case, market demand will determine the
system’s throughput. When this happens, an active internal bottleneck might not exist. Then, an
even simpler application known as Simplified Drum-Buffer-Rope can be applied.
Simplified Drum-Buffer-Rope is based on the same concepts as traditional Drum-Buffer-
Rope and is certainly in harmony with Theory of Constraints and the Five Focusing Steps. What
distinguishes it from traditional Drum-Buffer-Rope is its assumption of market demand as the
major system constraint, even when an internal capacity constraint temporarily emerges.10
10 Eli Schragenheim and H. William Dettmer
78
In mature apparel manufacturing environments, where stability has been achieved and the
system’s throughput is not dominated by an internal constraint, the Simplified Drum-Buffer-
Rope application can be implemented, thus simplifying the plant’s operating model.
79
08. Conclusion
80
The Theory of Constraints was developed in a made-to-order environment. There are several
formal Theory of Constraints applications where the detailed body of knowledge is rock-solid
and have been applied to hundreds or even thousands of different companies. The production
solution, which includes the planning and control technique known as Drum-Buffer-Rope can be
applied to any manufacturing business to generate the same outcomes. Hence, the production
solution is called an application.
This leads to the question that why has the theory of constraints not found popular
application in the apparel manufacturing industry. It may be argued that there is not much to gain
from it, but such an argument would be grossly inappropriate. As has been illustrated in this
paper, a very simple model applied in an unstable environment of high-mix/low-volume made-
to-order apparel manufacturing at an SME in Jaipur led to high due-date performance with
shortened lead times and reduced inventories. It was done without complex calculations or large
data collection efforts. This shows that drum-buffer-rope is a simple yet extremely powerful tool
to drive apparel manufacturers towards greater profits. Decreased lead times can provide
competitive edge to a company, and assuming there is no constraint in market demand, this could
lead to increased sales. The following co-relations also become true when lead times and
inventories are reduced –
Cost of inventory which includes costs like warehousing, handling, expedition and
working capital cost goes down.
Cost due to sales loss goes down.
Extra capacities are released, which reduces un-necessary cost of capital investment.
Ongoing improvement projects to improve bottlenecks increase throughput.
81
The apparel industry must eliminate its myopic view of focusing on local improvements.
Lean and Six Sigma are powerful tools but they must be applied keeping the impact on the
global system in mind. As has been implied in the paper, the first necessary condition for a
sustainable lean implementation is stability. This is exactly what Drum-Buffer-Rope provides. It
provides a schedule that works i.e. it remains valid and keeps the plant pumping out the right
products on time to meet delivery schedules despite inaccurate data, absenteeism, machine
breakdown, unreliable vendors, unexpected repair and rework etc.
The greatest advantage Theory of Constraints provides is the power or leverage. By focusing
on the constraint, the bottom line of the company can be directly affected. No other system, be it
Lean/JIT, Six Sigma or TQM acknowledges the existence of constraints. But that is never true.
Every system must have a constraint since if no constraints existed, the throughput of the system
would be infinite.
This simple acknowledgement of the existence of constraints has huge implications. It
challenges the very essence of the process of decision making my management. Traditional
management’s decisions are based on the older cost accounting model which apportions all costs
to products. Here lies a fundamental problem which is addressed comprehensively by the
financial application of Theory of Constraints known as Throughput Accounting. This basis of
cost allocation always prompts for actions which increase local efficiency. But once the
existence of constraints is acknowledges, the notion of local efficiency loses relevance. Theory
of Constraints prompts focus on global optima instead of local optimum. It has been applied to
hundreds of companies and documented evidence exist which showcase dramatic improvements.
82
Every system, however complex it might seem, is based on inherent simplicity. The more
complex a system is, the more it can gain by applying Theory of Constraints. Thus, apparel
manufacturers especially SMEs have much to gain from this body of knowledge.
8.1. Recommendations
Any company looking to implement the methods described in this paper must follow the
following steps.
1. Map the processes of the company.
Every plant is different. Hence, no two implementations will be the same. Thus,
all the processes from material release to the point of shipment must be mapped.
This will illustrate the inter-dependence between the various processes to reveal
the supply chain within the plan.
2. Identify the constraint
Since Drum-Buffer-Rope scheduling is designed on the constraint, the constraint
must first be identified. If the plant employs MRP/ERP systems, this can easily be
determined comparing the documented capacities of each process. However, since
most apparel SMEs do not employ such systems, they can simply identify the
constraint by an intuitive analysis of either of the three methods listed below –
- Finding the process where waiting time/inventory is highest
- The process which cause maximum disruption to downstream
processes
- Collect data on outputs of each process for a considerable period (a
month or above) to find the process with minimum productivity
83
3. Exploit the constraint
Since the constraint determines the throughput of the system, it must be exploited
to always be productive – doing what is supposed to be done. Each plant will have
a different exploitation strategy based on its operating environment. The best way
to exploit the constraint is to write a schedule for the constraint and make sure
that it is followed.
4. Subordinate everything to the constraint
This is done in order to protect the drum schedule from any variability. The drum-
buffer-rope model executes this subordination step by linking the material release
to the drum schedule. For applying the model, the production buffers must be
established and buffer management employed as has been described in chapter 5.
5. Elevate the constraint
Elevating the constraint is specific to each system. It should only be undertaken
once the constraint has been subjected to exploitation and subordination phases.
Lean/JIT, Six Sigma and TQM may be applied for elevation. Since now their
application is properly focused, their benefits would greatly impact the bottom line.
84
09. Bibliography
85
- Books -
Ford, 1922 Ford, Henry & Crowther, Samuel “Today and Tomorrow” Doubleday, Page & Co. (1926)
Ohno, 1988 Ohno, T. “Toyota Production System: Beyond Large-Scale Production.”
Productivity Press (1988)
Mabin & Balderstone, 2000
Goldratt, 1990
Johnson & Kaplan (1987)
Cox & Spencer,
1998
Umble & Srikanth, 1995
Senge, 1990
Mabin J. Victoria & Steven J. Balderstone “The world of the theory of constraints: a review of the international literature” CRC Press (2000)
Goldratt, E. M. “The haystack syndrome: sifting information out of the data ocean.” North River Press (1990)
Johnson, H. T., and Kaplan, R. S. “Relevance lost: the rise and fall of management accounting.” Harvard Business School Press (1987)
Cox, J. F. and Spencer, M. S. “The Constraints Management Handbook.” St. Lucie Press (1998)
Umble, M. and Srikanth, M. L. “Synchronous manufacturing: principles for world-class excellence” Spectrum Publishing (1995)
Senge, P. M. “The fifth discipline: the art & practice of the learning organization.” Random House (1990)
Goldratt, E.M,
1990
Goldratt & Cox, 1986
Goldratt,
1997
Stein, 1996
Schragenheim & Dettmer, 2000
Goldratt, E. M. “What is this thing called Theory of Constraints and how should it be implemented?” North River Press (1990)
Goldratt, E. M. and Cox, J. “The Goal – A Process of Ongoing Improvement” North River Press (1986)
Goldratt, E. M. “Critical chain.” The North River Press (1997)
Stein, R. E. “Re-engineering the manufacturing system: applying the theory of constraints (TOC).” Marcel Dekker (1996)
Schragenheim, E. and Dettmer, H. W. “Manufacturing at warp speed: optimizing supply chain financial performance.” The St. Lucie Press (2000)
86
- Articles -
Goldratt, 2009 Goldratt, E. M. “Standing on the Shoulders of Giants: Production Concepts versus Production Applications.” Gest. Prod. Vol. 16, No. 3 (2009)
Lee, Hwang,
Wang & Lee (2009)
Wheatley & Kellner-
Rogers, 1999
Scheinkopf, 1999
Umble & Umble, 1999
- Online Sources -
Woeppel, 2000
Youngman, 2005
Lee, J.H., Hwang, Y.J., Wang, M & Li, R.K. “Why Is High Due-Date Performance So Difficult to Achieve?—An Experimental Study” Production and Inventory Management Journal Vol. 45, No. 1 (2009)
s Wheatley, M. J. and Kellner-Rogers, M. “What Do We Measure and Why? Questions About The Uses of Measurement.” Journal for Strategic Performance Measurement (1999)
Scheinkopf, L. “Thinking for a change: putting the TOC thinking processes to use.” St Lucie Press/APICS series on constraint management (1999)
Umble, M. Michael and Umble, Elisabeth J. “Drum-Buffer-Rope for Lower Inventory” Industrial Management September (1999)
Woeppel, M. “Introduction to Drum-Buffer-Rope” http://www.pinnacle-strategies.com (2000)
Youngman, K.J. “A Guide to Implementing the Theory of Constraints (TOC)” http://www.dbrmfg.co.nz (2005)
87
Appendices
vi
Appendix A
vii
Appendix B
viii
Appendix C.1
ix
Appendix C.2
x
Appendix C.3
xi
Appendix C.4
xii
Appendix D
xiii
Appendix E
xiv
Appendix F
xv
Appendix G.1
xvi
Appendix G.2
xvii
Appendix G.3
xviii
Appendix G.4
xix
Appendix G.5
xx
Appendix G.6
xxi
Appendix G.7
xxii
Appendix G.8
xxiii
Appendix G.9
xxiv
Appendix H
xxv
Appendix I
xxvi
Appendix J.1
xxvii
Appendix J.2
xxviii
Appendix K
xxix
Annexures
xxx
Annexure 1
Training Needs identified for Managers and Supervisors my Method Apparel Consultancy in the NCR region depicting dismal realities.
Appendix A
SewingThead
CuttingFinishing Packing Sewing
Thead Cutting
Finishing Packing
8/3 3902 5412 5501 3810 - - - -9/3 3187 5903 5016 4565 - - - -
10/3 2379 4433 4165 3380 3156 5249 4894 3918 Sewing11/3 4335 3249 1440 1260 3300 4528 3540 3068 Packing12/3 6788 3682 3304 1300 4500 3788 2970 1980 Packing13/3 7937 4364 3418 2506 6353 3765 2721 1689 Packing15/3 4664 3887 3218 2000 6463 3978 3313 1935 Packing16/3 3795 4147 6057 4910 5465 4133 4231 3139 Packing17/3 3809 2839 5023 1407 4089 3625 4766 2772 Packing18/3 4552 3445 6454 8552 4052 3477 5845 4956 Thread Cutting19/3 5748 5949 4388 4574 4703 4078 5288 4844 Thread Cutting20/3 7269 4635 5207 1610 5856 4676 5350 4912 Thread Cutting22/3 5063 3680 4456 8533 6027 4755 4684 4906 Finishing23/3 5967 3480 5072 8884 6100 3932 4912 6342 Thread Cutting24/3 3371 4661 1810 1740 4801 3940 3779 6386 Finishing25/3 5934 4142 5322 3940 5091 4094 4068 4855 Finishing26/3 4309 2452 6309 3790 4538 3752 4480 3157 Packing27/3 4139 3750 2777 2810 4794 3448 4803 3513 Thread Cutting29/3 3732 3521 3055 5672 4060 3241 4047 4091 Thread Cutting30/3 3445 2111 3261 1260 3772 3127 3031 3247 Finishing31/3 4410 3379 5376 2403 3863 3004 3897 3112 Thread Cutting1/4 2221 3292 4666 1800 3359 2927 4434 1821 Packing2/4 2763 3156 4897 8580 3131 3276 4980 4261 Sewing3/4 6102 3410 1512 1460 3695 3286 3692 3947 Thread Cutting5/4 2859 3918 3671 6506 3908 3495 3360 5515 Finishing6/4 2019 4806 4790 2210 3660 4045 3324 3392 Finishing7/4 3577 4376 3270 8290 2818 4367 3910 5669 Sewing
DateOutput of Process 3 Day Moving Average
Bottleneck
0123456789
Sewing Thread Cutting Finishing Packing
Bottleneck Frequency
vi
Appendix B
Fabric for Body - - - - - Logical FlowRaw Material (Grey Fabric)
Cutting
Sewing
Thread Cutting
Finishing
Packing
Plant Structure - MA'AM Arts, Jaipur
Solid Dye
Print X
Print Y
_____ Physical Flow
1 Single Print
V/A/T AnalysisThe above structure illustrates the flow of products and processes. In this case, the plant has the characteristics of a T-Plant but the T structure is not clearly visible.
2
3
Mix & Match Prints
Solid Dye
Product Types
Operation Fabric for Lining
vii
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xi
Product Types V/A/T Analysis
1 Single Print The above structure illustrates the proposed logical flow of products and processes. Thread cutting as a separate process has been eliminated and a clear T structure is revealed.
2 Mix & Match Prints
3 Solid Dye
Operation Fabric for Lining - -
Solid Dye
Proposed Logical Plant Structure
Raw Material (Grey Fabric)
Fabric for Body Constraint Operation
Sewing
Print Y
Print X
Cutting
Drum 1 Drum 2 Drum 3
Packing
Finishing
Appendix D
xii
Appendix E
SMV
Attaching 9 panels of 8 th Tier 154.64 139.43 135.55 138.65 142.44 141.11 139.44 19.52 158.96 4.31Attaching 5 panels of 7 th Tier 84.01 77.41 71.81 81.51 75.17 78.07 76.79 10.75 87.54 3.53Attaching 3 panels of 6 th Tier 48.70 46.75 51.51 38.25 45.29 46.93 45.75 6.40 52.15 3.45Attaching 3 panels of 5 th Tier 51.03 38.91 47.94 54.58 47.45 47.45 47.27 6.62 53.89 2.85Attaching 2 panels of 4 th Tier 31.76 26.89 32.62 28.44 29.81 28.64 29.28 4.10 33.38 1.62Attaching 2 panels of 3 rd Tier 34.28 39.90 24.14 30.55 31.88 28.53 31.00 4.34 35.34 1.06Attaching 2 panels of 2 nd Tier 26.43 22.68 25.97 23.59 25.27 24.87 24.48 3.43 27.90 1.47Attaching 2 panels of 1 st Tier 21.43 20.48 18.96 19.29 19.55 19.52 19.56 2.74 22.30 0.87Gathering of 8 th Tier 137.32 118.04 121.18 148.53 128.89 129.14 129.15 18.08 147.24 9.92Gathering of 7 th Tier 69.19 59.18 71.38 57.43 66.77 78.52 66.66 9.33 75.99 6.79Gathering of 6 th Tier 73.42 80.68 71.78 46.68 70.20 77.52 69.37 9.71 79.08 5.66Gathering of 5 th Tier 53.43 47.29 46.68 50.69 50.62 50.84 49.23 6.89 56.12 2.69Gathering of 4 th Tier 51.68 50.05 51.36 41.10 48.05 50.86 48.28 6.76 55.04 3.37Gathering of 3 rd Tier 32.91 27.58 32.32 33.59 30.31 32.32 31.23 4.37 35.60 2.69Attachment of 8 th and 7 th Tier 426.88 382.67 370.27 389.27 374.46 377.68 378.87 53.04 431.91 5.03Attachment of 7 th and 6 th Tier 270.36 239.04 230.84 248.75 249.02 233.15 240.16 33.62 273.78 3.42Attachment of 6 th and 5 th Tier 278.92 223.58 212.54 353.35 249.56 216.52 251.11 35.16 286.26 7.35Attachment of 1 st and 2 nd Tier 77.05 69.68 69.35 67.10 67.59 68.01 68.35 9.57 77.91 0.86Attachment of 3 rd and 4 th Tier 97.66 106.24 86.20 85.48 85.67 86.26 89.97 12.60 102.57 4.90Attachment of 2 nd and 3 rd Tier 97.87 80.34 105.21 80.34 86.71 81.89 86.90 12.17 99.06 1.20Attachment of 2 nd and 3 rd Tier 166.13 176.23 160.48 131.62 151.56 120.85 148.15 20.74 168.89 2.75Lining attach 40.03 34.69 61.36 24.91 40.73 27.81 37.90 5.31 43.20 3.18Turn and top stitch of lining 103.92 83.95 93.69 101.29 99.36 105.30 96.72 13.54 110.26 6.34Lining attached to body 77.57 91.02 63.03 61.35 76.89 64.67 71.39 9.99 81.39 3.82Kaccha stitch at sides of waistband 23.10 22.64 16.07 23.60 21.69 22.92 21.38 2.99 24.38 1.27Close belt 55.78 57.66 44.62 53.12 53.83 50.70 51.99 7.28 59.26 3.48Attach belt to waist and hanger loop 93.77 98.41 87.93 78.00 86.36 76.52 85.44 11.96 97.41 3.64Close elastic band 8.71 7.96 8.25 7.98 8.18 7.47 7.97 1.12 9.08 0.37Attach elastic to the body 262.52 263.52 216.17 211.14 230.28 266.16 237.45 33.24 270.70 8.18Top secure stitch on elastic 48.34 41.07 52.62 42.13 42.41 39.49 43.54 6.10 49.64 1.30Label attach ( 2 labels at waist) 60.19 64.08 55.38 48.31 57.02 60.58 57.07 7.99 65.06 4.87Washcare label attach 37.68 39.37 31.55 33.39 36.03 38.29 35.73 5.00 40.73 3.05Bottom hem of lining 99.16 118.55 62.07 78.35 87.86 120.95 93.56 13.10 106.65 7.49
SAM 53.26 55.31 2.05
V
Allowance
@ 14%SMV
Increase in
Time
Readings (Thread Cut by Operators)Operation Avg. of 3 Readings x
Allowance @ 14%I II III IV
xiii
Appendix F
60 * 36 60 * 36
53.26 55.31
Thread ThreadCutting Cutting
800 40041 39
No. Rate (Rs.) Cost/Hour No. Rate (Rs.) Cost/Hour36 160 720.00 36 160 720.004 105 52.50 4 105 52.501 250 31.25 1 250 31.25
1/3 650 27.08 1/3 650 27.081 175 21.88 1 175 21.88
1/3 650 27.08 1/3 650 27.081/3 175 7.29 1/3 175 7.291/3 175 7.29
2 105 26.25
920.62 887.08
Net Profit (Throughput - Operating Expense)
102646 123832
Eliminating the Thread Cutting department by incorporating thread cutting at source by operators is compared to having a separate thread cutting department. They are compared on Lead Time and Costs based on Activity Based Costing and Throughput Accounting for a hypothetical order.
Throughput (Sales-Variable Costs) 199000.00 200000
300000 300000
Total Operating Expense 96354.50 76167.78
Days required 5.55 4.46
Operating Expense/Day 17364.99 17096.65
Net Profit 102646 123832
Hours to make 1000 Units
Comparing Lead Time based on Little's Law
Activity Based Costing
Cost Comparison Based on Throughput Accounting44.39 35.64
Floor Clerk
Thread Cutting Clerk
Thread Cutting Helper
Cost for 1000 Units 197354.50 176167.78Sales @ Rs. 300/Unit
Cost/Unit 197.35 176.17
10000 10000
Overhead/Minute 20.83 20.83
Cost/Minute 36.18 35.62
Minutes Produced 2663.41 2138.46
Labour Expense/Minute
Factory Overheads/Day
Cost/Unit14.78
0Thread Cutting Cost
Cost Component Cost/Unit15.34
Thread Cutting at SourceSeparate Thread Cutting DepartmentMeasurement
Throughput Rate (Per Hour Output)
= 41 = 39
800
Sewing Total
Manufacturing Lead Time(Inventory/Throughput Rate)
=
Inventory (Average WIP in Thread Cutting Department + Inventory in Sewing Line) 400 400
Sewing Total
Nil 400 400
Direct Material Cost 100.00 100.00
1020 =
Labour ExpenseOperators
Helpers
Line Master
Cost Comparison
1
Floor Incharge
QC @ End Line Inspection
Floor QC
Total Labour Expense/Hour
xiv
Appendix G.1
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
Body22-Feb 2980 8-Mar 149 13-Mar 3565 15-Mar 3944 16-Mar 2630 18-Mar 2862 20-Mar 2990 22-Mar 1200
10-Mar 275917-Mar 1090 19-Mar 1088 22-Mar 920 23-Mar 2400
Lining 18-Mar 1015 18-Mar 394422-Feb 690 11-Mar 657 24-Mar 304
Net23-Feb 1035.3 18-Mar 1015
Packing
28-Jan
17-Mar
Grey Issue to Printing/Dyeing (Mts)
Receive Printing (Mts) Print Checking (Mts) Cutting Sewing
4500144645 1664 A
3904
UU76786
Smocking
Black
Lining
Average
Thread Cutting Finishing
Ship Date
Lead Time
Late Days
Production Track
Style #
PO #
PO Date
Due Date
Sheet #
Qty
24-Mar
31 Days
7 Days
Fabric
Body 72 cm
17.5 cm
xv
Appendix G.2
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
Body19-Feb 2810 26-Feb 923 6-Mar 4375 9-Mar 3720 10-Mar 3720 11-Mar 140 12-Mar 130 19-Mar 3680
28-Feb 1835Lining 12-Mar 870 13-Mar 870
19-Feb 680 26-Feb 66213-Mar 1480 15-Mar 970
Net18-Feb 980 26-Feb 955 15-Mar 1190 16-Mar 1700
Average Ship Date 24-Mar
PO # 4500144646 Sheet # 1664 B Body 72 cm
Style # UU76786 Due Date 17-Mar White Fabric
Lead Time 36 Days
PO Date 28-Jan Qty 3680 Lining 17.5 cm Late Days 7 Days
Production TrackGrey Issue to
Printing/Dyeing (Mts)Receive Printing (Mts) Print Checking (Mts) Cutting Sewing Thread Cutting Finishing PackingSmocking
xvi
Appendix G.3
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
Body19-Feb 3180 28-Feb 3111 12-Mar 4570 13-Mar 4200 13-Mar 1750 16-Mar 1050 17-Mar 1070 20-Mar 424
Lining 14-Mar 2444 17-Mar 2400 18-Mar 870 22-Mar 372019-Feb 780 26-Feb 778
18-Mar 740 19-Mar 2200Net
18-Feb 1080 11-Mar 684
Average Ship Date 24-Mar
PO # 4500144647 Sheet # 1664 C Body 72 cm
Style # UU76786 Due Date 17-Mar Blue Fabric
Lead Time 34 Days
PO Date 28-Jan Qty 4144 Lining 17.5 cm Late Days 7 Days
Production TrackGrey Issue to
Printing/Dyeing (Mts)Receive Printing (Mts) Print Checking (Mts) Cutting Sewing Thread Cutting Finishing PackingSmocking
xvii
Appendix G.4
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
Body17-Feb 2650 16-Mar 2580 13-Mar 894 18-Mar 3504 18-Mar 2628 19-Mar 873 22-Mar 2240 24-Mar 3328
Lining 19-Mar 876 20-Mar 2625 23-Mar 121017-Feb 640 16-Mar 625 17-Mar 3200
Net16-Feb 910 13-Mar 894
Average Ship Date 24-Mar
72 cm
Fabric
Lead Time 36 Days
17.5 cm Late Days 7 Days
Production TrackGrey Issue to
Printing/Dyeing (Mts)Receive Printing (Mts) Print Checking (Mts)
PO # 4500144649 Sheet # 1664 D Body
Style # UU76786 Due Date 17-Mar Lush lawn
PO Date 28-Jan Qty 3456 Lining
Cutting Sewing Thread Cutting Finishing PackingSmocking
xviii
Appendix G.5
Date Qty (Mtrs) Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
Body11-Feb 3220 20-Feb 3125 24-Feb 5051 26-Feb 3200 27-Feb 2685 8-Mar 120 9-Mar 120 18-Mar 3840
Lining 26-Feb 1000 28-Feb 1450 9-Mar 420 10-Mar 420 19-Mar 30410-Feb 785 20-Feb 768
10-Mar 470 11-Mar 440Net
10-Feb 1180 22-Feb 1158 11-Mar 880 12-Mar 880
12-Mar 910 13-Mar 910
13-Mar 1080 15-Mar 1077
15-Mar 300 16-Mar 300
Average Ship Date 24-Mar
PO # 4500144651 Sheet # 1664 E Body 72 cm
Style # UU76786 Due Date 17-Mar Top - Pink Nova Fabric
Lead Time 42 Days
PO Date 28-Jan Qty 4144 Lining 17.5 cm Late Days 7 Days
Production TrackGrey Issue to
Printing/Dyeing (Mts)Receive Printing (Mts) Print Checking (Mts) Cutting Sewing Thread Cutting Finishing PackingSmocking
xix
Appendix G.6
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
Body16-Feb 2780 20-Feb 2698 9-Mar 4298 11-Mar 3720 12-Mar 3720 15-Mar 810 16-Mar 830 13-Mar 1580 20-Mar 1136
Lining 16-Mar 2160 18-Mar 900 15-Mar 1419 22-Mar 84817-Feb 680 20-Feb 662
17-Mar 730 19-Mar 750 16-Mar 1938 23-Mar 1640Net
17-Feb 960 3-Mar 938 22-Mar 1190 17-Mar 1966 24-Mar 56
18-Mar 1066
19-Mar 1748
20-Mar 2811
22-Mar 3417
23-Mar 2841
24-Mar 4380
Average Ship Date 24-Mar
PO # 4500144653 Sheet # 1664 F Body 72 cm
Style # UU76786 Due Date 17-Mar Daisy Fabric
Lead Time 37 Days
PO Date 28-Jan Qty 3680 Lining 17.5 cm Late Days 7 Days
Production TrackGrey Issue to
Printing/Dyeing (Mts)Receive Printing (Mts) Print Checking (Mts) Cutting Sewing Thread Cutting Finishing PackingSmocking
xx
Appendix G.7
C
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
A20-Mar 550 22-Mar 532 27-Mar 2208 29-Mar 1220 6-Apr 213 7-Apr 330 12-Apr 1200
7-Apr 430 8-Apr 300B
20-Mar 580 22-Mar 558 8-Apr 420 10-Apr 580
9-Apr 147C
20-Mar 1150 22-Mar 1118
90 cm
Average Ship Date 12-Apr
42.5 cm
Fabric
Lead Time 24 Days
45 cm Late Days 17 Days
Production TrackGrey Issue to
Printing/Dyeing (Mts)Receive Printing (Mts) Print Checking (Mts)
PO # AT91007 Sheet # 1660 A A
12002-FebPO Date Qty
Style # AT91007-3 Due Date 27-Mar Solid Off White
B
Cutting Sewing Thread Cutting Finishing PackingSmocking
xxi
Appendix G.8
C
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
A6-Mar 535 13-Mar 518 29-Mar 2144 31-Mar 1170 3-Apr 85 9-Apr 1158 12-Apr 1150
B 5-Apr 3906-Mar 560 13-Mar 542
6-Apr 400C
6-Mar 1120 13-Mar 1084 7-Apr 290
90 cm
Average Ship Date 12-Apr
42.5 cm
Fabric
Lead Time 38 Days
45 cm Late Days 17 Days
A
B
Grey Issue to Printing/Dyeing (Mts)
Receive Printing (Mts) Print Checking (Mts)
PO # AT91007 Sheet # 1660 B
PO Date 2-Feb Qty 1150
Production Track
Style # AT91007-3 Due Date 27-Mar Solid Beige
Cutting Sewing Thread Cutting Finishing PackingSmocking
xxii
Appendix G.9
C
Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty Date Qty
A11-Mar 535 27-Mar 514 29-Mar 2146 30-Mar 1170 7-Apr 70 9-Apr 460 9-Apr 580 12-Apr 1150
B 8-Apr 390 10-Apr 435 10-Apr 133011-Mar 560 27-Mar 544
9-Apr 328 12-Apr 265 12-Apr 1670C
10-Mar 1120 27-Mar 1088 10-Apr 378
Sewing Thread Cutting Finishing PackingGrey Issue to Printing/Dyeing (Mts)
Receive Printing (Mts) Print Checking (Mts) Cutting Smocking
90 cm
Average Ship Date 12-Apr
42.5 cm
Fabric
Lead Time 32 Days
45 cm Late Days 17 days
A
B
PO # AT91007 Sheet # 1660 C
PO Date 2-Feb Qty 1150
Production Track
Style # AT91007-3 Due Date 27-Mar Solid Moca Brown
xxiii
C/T Upper 6.39 sec. ,
Lining 1.69 sec
27,000 x 2 sec available
C/T Upper 36 sec. ,
Lining 11.8 sec
27,000 x 3 sec available
C/T 3208 sec
27,000 x 30 sec.
available
144 sec.
24 days
8.08 sec.
2 days
47.8 sec
3 days
3208 sec.
7 days
2
Grey Store
24 days
C/T 144 sec
27,000 x 2 sec.
available
2 days
2
Printed fabric checking
3 days
3
Cutting
30
Sewing
7 days
1
Thread Cutting
C/T 196 sec
27,000 sec. available
1 day
1
Pressing
¼ days
C/T 43 sec.
27,000 sec. available
1
Checking
¼ days
C/T 58 sec.
27,000 sec. available
5
Packing
C/T 153 sec.
27,000 x 5 sec. available
1day
43 sec.
¼ days
58 sec.
¼ days
153 sec.
1 day
196 sec
1day
Production lead time (from Grey issue)- 14.5 days
Processing lead time- 3857.88 sec.
Appendix H
xxiv
S M L XL S M L XL S M L XL S M L XL1738 H 1 160 50 100 10 50 100 10 50 100 10 10 20 10 40
" 2 300 100 110 90 150 210 100 140 190 90 90 180 90 360" 3 380 90 190 100 240 400 200 140 200 100 100 200 100 400" 4 380 80 200 100 320 600 300 120 200 100 100 200 100 400" 5 380 80 200 100 400 800 400 100 200 100 100 200 100 400" 6 380 100 200 80 500 1000 480 100 200 80 80 160 80 320" 7 380 100 200 80 600 1200 560 120 240 80 80 160 80 320" 8 380 100 190 90 700 1390 650 140 270 90 90 180 90 360" 9 380 100 180 100 800 1570 750 150 270 100 100 200 100 400" 10 400 100 200 100 900 1770 850 150 270 100 100 200 100 400" 11 400 100 200 100 1000 1970 950 150 270 100 100 200 100 400" 12 400 100 200 100 1100 2170 1050 150 270 100 100 200 100 400" 13 400 100 200 100 1200 2370 1150 150 270 100 100 200 100 400
1738 H; 1738 G 14 400 100 200 100 1300 2570 1250 150 270 100 100 200 100 4001738 G 15 400 100 200 100 1400 2770 1350 150 270 100 100 200 100 400
1738 G; 1732 A 16 400 80 190 130 1480 2960 1480 130 260 130 130 260 130 5201732 A 17 280 60 120 70 30 60 120 70 30 60 120 70 30 30 60 60 30 180
1732 A; 1732 B 18 350 55 86 136 73 115 206 206 103 85 146 146 73 73 146 146 73 4381732 B 19 350 48 120 120 60 163 326 326 163 60 120 120 60 60 120 120 60 360
1732 B; 1714 A 20 350 43 86 86 43 206 412 412 206 43 86 86 43 43 86 86 43 2581714 A 21 200 50 60 60 30 50 60 60 30 50 60 60 30 30 60 60 30 180
1714 A; 1714 B 22 320 37 114 114 57 87 174 174 87 57 114 114 57 57 114 114 57 3421714 B 23 400 74 148 148 74 161 322 322 161 74 148 148 74 74 148 148 74 444
Detailed Schedule for Drum I
Annexure J.1
xxvi
TotalSheet #Size Wise Output Cumulative Status at End of Day Packed
Day Output
S M L XL S M L XL S M L XL S M L XL1738 F 1 160 50 100 10 50 100 10 50 100 10 10 20 10 401738 F 2 300 100 110 90 150 210 100 140 190 90 90 180 90 3601738 F 3 380 90 190 100 240 400 200 140 200 100 100 200 100 4001738 F 4 380 80 200 100 320 600 300 120 200 100 100 200 100 4001738 F 5 380 80 200 100 400 800 400 100 200 100 100 200 100 4001738 F 6 380 100 200 80 500 1000 480 100 200 80 80 160 80 3201738 F 7 380 100 200 80 600 1200 560 120 240 80 80 160 80 3201738 F 8 380 100 190 90 700 1390 650 140 270 90 90 180 90 3601738 F 9 380 100 180 100 800 1570 750 150 270 100 100 200 100 400
1738 F; 1738 G 10 380 100 200 100 900 1770 850 150 270 100 100 200 100 4001738 G 11 380 100 200 100 1000 1970 950 150 270 100 100 200 100 4001738 G 12 400 100 200 100 1100 2170 1050 150 270 100 100 200 100 4001738 G 13 400 100 200 100 1200 2370 1150 150 270 100 100 200 100 4001738 G 14 400 100 200 100 1300 2570 1250 150 270 100 100 200 100 400
1738 G; 1732 C 15 400 80 190 130 1380 2760 1380 130 260 130 130 260 130 5201732 C 16 280 60 120 70 30 60 120 70 30 60 120 70 30 30 60 60 30 180
1732 C; 1732 D 17 350 55 86 136 73 115 206 206 103 85 146 146 73 73 146 146 73 4381732 D 18 350 48 120 120 60 163 326 326 163 60 120 120 60 60 120 120 60 3601732 D 19 350 43 86 86 43 206 412 412 206 43 86 86 43 43 86 86 43 258
xxvii
Sheet # Day OutputSize Wise Output Cumulative Status at End of Day Packed
Total
Detail Schedule for Drum II
Annexure J.2
Annexure K
Date 22/3 23/3 24/3 25/3 26/3 27/3 29/3 30/3 31/3 1/4 2/4 3/4 5/4 6/4 7/4 8/4 9/4 10/4 12/4 13/4 14/4 15/4
1732-A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Buffer Status 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85
1732-B 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Buffer Status 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90
1732-C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Buffer Status 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
1732-D 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Buffer Status 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
Date 16/3 17/3 18/3 19/3 20/3 22/3 23/3 24/3 25/3 26/3 27/3 29/3 30/3 31/3 1/4 2/4 3/4 5/4 6/4 7/4
Sheet 1738-H 1 2 3 4 5 6 7 8 9 10Buffer Status 10 20 30 40 50 60 70 80 90 100
Sheet 1738-G 1 2 3 4 5 6 7 8 9 10Buffer Status 10 20 30 40 50 60 70
Sheet 1738-F 1 2 3 4 5 6 7 8 9 10Buffer Status 10 20 30 40 50 60 70 80 90
Date 7/4 8/4 9/4 10/4 12/4 13/4 14/4 15/4 16/4 17/4 19/4 20/4
1714-A 1 2 3 4 5 6 7 8 9 10Buffer Status 10 20 30 40 50 60 70
1714-B 1 2 3 4 5 6 7 8 9 10Buffer Status 10 20 30 40 50 60 70 80
Lateness = 3 Days
Lateness = 0 Days
Lateness 2 Days
Lateness = 0 Days
Lateness = 1 Day
Lateness = 4 Days
Lateness = 2 Days
Lateness = 3 Days
Lateness = 2 Days
xxviii
xxx
Annexure 1
Training Needs identified for Managers and Supervisors my Method Apparel Consultancy in the NCR region depicting dismal realities.