How to Perform DIY Production Scheduling to Make the Most of Your Production Assets February 18, 2015by Hugh Walters SHARE: Useful ideas for maximizing the power of Microsoft Excel for Supply Chain Analysis, Part II This is the second post in a three-part series that describes how toperform desktop network optimization, job scheduling and vehicle routing with nothing but Microsoft Excel. Future posts will focus on forecasting and supply chain finance. We hope you find these topics interesting and encourage you to reach out to Hugh with any questions. Introduction In my previous post, I talked about performing a desktop transportation/ network optimization. This was an interesting class of problems that produced valuable information and insights regarding the cost and service components of a distribution network. These problems require a good bit of pre-work related to data gathering and analysis, but the worksheet setup is fairly straightforward, perhaps even intuitive. The job scheduling problem requires less pre-work, but the set-up is more complicated and less intuitive. This makes it more difficult to explain…at least in my mind. However, the benefits are much more tangible. If organized properly, the solution methodology can be used several times per day to schedule and re-schedule work. Further, analyzing the results will reveal the location of bottlenecks and opportunities to streamline operations. At the simplest level, the objective of these problems is straightforward: schedule production to get as much work done as possible in the shortest amount of time. However, we will modify the objective slightly to make the problem more realistic. Production orders will be organized such that groups are completed at approximately the same time. Think of this as a way to have specific production orders completed by a certain cut-off time or cut-off date. To solve this problem, I leverage the idea that solving an optimization problem consists of two distinct but connected parts: problem set-up and solution search. Like my other post, Microsoft Excel will be the tool for problem set-up and solution search. However, since this class of program does not lend itself to searches based on linear programming techniques, we will once again use the Evolutionary Solver in Excel (released in version 2010) to search for the solution. Characterizing the Problem In this situation, pretend that you are the manager of a value-added service (VAS) operation. You are responsible for scheduling the jobs through one of eight VAS processing lines. Your lines all have the same capabilities. However, because of differences in equipment, space, experience, and
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How to Perform DIY Production Scheduling to Make the Most of Your Production Assets February 18, 2015by Hugh Walters
SHARE:
Useful ideas for maximizing the power of Microsoft Excel for Supply
Chain Analysis, Part II
This is the second post in a three-part series that describes how toperform desktop network
optimization, job scheduling and vehicle routing with nothing but Microsoft Excel.
Future posts will focus on forecasting and supply chain finance. We hope you find these topics
interesting and encourage you to reach out to Hugh with any questions.
Introduction
In my previous post, I talked about performing a desktop transportation/ network optimization.
This was an interesting class of problems that produced valuable information and insights
regarding the cost and service components of a distribution network. These problems require a
good bit of pre-work related to data gathering and analysis, but the worksheet setup is fairly
straightforward, perhaps even intuitive.
The job scheduling problem requires less pre-work, but the set-up is more complicated and less
intuitive. This makes it more difficult to explain…at least in my mind. However, the benefits are
much more tangible. If organized properly, the solution methodology can be used several times
per day to schedule and re-schedule work. Further, analyzing the results will reveal the location
of bottlenecks and opportunities to streamline operations.
At the simplest level, the objective of these problems is straightforward: schedule production to
get as much work done as possible in the shortest amount of time. However, we will modify the
objective slightly to make the problem more realistic. Production orders will be organized such
that groups are completed at approximately the same time. Think of this as a way to have specific
production orders completed by a certain cut-off time or cut-off date.
To solve this problem, I leverage the idea that solving an optimization problem consists of two
distinct but connected parts: problem set-up and solution search.
Like my other post, Microsoft Excel will be the tool for problem set-up and solution search.
However, since this class of program does not lend itself to searches based on linear
programming techniques, we will once again use the Evolutionary Solver in Excel (released in
version 2010) to search for the solution.
Characterizing the Problem
In this situation, pretend that you are the manager of a value-added service (VAS) operation. You
are responsible for scheduling the jobs through one of eight VAS processing lines. Your lines all
have the same capabilities. However, because of differences in equipment, space, experience, and
Route 1 it is possible to re-sequence the stops and reduce the distance by 80 units, a 20%
reduction. The results look like this:
Early in first article mentioned that there was a way to group the stops to speed up and simplify
the solver routine. One way to perform this grouping is to divide the stops into sections. One of
the simplest ways to do this is through an angular sweep of the stops produced by dividing the
graph into equal 120 deg sections. The stops that fall into each section can then be optimized
using the techniques similar to the ones discussed here to obtain faster solutions that are much
closer to optimal.
Vehicle routing is a core competency for many companies and improvements result in improved
asset efficiency, reduced cost, and improved customer deliveries. Some companies have produced
closed-loop routes over time, but never reviewed them in any systematic way to insure they
remain efficient as routes of deliveries are added or deleted. In some cases, these routes have
been run for years without a review to determine if there are opportunities to consolidate or
reorganize routes.
We believe this is a huge opportunity to save money and miles and would like to review the way
your organization performs its routing. Please contact me to discuss ways that Centric can help
you review your routes and determine opportunities for improvement.
Addressing uncertainty in sales plans with supply chain techniques can become a key differentiator and a competitive weapon. Our chief weapons are time and flexibility.
I love manufacturing. The idea of making something that people want to buy fills me with a sense of pride. It’s almost a patriotic passion, and it’s for this reason I lament manufacturing’s demise, especially here in Northeast Ohio, my home. I’ve wrestled with the reasons and realize they are many and complicated. I just can’t shake the feeling that we’ve lost our competitive spirit and a desire to win. For my part, I’ve tried to do what I can to promote a higher level of competiveness with the companies where I consult.
Offshore manufacturing is a reality, but the willy-nilly movement of production off our shores over the past two decades has seen a small turnaround in recent years. In my mind, this turnaround has been too slow and the opportunity to bring some of this manufacturing back to the U.S. has not been pursued as aggressively as it should.
One area that continues to astound me is our inability to mount a compelling business case that compares the onshore versus offshore costs of manufacturing, materials, logistics and labor as well as the components of time, return on inventory investment and the risk of the lost sale because inventory is moving in longer supply chains.
The idea of the lost sale is not a new or complicated one, but it is difficult to measure. The most effective means of measurement I’ve seen revolve around assessing sales velocity and understanding the likelihood of a sale. There is also the need to consider stockout situations and assess the likelihood of sales that would have happened.
Although this is a pretty straightforward explanation, it is still difficult to assess and isolate meaningful data. These measurements are still flawed because there is not an effective way to test stockout timing or the purchase of a substitutable item. It is absolutely necessary, however, that lost sales be measured and it is absolutely necessary that steps are taken to prevent lost sales and by extension, stockout situations.
Generally, manufacturers want to sell as much of their wares as possible since they generate profit from each sale. This reveals the nature of the problem: being able to anticipate how much will be sold and how much profit will be made requires knowledge of future events. There is no crystal ball to see into the future, and the farther we look, the more uncertain we become. We are left with making educated guesses about the future, and the only thing we know for sure is that more information results in better guesses. Therefore, addressing uncertainty in our sales plans with supply chain techniques can become a key differentiator and a competitive weapon. Our chief weapons are time and flexibility.
As a manufacturer and supplier, selling the benefits of additional planning and reaction time to a retailer is critical. What can be done with this additional time? Ideally it can be used to increase sales by focusing on activities related to adjusting and refining actions to meet future demand. Where does the time come from? When viewed within the context of an offshore import there are multiple time buckets including:
In host country
At port of embarkation (incl. customs clearance)
Transit
At port of debarkation (incl. customs clearance)
In destination country enroute to destination
This can easily take three to four weeks, a significant portion of a selling season. The example below may better illustrate the benefits of additional time:
A national retailer gets its house brand of snow shovels from an offshore supplier. The process
they follow includes reviewing historical data to forecast a sales quantity, placing an order in
March for delivery in September and distributing to retail locations throughout October for sale
throughout the winter season. Last year a sales executive at a Northeast Ohio (NEO) [PU1] manufacturing company noticed
that the shovels had been OOS (out-of-stock) at her local store. She inquired why the shovels had
been OOS so long and discovered that because the shovels had all been distributed in October, it
was difficult, if not impossible; to move products back through the network for redistribution. As part of the executive team at her company, the sales executive is very interested in finding
ways to consume her company’s winter production capacity as well as making inroads with a
large national retailer. She puts together some numbers to determine if there is a compelling
business case. She estimates that a winter storm gives a one-week warning and this becomes the order lead time
for new shovels. The shovels need to be the same and sold at the same price. She estimates that
the imported cost is $12, her company’s cost is $15 and the sales price is $24. She also believes
there is a 20 percent sales lift by having the shovels at the right place at the right time, a service
her company can offer because of the additional time and their flexibility. Here is the deal she proposes:
Instead of purchasing all 5,000 shovels offshore, purchase 80 percent (4,000) offshore and 2,000
from the NEO company, deferring distribution to the time of need. The result is a better in-stock position as products are distributed just before the time of need (a
weather forecast) and a 10 percent increase in gross margin dollars. Other intangible benefits
include happier customers and an increase in associated sales such as ice-melt. There is a way to leverage time and supply chain flexibility to bring manufacturing opportunities back to the U.S. Since this was a very simple example many costs were not included, making the actual opportunity potentially much larger.
By taking the time to measure lost sales and allowing for additional planning and reaction time, it IS possible for medium and small manufacturers to compete effectively with the offshore behemoths.