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Overall Equipment Effectiveness: Guidelines for the CPG Industry
And Its Suppliers
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Overall Equipment Effectiveness:
Guidelines for the CPG Industry
And Its Suppliers
-
2012 by the Alliance for Innovation and Operational Excellence;
Reston, Va.
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
i
Intended Audience This white paper is intended for all consumer
packaged goods, food and beverage, and pharma-
ceutical manufacturers and their suppliers interested in
implementing a continuous improvement
initiative at the plant level. An Overall Equipment
Effectiveness (OEE) continuous improvement initia-
tive allows companies to expose all losses within their
operations to drive objective and informed
decision making for improvement plans.
This paper is particularly targeted toward companies that have
no prior experience imple-
menting an OEE metric program, or that have been unsuccessful in
completing an OEE initiative. CPG
organizations that have established an OEE program may also find
utility in this white paper as a tool
for sharing OEE best practices with others in the industry.
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AIOE Operational Reliability Solutions Group
ii
Contributors This paper would not have been possible without the
collaboration of those who truly value
operational excellence in manufacturing. The Alliance would like
to thank the OEE team, and in par-
ticular, Platinum Sponsor GE.
Bill Herbes, B & G Foods, Inc.
Robby Martin, Bush Brothers & Company
Phil Phillips , The Coca-Cola Company
Peter Hock (Chair), ConAgra Foods
Scott Butler, Del Monte Foods Company
Shawn Sassaman, Furmano Foods
Erin Bradshaw (Technical Writer) , GE
Robert Gates, GE
Tim Rich, The Hershey Company
Paul Dash, Inventure Foods, Inc.
Mark Hanley, Land OLakes, Inc.
Jeremy Kacuba, Leprino Foods Company
Ben Gibbons , Musco Family Olive Co.
Brett Davis, Musco Family Olive Co.
Leo Robertson , Pearson Packaging Systems
William Cooper, Nestle Purina PetCare Company
Terry Zarnowski, Schneider Equipment
Mike Pieper, Siemens Corporation
Scott Spencer, Snyders-Lance, Inc.
Bill Snow, SPX Flow Technology
Chad Sprinkman, WM Sprinkman Corporation
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
iii
Table of Contents
Introduction
Case Study 1:
OEE Delivers $5 Millioni in Annual Savings
...........................................................................
iv
Business Drivers
............................................................................................
1
Case Study 2:
OEE Enables 10 Percent Increased Efficiency
.......................................................................
2
Getting Started with OEE
..............................................................................
3
Case Study 3:
OEE Reduces Downtime by 39 Percent
................................................................................
5
OEE Implementation Advice
.........................................................................
8
Measurements & Calculations
......................................................................
8
Conclusion
.....................................................................................................
10
Case Study 4:
OEE Reduces Manufacturing Costs 15 Percent
....................................................................
11
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Join the discussion on OEE at http://alliance.pmmi.org
Case Study 1:
OEE Delivers $5 Million in Annual Savings A glass bottle
manufacturer in the U.S. found the business need to grow sales and
meet
quality, consumer safety, and environmental protection goals and
implemented an OEE regimen to meet this sales growth imperative.
Delivering results would not only affect their bottom line, but
would also prove to customers that their company is committed to
innovative, efficient, and environmentally friendly production
practices. To accomplish their goals, they chose to imple-ment an
automated OEE information system to collect and present data from
all steps in bottle making, including batch, furnace, forming,
finishing, inspection and packing. This system rec-orded equipment
downtime events, equipment process data, and rejects automatically,
and required operators to manually input defect observations into
the system.
Additionally, they implemented an automated reporting process to
provide visibility into their operations. Their implemented
solution serves multiple users within the plant - from oper-ators
on the lines to maintenance managers to senior managers who need
quick, graphical re-ports via the web.
As a result of streamlining and standardizing basic OEE
measurements across the plant, the
bottle manufacturer was able to increase production by 5
percent, decrease defects by 25 per-
cent, reduce plant downtime 25 percent, decrease energy
consumption for their furnaces, and
decrease furnace emissions by 80 percent. All of these
improvements add up to deliver savings
of $5 million annually.
The software program that the team
chose to implement interfaced with
the companys installed base of equip-
ment including sensing and inspec-
tion devices, PLCs, and scales and
timing systems to deliver real-time
data on fill variance distribution (art)
and defects. This enabled the improve-
ment team to make more informed
decisions. This is the pinnacle of an
OEE program.
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
v
Introduction Consumer packaged goods (CPG) companies and their
suppliers have been
steadfast in their pursuit of continuously improving their
bottom line while de-
livering high quality products to customers. In support of these
goals, opera-
tional measurement and reporting enables CPG companies to
discern the best-
value opportunities, to assign accountability and to track
progress. Since neces-
sity is the mother of invention, and there has been no single
authorizing group
to set guidelines, operations measurement has sprung up with a
variety of ap-
proaches. Lack of standard terminology and definitions has
hampered efforts to
make comparisons between plants and industries, and leant
confusion to dis-
cussions between vendors and suppliers.
Out of the noise and confusion, Overall Equipment Effectiveness
(OEE) is gain-
ing the broadest adoption as the most powerful, systematic tool
available to
help companies expose losses. OEE enables companies to view
operations
through a consistent and objective set of measurements. Once
opportunity are-
as are identified, management teams can make better data-driven
decisions to
improve operations. Subsequently, it is critical that the OEE
metrics be clearly
communicated and understood in order to sustain and build on
great results.
This white paper will establish a roadmap for a systematic
approach to measur-
ing and tracking OEE for any piece of equipment or process, and
present stand-
ard guidelines for initiating an OEE program. The authors are
members of a
team established by the Alliance for Innovation and Operational
Excellence for
Overall Equipment Effectiveness, and will share best practices
about how to re-
view the financial business drivers behind establishing an OEE
metric regimen,
how to get started, and how to gauge the efficacy of OEE
programs.
To accomplish these goals, the authors will share success
stories from CPG com-
panies that are achieving operational excellence, as well as
details about how
these companies started their journeys and moved through the
phases of the
OEE roadmap. By establishing tangible user experiences within
the framework
of good project execution, the authors anticipate that companies
new to OEE
metric reporting can achieve faster implementation and broader
workforce ac-
ceptance, accelerating their continuous improvement initiatives
for equipment
effectiveness.
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AIOE Operational Reliability Solutions Group
vi
Figure 1: OEE: Pervasive Driver of Business Performance
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
OEE Business Drivers Every CPG program manager must be able to
justify the financial and manpower commitment of
undertakings such as an OEE metrics program. In addition, such a
program is doomed to failure with-
out strong alignment to company-wide metrics and goals.
Whether ownership is public or private, the end goal of the
business is to continually increase
value to the owners. One of the largest value drivers for
enhanced operational efficiency is its impact
on cash flow. The three main financial components of cash flow
are sales growth, cost and capital
investment. A thorough OEE platform will improve elements within
each of these areas (Figure 1).
Sales Growth The three major performance areas within CPG
plant-level operations that affect sales growth
are quality, service and innovation. An OEE regimen touches
these metrics at a fundamental level.
Measuring OEE and eliminating production upsets will result in
greater process stability and product
consistency. This, in turn, reduces rejects and rework, and
allows for fewer out-of-specification prod-
ucts. The end result is consistent delivery of in-spec product
to the customer. When it comes to inno-
vation, an OEE regimen ultimately leads to a deepened
understanding of equipment capabilities,
enabling better utilization of technology for new product trials
and deeper process knowledge at
new product launches.
Cost The most apparent advantage that is gained in implementing
an OEE regimen is a reduction in
operating costs. In a production environment, operating costs
stem from four key performance di-
mensions: safety, material usage, labor productivity and
overhead. The first of thesesafetyis a goal
in and of itself as well as a cost consideration. OEEs
connection to safety is obvious. An effective OEE
improvement program will reduce the number of human touches on a
given machine, such as the
clearing of jams, thereby decreasing the risk for
OSHA-reportable incidents. Because OEE exposes all
losses, it directs management to address the root causes of
scrap and waste, thus enabling fixes that
result in decreased material costs. CPG manufacturers are able
to drastically reduce the amount of
rejected material by targeting their largest losses, such as
reductions in purge losses during sanitiza-
tion, and product or packaging defects that occur when a system
upsets. OEE enables focus and pri-
oritization of activities to maximize uptime and drive out stops
and non-productive time. Because
OEE affords a view of all losses at a very granular level, the
causes of hidden inefficiencies can be
exposed. This leads to increased labor utilization, decreased
unplanned overtime costs and de-
creased overhead expenses such as power and water utilities.
Capital Investment Since capital investment is usually a
long-term, strategic decision, improvement teams often
overlook the interplay between investment decisions and OEE.
Companies who achieve OEE im-
provement can generate higher output and flexibility with their
existing asset base.
This enables them to avoid capital investments driven solely by
productivity gaps. Capital avoid-
ance has the added benefit of MRO parts inventory avoidance.
Additionally, exposing and reducing
failures prolongs the useful lifecycle of existing equipment,
thus lengthening the amount of time
between capital expenditures. Finally, OEE has a significant
impact on the amount of cash companies
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Case Study 2:
OEE Enables 10 Percent Increased Efficiency After making a
decision to
drastically change the business model, a large gum producer
found itself needing to increase its flexibility and efficiency to
keep up with a growing demand. In order to solve this problem, the
producer used an OEE process model to identify areas for growth and
opti-mize production performance.
The project team chose to pilot an OEE program on a clearly
underperforming packaging line that offered high-volume through-put
with a mix of manual and auto-mated procedures, and chose a
pro-duction management software suppli-er with experience in the
OEE space as a partner in implementing this project. First, the
team connected the islands of machines on the pilot line creating a
Profibus network to a new front-end PLC, which caused no disruption
to on-going production. Next, an Ethernet link from the front-end
PLC to the existing OPC Server provided a data route to a database.
The software module the company chose accesses the data in the
database and delivers a Scoreboard to a plasma screen on the line.
In the pilot and today the Scoreboard charts the shift productivity
curve and displays key information such as the current
productivity, the line stoppage time, total production, production
per minute and waste. The software also produces reports showing
the productivity curve and stoppage times.
This OEE dashboard captures product line, downtime event,
and
waste information in a user-friendly timeline format.
Additional-
ly, the system records detailed information for each
downtime
event, allowing the improvement team to understand or
analyze
the root cause for multiple events of the same type. With
this
level of detail on production line status and loss data, the
team
can quickly and easily identify problem areas and can drive
im-
provements that have meaningful impact.
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
must tie up in inventory. Product changeovers are clearly a
loss. Companies without an effective OEE
improvement program will try to minimize changeovers. As a
result, production cycle times are long,
and inventories must grow to accompany them. OEE improvement
enables companies to build the
technical competency to neutralize the losses from increased
changeovers, and to achieve rapid and
successful restarts after each change. OEE improvement efforts
which include focus on rapid change-
over provide a powerful means to generate a rapid cash infusion.
In this way, decreased inventory
levels generate cash for investment in research, marketing,
sales, and manufacturing improvement.
Closing Financial Thoughts When starting an OEE regimen, program
managers need to secure buy-in from all major stake-
holders. These stakeholders are likely to see the value that an
OEE-based continuous improvement
program adds to their bottom line when specific benefit impacts
are broken down into financial per-
formance drivers. Additionally, their support will form the
foundation for establishing project success
metrics. Oftentimes, OEE programs fail because they are not
delivering the value intended. This
typically occurs when the safety, quality, cost, delivery and
working capital impact of operations per-
formance is not clearly understood, or when a project scope and
expected results are not clearly
defined and agreed upon. Program managers should meet with
stakeholders to define OEE imple-
mentation success based on the metrics that the given group of
stakeholders cares about most. This
will ensure that the program will be based on realistic program
practices, thus enabling successful
implementation of a strongly grounded OEE regimen.
Getting Started with OEE Engaging stakeholders in an OEE program
is not as hard as it may seem, as communicating a
plan to increase sales growth and cash flow is generally greeted
with a positive response. The real
work comes with designing an OEE program that includes the right
scope and scale. If an OEE pro-
gram is poorly executed, it may not be allowed to expand.
Similarly, if the program is too large, it
may not show value quickly enough to gain momentum. To help
avoid these pitfalls, the authors will
be very prescriptive on the OEE roadmap (see Figure 2).
Figure 2: OEE Roadmap
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For this paper, the authors will focus on the first
stepinitiationand will review the best practic-
es to help program managers achieve this crucial step in moving
along the operational excellence
journey. Understanding how to be effective in this step will
enable success in the other steps
throughout the OEE journey. The initiation step involves four
consecutive stages: Plan, Do, Check,
and Act. Executing each of these phases in order will provide
integrated transitions from planning to
implementation.
Plan Like all great projects, a successful, sustainable OEE
regimen starts with a clearly defined scope
and articulated deliverables that engage the key stakeholders.
The success metrics chosen for the
OEE regimen should be impactful, easy to track and easy to
understand. During this development
phase, it is best to limit the first OEE scope to one area that
can be reasonably expected to succeed;
over-promising and under-delivering will immediately disengage
stakeholders, resulting in failure. To
avoid this, it may be advisable to start with a smaller pilot
project that enables the program to estab-
lish a foothold. The lessons learned here will prove valuable as
the OEE metrics are rolled out to larg-
er areas.
It is best to start on a department or line that is critical to
business performance and has signifi-
cant improvement opportunities. In this phase, it is important
to define the analytical and report
deliverables first, and then determine the primary data
collection elements required for these deliv-
erables. The program can be started small and grown with
success; this will enable program manage-
ment to shake out the bugs while still logging some gains from
the process.
Many people start by driving down to a product line and
logging:
Schedule time (both value added and non-value added)
Production potential at zero loss
Planned downtime (type, location, duration)
Unplanned downtime (type, location, duration)
Production rate
Scrap and/or rework amount
An OEE program startup cannot be handled by one person alone.
This new metric will affect the
entire production team, from plant managers to equipment
operators. It is of utmost importance to
ensure the appropriate level of engagement from the operators in
particular, as they bear direct
witness to the results and issues that are now under greater
scrutiny. Once managers, supervisors,
and operators align on the value of this data collection, in
terms of its importance to the programs
future success and impact on the health of the business, the
program management team can more
easily ensure accountability.
The most successful OEE system designs are developed by
cross-functional teams.
Collaboration between quality, engineering, production, floor
associates and management will
promote engagement and uncover the most important organizational
needs. However, it must be
remembered that too many nice to have features could doom the
project. The key to a robust data
collection system is to collect only what is needed at the
granularity that is needed. Two factors drive
the need for very tight scoping of data requirements: resolution
and data management.
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
These reports show the same fault data
analyzed by shift (top) and by production line
(bottom).
This functional view enables the team to
prioritize improvement opportunities through
comparative analysis, validating and verifying
the business case for individual projects.
Case Study 3:
OEE Reduces Downtime by 39 Percent This OEE improvement program
took place in a large brewery facility. Within its company,
this
plant is the second largest brewing plant, producing over 2.7
million hectoliters annually. The
bottling line within the plant was already using a software
program to record and track downtime
events. The in-place program promoted operators to record
information on downtime events lasting
five minutes or more. This manual approach to OEE allowed them
to realize significant capacity gains
but proved to be very time-intensive for the operators. For this
reason, it was easy to develop a busi-
ness case for a more accurate, automated, and granular system.
Additionally, the company wanted
their new system to automate the analytics and reporting process
and to deliver these results on the
web.
They installed an automated system was installed that interfaced
with sensors at various points
on the production line. An analytical software program modeled
all machines on each line, giving a
detailed description the equipments current state. A
corresponding electrical signal in the database
linked to each such description (stoppage, shortage,
lowering/raising of forklift, etc.). Using this in-
formation, the software can determine if at a given time a
machine has stopped, or released a faulty
product, or performed its operation incorrectly, or transferred
to another machine a set number of
items. Additionally, the project team added functionality to
allow operators to add more data on
production line events. In the last phase of the project, the
brewer invested in a web-based solution
that provides reports in real time.
After project implementation, the brewery saw a 39 percent
decrease in the total number of
mechanical and electrical downtime events and increased
availability of human resources. They also
have active access to information on breakdowns and stoppages,
enabling the continued elimination
of losses.
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Resolution is the ability of the data collector to discern and
record the event accurately, and can
be thought of in terms of time and event description. For
example, an operator cannot be expected
to give information on something he cannot see or does not
understand. This lack of discernment
could be because the event happened too quickly, or the operator
was otherwise engaged and did
not have enough evidence to determine what happened after the
fact. Very often, technology can
open new vistas of data resolution, but we should never overlook
the importance of operator en-
gagement and input.
Data management refers to the practicality of collecting,
organizing, analyzing and reporting the
information that is collected. Highly granular data sets must be
sifted for meaningful patterns, and
that requires much more automation than can be managed
effectively with standard desktop ana-
lytics. The time spent understanding and optimizing the data
collection process will pay off in the
first OEE implementation as well as every future OEE
implementation. At the start of the OEE imple-
mentation, it is suggested that initial focus be on
effectiveness. Once managers are satisfied with the
quality of data and analysis, focus can shift to improving the
efficiency of the data system.
The final aspect to address in the planning phase is to ensure a
mechanism to ensure the accu-
racy of the OEE data and to efficiently communicate results with
all of the stakeholders. In order to
communicate results and trends, management should set up a
cadence for data review and reporting.
Ideally, OEE discussions should be integrated into regular
daily, weekly and monthly business review
& planning meetings.
In order to ensure the accuracy of the data, a system of
ownership and oversight is needed. On
a daily basis, line data owners should scrub their data to
correct errors and provide feedback to the
operators to teach or reinforce good data collection methods. At
the plant level, a single owner
should be tasked to inspect the daily verification activities
and to devise methods and systems to
improve the information value generated. This data verification
process should be allowed to evolve,
but the frequency, accountability, recognition, and
reinforcement of these reviews must happen
consistently in order to instill the value of the OEE regimen.
When possible, the teams most affected
by the new process should be afforded the ability to refine the
data collection method as well as the
look and feel of the reports. One approach would be for the
program management to provide the
teams with a starting template, then afford the teams with the
ability to provide input on what
works and what needs to be modified. Through this approach, the
teams will gain ownership of the
report and the data, thus increasing data accuracy and
accountability. After an effective skeleton has
been designed for the OEE regimen, program managers can act on
the lessons gleaned therein.
Do In order to drive aligned action on the insight gained from
the OEE implementation steps, man-
agers must ensure that the necessary stakeholders feel motivated
and empowered to support the
OEE process and thus effect change. For this reason, it is
important to put an organizational model in
place to direct and encourage sustained support of the OEE
regimen at this phase of initiation. Em-
ployees at various levels of the organization will be expected
to measure performance and guide
changes, so a formal model for driving behavior change allows
for reinforcement and communica-
tion of the value that these change drivers add.
Two effective models that are widely accepted are the Hiatt
ADKAR and the Galbraith Star. The
Hiatt ADKAR model expresses the need for awareness, desire,
knowledge, ability, and reinforcement
of the initiative to all relevant stakeholders. The Galbraith
Star organization model expresses the
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
& Its Suppliers
need for ongoing support for the various initiative tasks,
people and skills, structure, information,
decision processes, and rewards. These popular models are two
examples that the authors recom-
mend examining, but it is important that program managers employ
a strategy that is commonly
accepted and understood throughout their organization.
The largest pitfall that many OEE programs fall prey to at this
point in the initiation phase is
holding the wrong person or group of people accountable for the
wrong metric in a way that dis-
courages accurate data collection and reporting. Employees at
all levels will seek to exclude OEE
losses for which they do not want to be held accountable, and
this can be detrimental to an OEE
program. Excluding important data elements will restrict
visibility to the available areas for improve-
ment, leading to diminished and perhaps distorted decision
making processes. Managers must limit
the scope to which accountability is assigned so as to include
only data elements that are within the
spans of control of those collecting the data. A commitment from
the stakeholders for open trans-
parency, and not punishment, is critical at this juncture.
Misuse of the accumulated data will under-
mine trust and weaken chances for successful implementation of
OEE systems and improvement
initiatives.
Check This stage of the program initiation for OEE is a holistic
review and refinement of the program in
place. A review should be made of the gaps in the data
collection process, including any gaps that
may exist in design, training, and daily execution of the OEE
metric. It is important to review the data
reporting and analysis process to ensure calculations and
reports are efficient, accurate, and timely.
Lastly, the most crucial element to address is the utilization
of the OEE metric to inform activity,
track progress, and measure results. If the newly implemented
OEE metric is not used to improve
business performance and results, all of the accumulated insight
into the process is meaningless and
the OEE journey will quickly come to an end either through a
lack of results or apathy.
Act Natural areas for improvement will fall out of the data
collected, and this awareness must be
used to tackle large inefficiencies and improve overall
performance. These improvement areas will
most likely require the attention of an improvement team to
introduce necessary process, equip-
ment, or operating procedure changes. These improvements can be
in the form of the corporate
continuous improvement process, but often fall into broad
categories of improved communication,
planning, maintenance, or operations.
There are many processes and tools available for improvement.
Whatever method is adopted,
simple, sustainable improvements can make large differences in
OEE and productivity. Additionally,
measurement of OEE before and after changes will support
continuous improvement throughout the
life of equipment and processes. It is at this point that
program managers can explore expanding the
successes achieved in initial OEE programs to new lines,
departments, and processing stages. Once
the OEE metric has been proven to drive improvement and
performance, managers can grow the
OEE program to expose all operational inefficiencies. As the OEE
program gains traction, program
management must move to prioritize changes for the largest
impact, establish OEE as the foundation
for all plant-level loss exposure and subsequent decision
making, and monetize the improvements
driven by the plant-wide adoption of OEE.
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OEE Implementation Advice In order to better equip CPG managers
to initiate an OEE programs, the authors have the follow-
ing advice from industry experts in implementing OEE
programs:
Dont be alarmed by initial drops in efficiency percentages.
Proper calculation of OEE will
typically drop a plant or line from 90110 percent performance to
5080 percent OEE.
Overall performance has not dropped off; rather, the OEE program
is measuring all losses so
that they can be eliminated. Educating the plant floor and first
line supervision on how OEE
is calculated will help with buy-in of the new, lower
metric.
Dont make excuses. OEE only makes sense if all downtime and
uptime are included in the
calculations. Plants or lines should not be permitted to take
out events; automated data col-
lection and calculation mitigates this risk. Changeovers,
sanitation, and maintenance are all
losses that can be minimized, if not eliminated.
Dont underestimate the need for change management. Structured
programs like the AD-
KAR Model will ensure that key people and steps are not
overlooked in the process, and will
help ensure that gains are sustained.
Dont underestimate the need to communicate. An OEE journey is
predicated on changing
the culture toward one of honest root cause analysis. This must
be demonstrated by the
entire leadership team to the plant floor. Visual controls like
display boards near lines or at
meeting sites indicating performance and cost metrics are
invaluable to show that leadership
cares about results.
Measurements & Calculations Thus far, discussion has focused
on the implementation issues of an OEE regimen. In order to
drive corrective action and continuous improvement, certain
detailed calculations and analytics must
be developed, as well. At a high level, OEE is a ratio of the
acceptable units produced to the potential
units that could be produced over a specified interval. This
metric is certainly very easy to under-
stand; unfortunately, it does not give us actionable data. We
must break OEE down further to ex-
pose, prioritize and address improvement opportunities.
At a granular level, OEE is calculated as the product of three
percentages: availability, rate per-
formance, and quality. All losses identified through the data
collection process can and should be
attributed to one of these three categories in order to
systematically drive change at the appropriate
level and magnitude.
OEE =
Availability (%) x Rate Performance (%) x Quality (%)
Availability describes the losses that result from downtime, both
planned and unplanned.
Some of the most common types of availability losses result from
maintenance and clean-
ing activities, line changeovers, equipment failures, starvation
due to missing input materi-
als upstream, and blockages due to outages in downstream
conversion work centers or
handling processes.
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
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Rate performance describes the losses that result from running
the equipment at speeds below
the target rate. Rate losses inherently occur during ramp-down
and ramp-up around machine
stops, or from machine settings that differ from the target
rate. The target rate is generally de-
fined as the best demonstrated instantaneous rate that an SKU
can run through the chokepoint
of the production system. A machine may run different SKUs at
different rates, but there should
be only one target rate for each SKU for that machine.
Rate is a very important metric that is used by many functions
to plan capital investments
and to plan and execute the production schedule. Table 1 will
help sort out the different
ways to look at rate. Each approach is valid; the important
thing to remember is that only
the target rate is relevant to OEE.
Quality describes the losses that result from
quality defects. These losses must take into ac-
count all scrap and rework incurred over the
identified interval for the given process. Sanita-
tion defects, out-of-spec production, in-process
damage, and incorrect material usage are some
of the common examples of quality losses. For
process systems that deliver continuous flows or
bulk batches, the output may be graded based
on certain parameters such as percent purity,
percent solids and density. Where applicable,
these output parameters figure into the
quality component of the equation for OEE,
above.
Once it has been identified how all data ele-
ments fit into each category, the overall equip-
ment effectiveness may be calculated for the
process. It is important to note that continuous
and discrete operations should be calculated
separately , as these two types of processes tend
to operate at different baselines.
Calculating these values separately will ensure
that one area of improvement is not overshad-
owed by a high efficiency in another portion of
the larger process. A separate procedure must be used to roll up
multiple OEE metrics at various
parts of the plant to obtain a larger OEE rating overall.
*Rates for each line can be SKU-specific; there should be
only one target rate for each SKU on a given line. Differ-
ent lines may have different rates for the same SKU.
Metric Definition
Ideal Rate*
The highest sustainable instantane-ous line rate on the line
constraint that Operations, Engineering, and R&D believe can be
achieved over the next five years that: (1) Has a technical basis
for achievement, (2) Does not require a capital appropria-tion for
capacity increase
Theoretical Max Rate (T-Max)*
The engineering or OEM-designed instantaneous rate at the
chokepoint unit operation.
Locked Tar-get Rate (LTR)*
The maximum demonstrated pro-duction rate, expressed as units
produced per uptime minute. LTR excludes losses related to input
material deficiencies, production stoppages, production slow-downs,
ramp-ups, ramp-downs, quality or rework losses, etc.
Planning Rate*
The rate used for production sched-uling based on a recent
survey of throughput capability of the system, factoring in
production efficiencies. Planning rates may or may not in-clude
changeover or line set-up ime, depending upon the platform.
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Overall Equipment Effectiveness: Guidelines for the CPG Industry
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Case Study 4:
OEE Reduces Manufacturing Costs 15 Percent A Fortune 150
consumer packaged food company found it imperative to drive
continuous man-
ufacturing improvement in order to generate cash flow that will
fund marketing and innovation and
to grow sales and margin. Their strategy to meet this goal
included developing and deploying a bal-
anced score card using OEE as a key performance indicator. In
analyzing the current state of their
operations, the company was faced with consolidating performance
metric terminology and calcula-
tions for over 200 production lines in 30 plants to gain
enterprise OEE visibility.
The company identified a very specific execution plan which
included the following steps: define
terms, calculation methods and system specifications; obtain
capital approval; select an automation
vendor; and roll-out OEE system to plants iteratively. Each roll
out included shop floor equipment
ERP updates, local configurations, operator training, and system
validation. Because this process was
iterative, the company was able to incorporate learnings to
succeeding roll-out plans.
Their OEE program roll-out was completed on time in less than 24
months and under budget.
Subsequently, OEE data visibility supported a 5 percent
improvement in cumulative annual cost and
productivity, 15 percent reduction in manufacturing costs, a
decrease in recordable incidents, and
improved quality and service. Additionally, they now have
visibility to line, plant, and technology
platform performance and a robust system to product timely and
accurate data and reports. Produc-
tion potential and productivity losses can be uniformly
quantified to ensure inefficiencies are objec-
tively addressed. This OEE program enables the company to
increase their profitability and lead the
industry in manufacturing excellence.
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Conclusion This paper has provided a foundation for plant-level
continuous improvement initiatives on
which consumer packaged goods, food and beverage, and
pharmaceutical companies can build. One
cannot improve what cannot be measured, and this is most true in
the manufacturing world. Imple-
menting OEE initiatives in a structured and calculated manner
ensures that results will be accurate
and actionable for real cost savings. Streamlining and
standardizing OEE regimen initiation and adop-
tion enables efficient project management, objective decision
making, and cost savings that are sus-
tainable and expandable, enabling growth and adding to the
bottom line.
It is important to limit the scope of the OEE implementation
project to a portion of the plant
where improvement is realistic and necessary. Most OEE programs
fail when the initial boundaries
and goals for the initiation stage are not clearly defined or
well thought out. Spending the majority of
time up front to understand how and why each data point is
important to measure will lead to a
smoother execution and adoption by the most essential
stakeholders; without this buy-in, long-term
success will not be supported or promoted. Once the initial
process is rolled out, management must
take time to refine the data collection, analytics, and
reporting processes with those most affected
to ensure that the program is sustainable. Rushing any portion
of the design and refinement is not
recommended.
It is also important to note that in order to drive and maintain
process changes, program man-
agement must secure employee support on multiple levels. This
involves being clear and transparent
in the benefits and goals of an OEE program, enabling
appropriate behavior, and providing continu-
ous feedback on progress and gains. Employees at all levels will
attempt to omit data elements for
which they do not feel they are responsible. This will skew
results, and can lead to uninformed deci-
sion-making. For this reason, it is beneficial to adopt an
organizational model to guide the companys
approach to OEE program promotion.
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