Theory of Constraints Archives - 6sigma

Theory of Constraints Addresses Weakest Link

OpEx Learning Team — Fri, 28 Feb 2025 06:16:02 +0000

The Theory of Constraints (TOC) adopts the common idiom that “a chain is no stronger than its weakest link and refers to the understanding that processes are crucially vulnerable because the weakest person or part of the process can damage or break even the strongest of organizational processes. TOC principles view organizations as being limited in achieving its goals by a very small number of constraints. There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization around it. The definition of a constraint is anything that prevents the system from achieving its goal. There are many ways that constraints can show up, but a core principle within TOC is that there are not tens or hundreds of constraints, but at most, only a few in any given process. These constraints can be either internal or external.

The TOC theory seeks to provide precise and sustained focus on improving the current constraint until it no longer limits throughput, at which point the focus moves to the next constraint. The underlying power of Theory of Constraints flows from its ability to generate a tremendously strong focus towards a single goal and to removing the constraint to achieving more of that goal.

There are five steps for focusing the Theory of Constraints:

Identify the constraint
Decide how to exploit the constraint
Subordinate everything else to previous step
Elevate the constraint
Go back to the starting step, while avoiding inertia

Even though its origins connect with manufacturing, the Theory of Constraints can be an effective method for problem solving across all industries. It can be seen as a methodology used to focus on problems currently being experienced, the cause and effect of those problems, and the best course of action to remove them.

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Bottleneck Analysis Improves Flow

OpEx Learning Team — Fri, 28 Feb 2025 06:15:57 +0000

“I say an hour lost at a bottleneck is an hour out of the entire system. I say an hour saved at a non-bottleneck is worthless. Bottlenecks govern both throughput and inventory.”

Eliyahu M. Goldratt

There can be multiple causes of slowdowns and disruptions in workflow. One of the most serious causes can be bottlenecks. When efficiency is crucial to an workflow process, a bottleneck can significantly impact the bottom line and customer satisfaction of any organization. A bottleneck analysis offers an organization opportunities to improve efficiencies, customer satisfaction and ensure workflows at an even rate.

A bottleneck analysis is a detailed process where an organization gathers as much detailed information about the flow of a particular product or process. Specifically, data is gathered about the point(s) in the process where workflow is bottlenecking. This type of analysis can be done specifically to identify the cause of a bottleneck that is causing problems, or to learn about processes where a bottleneck is likely to occur in the future. The bottleneck analysis will provide important information about how things are done, and how they can be improved.

When performing the analysis, it is crucial to not only look at where the bottleneck is occurring, but the entire workflow process. This will give a better picture of what is really occurring at all stages of the process, along with what occurs just before and after the bottleneck. If a bottleneck early in the workflow process is eliminated, it may result in a new one forming further down the line. A properly performed analysis will not only help to find solutions to the existing bottleneck, but will also help to prevent new ones from forming.

Preventing bottlenecks would be ideal to avoid having to manage and resolve them in the future. There are ways to work around them when planning the production environment. Giving employees free rein over minor decision-making will allow them to make the decision they feel is most efficient. Establishment of standardized exchanged protocols can minimize the potential for future bottlenecks to occur through minimizing downtime.

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[VIDEO] Improving Flow With Bottleneck Analysis

OpEx Learning Team — Fri, 28 Feb 2025 06:15:57 +0000

One of the most serious causes of workflow process breakdowns is bottlenecks. When efficiency is crucial to an workflow process, a bottleneck can significantly impact the bottom line and customer satisfaction of any organization. A bottleneck analysis offers an organization opportunities to improve efficiencies, customer satisfaction and ensure workflows at an even rate.

Watch this educational video on Bottleneck Analysis!

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Shmula Goes Camping: Drum-Buffer-Rope and Theory of Constraints

admin — Fri, 28 Feb 2025 06:02:59 +0000

My family and I went camping with my brother-in-law and his family. We went to a place in Utah called Uinta National Forest — it was beautiful. We prepared well, got the tent and camping stuff ready, then headed to the camp site on Friday. When we arrived, we set-up camp, then we went on a hike.

That’s us above on a hike — that’s me with the blue shirt holding a baby; yeah, the Asian guy, that’s me. It was just absolutely beautiful up there. It was nice to be in nature.

During our hike, I couldn’t help but think of the Boy Scout chapter in Goldratt’s “The Goal”. You know, the chapter where Goldratt introduces the Drum-Buffer-Rope system.

Before explaining the Drum-Buffer-Rope (DBR) system, let me first explain some basic characteristics of systems, in general:

Every system has a bottleneck.
A bottleneck is a state of affairs where demand for service exceeds the capacity to serve.
The Throughput of a system is dependent on the Throughput of the Bottleneck.
Given (1), (2), & (3), for maximum output, a system ought to keep the bottleneck working at 100% capacity with little or no defects (scrap, waste (muda), time-traps).
Given (4), Non-bottleneck processes should be working at less than 100% capacity, so as to not over-burden the bottleneck with large batches of work-in-process (WIP).

The characteristics above are basic to any system — manufacturing, clinical, software, or otherwise. Put on your Systems-wide Hat and think about your experience thus far, regardless of industry: bottlenecks are everywhere. That’s not the problem, but managing it is. Hence, the Drum-Buffer-Rope System.

Managing the Constraint is mostly about managing the non-bottleneck systems and making them “aware” how fast they should work — when they should slow down, when they should stop, or when they should increase pace and by how much. The Drum-Buffer-Rope system allows for a systems-wide awareness.

The Drum

The Bottleneck or Constraint, acts as a Drum — it sets the rythm that the whole system should follow. In Lean Manufacturing, this is also called “Takt Time.”

The Buffer

There are situations when when upstream processes can’t produce as much as is needed by the Bottleneck; the result: the Constraint is starved and overall system output is compromised. So, we must have a buffer of inventory that is the size of the accounted-for variation is demand. This will help to level-out variation. A Buffer will assure that the Constraint never has to wait and, waiting is a form of waste.

Similarly, if upstream processes are producing more than the Constraint has the capacity to handle, then there’s going to be excess inventory sitting in front of the Constraint and, hence, a feast.

Put another way, the Buffer is the inventory and inventory is directly related to Lead Time (I explain this in 2 previous posts on Little’s Law here and here.

This phenomena is sometimes called the Feast-of-Famine Syndrome.

DBR is used to avoid either of these scenarios — the Feast or the Famine — by dictating the batch size and frequency of the inputs into the Buffer.

The Rope

The Rope is a method by which the Constraint can signal to the upstream processes (non-bottleneck processes) when to slow down, when to stop, or when to produce faster and the quantity. This is called “Pull Scheduling” in Lean Manufacturing terms. In software, this can be implemented as a data structure called a Stack, with “Push” and “Pop” as the methods for pulling from the Stack.

Applications of Drum Buffer Rope

When I was with Amazon.com, I led a project where I investigated a production line that was experiencing a Feast/Famine scenario. There was a lot of waste on this line and it impacted daily production in a serious way. As the team lead, I set out to observe, interview the operators, and collect data on this line. I quantified the cost to Amazon that was a result of the Feast/Famine scenario — costs in terms of actual dollars resulting from missed orders, upgraded orders, overtime of operators, product damage, and safety issues.

The distribution you see above is best approximated by the Poisson Distribution, which means that the Mean and the Standard Deviation are approximately the same. What does this mean? The picture above graphically shows the ~~Famine~~ Feast scenario — product in totes arrive at the constraint ALL at the same time.

Solution? I led a team of software and industrial engineers that re-engineered this line and we implemented a DBR solution, where the pack-rate at the Constraint would dictate what the upstream pick-rate should be. In other words, we made sure that the pick-rate would never be higher than the pack-rate. This solution worked and Amazon saved a lot of money and customers benefit.

Drum-Buffer-Rope is an intuitive solution to a seemingly complex problem. DBR is seen in many areas including Agile Development, Manufacturing, and Medicine (Emergency Room Visits). It’s an effective business tool to manage the constraints that every business faces.

Oh, by the way, camping was great!

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Managing Constraints and Bottlenecks Under Peak Volumes

admin — Fri, 28 Feb 2025 06:02:09 +0000

One of the key lessons in The Theory of Constraints is that the contraint or the bottleneck determines the throughput for the entire system. This means, then, that if we optimize and improve a non-bottleneck, then those efforts have zero impact on the overall throughput of the system. It is only when we improve and optimize the contraint that we will see improvement in the throughput of the entire system. Every system has a constraint — that is neither good nor bad — but just a fact of dynamic systems. The key is to identify and then manage. Once you’ve identified the constraints in your system, then the next step is to manage it.

I was able to obtain some empirical volume data for Burger King. The data below is taken from 1 Burger King restaurant. I imagine the numbers would be significantly different if we were to average the volume by geography, restaurant size, or by other factors. Now, consider the following process map for a typical Burger King:

Over the course of an average month, Burger King produces 34227 sandwiches. This means, then, that for an average hour, Burger King produces 198 sandwiches per hour during normal hours. But, on Friday and at 12:00PM, Burger King experiences higher-than-normal volume and so we add a “Peak Multiplier” of 18% and 17.9% to arrive at 256 sandwiches during Peak Hours. The “Peak Multiplier” is not completely arbitrary, but a quasi-educated guess at the volume increase during those hours. In both cases of Fridays and Lunch Hours, we add a ~20% multiplier.

Now, let’s take a look at the process map. We see the Assembly Step producing 200 sandwiches an hour. We consider the Assembly to be the constraint in the system. The upstream processes produces more than 200, but when we arrive at the Assembly, the capacity of that step is lower than its upstream processes. So, the maximum throughput of the entire system above is 200 sandwiches per hour.

Under normal hours, the constraint functions reasonably well. Since normal hour demand is 198 sandwiches per normal hour, the Assembly Step can produce at least at that amount — but, it’s cutting it close. Under peak volume, the constraint is not able to fulfill demand.

How To Manage A Constraint

Under normal hours, it appears that the Assembly Step can produce at expected demand. But, there are several things that could put burden on the constraint and cause it to producing less than capacity. Here are some of those items:

Rework: Having to Re-Assemble sandwiches adds undue burden on the system and exaggerates the effects of the constraint, leading to a potentially higher-than normal work-in-process, or build-up.
Set-up & Changeover: If all the parts aren’t immediately available in the Assembly step, then it could lead the operator to slow down which could lead to build-up and higher-than-normal work-in-process.

It’s easy enough to see that the Assembly Step needs some help. Here are several things Burger King — or any system with constraints — can do to better manage the natural constraints that are in every system:

Eliminate Defects at the Constraint: This means that all waste is eliminated or reduced at the constraint.
Have the Quality Steps in Front of Constraint: In support of the first bullet, make sure that the parts entering the Assembly step are free of defects.
Support the Constraint: Add labor to the constraint or more lines, if that is prudent.
Appropriately use Buffers: Systems with Constraints exhibit a feast/famine phenomena. To avoid having too much coming into the constraint or too little coming into the constraint, have a buffer of parts large enough that the constraint stays appropriately busy. Put another way, reduce the variation in front of the constraint as much as is possible. A Drum-Buffer-Rope system might be appropriate for some systems.
Evaluate the overall system: How much of the steps in the system are really value-add to the customer? What is the process-cycle effeciency of the process?

Conclusion

All systems have constraints. Identify what they are, quantify the effects, then manage it. The above Burger King example shows how this can easily be done. What are the constraints in your systems? What can you do to better manage those constraints?

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Thinking One Step Ahead with SMED

OpEx Learning Team — Mon, 21 Aug 2017 20:58:02 +0000

Thinking One Step Ahead with SMED

Proper optimization is not just about making the facility run well with the current parameters in mind, but also to allow it to run as efficiently as possible in the future, considering upcoming developments. You have to always be one step ahead of the current environment and make informed strategical decisions.

SMED stands for Single-Minute Exchange of Die, and it refers to a methodology for improving the processing rate of a manufacturing plant. It achieves that by streamlining the process of switching from one product to the next one in line, and ensuring that all of your machines keep running at optimal efficiency at all times. It can also be used in an office setting, such as switching from task to task.

From a lean perspective, we want to complete tasks one at a time. When we batch our work, it’s often a result of the time required to changeover from product to product, or task to task. SMED can help us reduce the changeover time, to make it more efficient to operate in smaller batches.

SMED is also referred to as changeover reduction.

Going in depth

There are many intricate details to SMED. It’s a more general term referring to the process of changing targets within your work. The name of the methodology also comes from the fact that Toyota, in the past, identified larger dies as the most problematic objects in their manufacturing chain. Dies in an office setting could be a software program that takes time to load.

Changeover times are often responsible for the biggest slowdowns in productivity, and that streamlining the process of switching work could have dramatic effects on the overall output of the business.

It’s also important to note that single-minute refers to the idea that those “exchanges” should occur in a single-digit minute (0-9 minutes), not necessarily in sixty seconds. Anything up to about ten minutes is okay in the eyes of SMED, although of course the specific time is going to vary from one company to another.

SMED and continuous improvement

SMED goes hand in hand with continuous improvement, as it can allow you to always seek to maximize the potential capacity of the organization. It’s a technique that can be applied regardless of the specific current situation, making it highly flexible and suitable for incremental upgrades. What’s more, SMED can ensure that an organization running with more advanced modern technology is always utilizing that technology to its full potential, looking for opportunities to improve its output.

What exactly should you do to implement SMED though? There are several main components to the methodology, and the exact way of using it is going to vary across the board. The general idea is to ensure that there is a clear separation of internal and external setup, so that the state of the machines or computer systems can be reset as quickly as possible.

Internal Setup – Time spent in changeover when the machine or system is idle
External Setup – Time spent in changeover when the machine is working on something else

For example, when you look at the time to changeover your work, how much could be done while you’re finishing up the last job or project? Could someone else be getting the next item ready to go? Getting these tasks started earlier is an example of moving from internal to external setup.

In addition, the creator of SMED states that it’s important to focus on standardizing the functionality of the company’s machines and systems, not the specific output they’re producing. In a manufacturing setting, clamps should be functional, or alternatively fasteners should be removed completely if that’s not possible. This reduces the actual time to complete the task.

Introducing some additional intermediate steps in the process can also have a positive effect on the overall performance. Sometimes the lack of buffer zones can be a major contributing factor to performance issues, and 5S is a great method to ensure that those problems don’t go unnoticed.

Last but not least, there is also a strong suggestion that the company should look into automating as much as possible from its current range of tasks. This is an obvious one in many industries, especially auto manufacturing where SMED is rooted. Priority should be placed on the internal setup tasks that slow down the overall changeover time.

Conclusion

SMED can be a great way to always have a good edge in your company. It’s a flexible technique that can be highly useful to a variety of different organizations, and it’s also aligned with the current trends in technology and the direction we’re moving towards for the future. There are some clearly valuable lessons to be learned from SMED, and every leader should make it a point to familiarize themselves with the principles behind it as early as they can in their career.

Learn more about SMED >>>

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Practical Applications of Queueing Theory: Apply Lean at the Constraint to Eliminate the Bottleneck

admin — Tue, 26 Aug 2014 17:11:38 +0000

This article is on the Practical Applications of Queueing Theory and how some of the assumptions of Queueing Theory can break down, necessitating the need for government intervention.

Queueing Theory is based on several assumptions. One of those assumptions is that when demand exceeds capacity, the result will be waiting lines. Often in situations where demand exceeds the capacity, we can either create more capacity and/or eliminate any waste at the point of constraint in the system. Let’s explore some basics on why, exactly, do we wait at all.

Why Do We Wait?

Consider the figure below:

In most operations, capacity is actually constant. A factory can only have so many machines; an airline can have so many flight attendants; a grocery store can have so many cash registers. Not only is it constant, but there’s also an upper limit to capacity – a ceiling. Now, let’s go back to the figure.

During the period A and C, capacity exceeds the arrival rate of customers.
So, any customer that arrives and is served between periods B and D, will increase the length of the line and the average waiting time.
Conclusion: The average utilization of this operation is less than 100% because the average arrival rate is lower than capacity, yet customers experience a waiting time greater than zero. Why? Because of the “lumpiness” of the arrival rate – natural variation in the system.

In some cases, adding more capacity has a low cost. For example, opening up cash registers at a supermarket has a low relative cost. On the other hand, adding more doctors to relieve the waiting time at an emergency room has a relatively high cost attached to it.

What about reducing or eliminating waste at the constraint? Often times, this also has a relatively low cost – if there is adequate training in lean methods, root cause analysis, and a decent understanding of systems thinking, most anyone can eliminate or reduce waste at a bottleneck in the system.

But, what if there is available capacity, but they are not marshaled or deployed by choice?

That’s exactly what is happening at supermarkets in Venezuela [1. http://panampost.com/belen-marty/2014/08/22/got-shortages-chavistas-sic-operation-queue-killer-on-cash-registers/].

Operation Queue Killer

The Venezuelan government has launched a new initiative they call “Operation Queue Killer”, or Eficiencia Mata Cola in Spanish. In an audit of 66 private supermarkets, the investigators claim that more than half had at least one defective cash register. While others had fully functioning cash registers, but management chose not to open them. Both of these root causes lead to longer lines and longer waiting time.

The investigation doesn’t call out specifically, but there’s an undertone in the article that points to unfair pricing that are the result of fabricated demand, evidenced by the long waiting lines. Operation Queue Killer has one goal, according to Mendez, the Superintendent of Fair Prices:

Protect the sustenance of the Venezuelan Family

Continuing, Mendez claims the following:

When we conducted a thorough examination of why people are waiting in line, the phenomenon that drew our attention the most was that inspected supermarkets had more than half of their cash registers closed. Some even had 81 percent of their registers closed, and people waiting in line for three hours.

It seems to me that if there is truly widescale collusion, and shopkeepers are fabricating scarcity in order to drive up prices, it probably makes sense that the government is stepping in. To a queueing theorist, however, this is very interesting because this is one of the rare cases where factory physics aren’t the only things we are dealing with – now it’s human intervention.

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Lunch Line Design Utilizing Constraints and Bottlenecks to Prevent Childhood Obesity

admin — Mon, 20 Feb 2012 11:42:21 +0000

We know from the Theory of Constraints that every system has a bottleneck via effective lunch line design. The goal, then, isn’t to eliminate the bottleneck, but learn how to manage the overall system by effectively managing the constraint in that system. This is true in most cases. But, there are cases where purposely creating a bottleneck can obtain the desired outcome. Thus is the case with preventing Childhood Obesity and the Lunchroom.

A research cooperative called Smarter Lunchrooms is in the business of helping students make smarter choices by subtly changing their behavior. They use ideas from behavioral economics and psychology to guide better choices. One really interesting case study involves the wise implementation of a bottleneck.

The experiment looked at guiding the choice of regular skim milk versus chocolate milk and soda. So, this group partnered with a school to change the layout of the lunchroom and placed the chocolate milk and soda in an area where it was difficult to get to and only very few children could be there at any one time. At the same time, the school then placed the regular skim milk in an area where it was easily accessible.

Their findings: chocolate milk and soda sales went down and the sales of regular skim milk went up.

Here is an example where the implementation of a bottleneck led to better outcomes. And, the subtlety of the design likely went unnoticed by the children, yet they made better choices without even knowing they were making better choices.

The upshot?

Initiatives and approaches like this are wise, low cost, but effective ways at addressing childhood obesity.

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The Theory of Constraints Fundamentals

admin — Thu, 17 Jun 2010 11:24:12 +0000

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This article is part of a series on Lean and the Theory of Constraints. Here is the 3 part series:

In a previous post on Lean and Theory of Constraints, I argued that the decision is not an either/or, but rather “and”. In other words, there’s room for both and each can be complementary to each other.

In this post, I’ll do my best to describe the fundamentals of The Theory of Constraints. Then, in a next post, I’ll attempt to describe the Fundamentals of Lean Management (Lean Thinking, Lean Enterprise, Lean Manufacturing).

The Theory of Constraints Fundamentals

The Theory of Constraints was explained in the bestseller “The Goal“[1. Eliyahu Goldratt, “The Goal”, Chapter Summaries:

Chapter One: The first chapter gets the reader acquainted with Mr. Alex Rogo and his apparent problems with his production plant. This is shown through a confrontation between Mr. Rogo and his boss Mr. Peach, the Division Vice President. The dispute is over an overdue order #41427. Through their conversation it’s learned that Mr. Peach will not settle for anything less than the order being shipped today, and since the plant is neither productive nor profitable, Alex has three months to show an improvement or the plant will be shut down!

Chapter Two: This chapter gives insight to Alex’s home life. Since moving back to his hometown six months ago, it seems adjustment isn’t going well for his family. It’s great for Alex, but it’s a big change from the city life that his wife is used to. You also experience Mr. Rogo’s background through his reflections back on his travels to eventually find himself back where he started. “He’s now 38 years old and a crummy plant manager”. By the way, the order #41427 does get shipped, but not very efficiently. All hands in the plant are working on one order with forbidden overtime to boot.

Chapter Three: Mr. Peach calls a meeting at headquarters for all plant managers and his staff. At the meeting everybody finds out how bad things are and are given goals to achieve for the next quarter. Through the grapevine Mr. Rogo finds out perhaps why Mr. Peach has been acting so erratic lately, the Division has one year to improve or it’s going to be sold, along with Mr. Peach.

Chapter Four: While at this meeting, Alex thinks back on a recent business trip where he ran into an old physics professor, Jonah, at the airport. Jonah puzzles Alex with how well he knows how Alex’s plant is doing. Jonah has no knowledge of where Alex is employed. Johan predicts the problems of high inventories and not meeting shipping dates. He also states that there is only one goal for all companies, and anything that brings you closer to achieving it is productive and all other things are not productive.

Chapter Five: Alex decides to leave the meeting at the break. He has no particular place he would like to go; he just knows this meeting isn’t for him, not today. He needs to understand what the “goal” is. After a pizza and a six pack of beer it hits him, money. The “goal” is to make money and anything that brings us closer to it is productive and anything that doesn’t isn’t.

Chapter Six: Mr. Rogo sits down with one of his accountants and together they define what is needed in terms of achieving the goal. Net profit needs to increase along with simultaneously increasing return on investment and cash flow. Now all that is needed is to put his specific operations in those terms.

Chapter Seven: Alex makes the decision to stay with the company for the last three months and try to make a change. Then he decides he needs to find Jonah.

Chapter Eight: Alex finally speaks to Jonah. He is given three terms that will help him run his plant, throughput, inventory, and operational expense. Jonah states that everything in the plant can be classified under these three terms. “Throughput is the rate at which the system generates money through sales.” “Inventory is all the money that the system has invested in purchasing things which it intends to sell.” “Operational expense is all the money the system spends in order to turn inventory into throughput.” Alex needs more explanation.

Chapter Nine: Alex fresh off his talk with Jonah gets word that the head of the company wants to come down for a photo opportunity with one of Alex’s robots. This gets Alex thinking of the efficiency of these robots. With the help of the accountant, inventory control woman, and the production manager, Alex discovers the robots increased costs, operational expenses, and therefore were less productive. Implementing the robots increased costs by not reducing others, like direct labor. The labor was shifted to other parts of the plant.

Chapter Ten: After explaining everything, Alex and his staff (Bob from production, Lou from accounting and Stacey from inventory control) hammered out the meaning of throughput, inventory and operational expense until satisfied. Lou, states the relationships as follows. “Throughput is money coming in. Inventory is the money currently inside the system. And operational expense is the money we have to pay out to make throughput happen.” Bob is skeptical that everything can be accounted for with three measurements. Lou explains that tooling, machines, the building, the whole plant are all inventory. The whole plant is an investment that can be sold. Stacey says, “So investment is the same thing as inventory.” Then they decide that something drastic is needed to be done with the machines. But how can they do that without lowering efficiencies? Another call to Jonah is placed and Alex is off to New York that night.

Chapter Eleven: The meeting with Jonah is brief. Alex tells Jonah of the problems at the plant and the three months in which to fix them. Jonah says they can be fixed in that time and then they go over the problems the plant has. First, Jonah tells Alex to forget about the robots. He also tells Alex that “A plant in which everyone is working all the time is very inefficient.” Jonah suggest that Alex question how he is managing the capacity in the plant and consider the concept of a balanced plant. According to Jonah, this “is a plant where the capacity of each and every resource is balanced exactly with demand from the market.” Alex thinks a balanced plant is a good idea. Jonah says no, “the closer you come to a balanced plant, the closer you are to bankruptcy.” Then Jonah leaves Alex with another riddle, what does the combination of “dependent events” and “statistical fluctuations” have to do with your plant? Both of those seem harmless and should work themselves out down the production line.

Chapter Twelve: This short chapter tries to capture the essence of the problems the job is causing at home with the extra workload. The marriage is very strained because of the devotion Alex needs to give to the plant.

Chapter Thirteen: Stuck for the weekend as troop master, Alex discovers the importance of “dependent events” in relation to “statistical fluctuations”. Through the analogy between a single file hike through the wilderness and a manufacturing plant, Alex sees that there are normally limits to making up the downside of the fluctuations with the following “dependent events”. Even if there were no limits, the last event must make up for all the others for all of them to average out.

Chapter Fourteen: Finally, through the dice game or match bowl experiment, it becomes clear that with a balanced plant and because of “statistical fluctuations” and “dependent events” throughput goes down and inventory along with operating expenses goes up. A balanced plant is not the answer.

Chapter Fifteen: Fully understanding the “dependent events”, Alex puts the slowest kid in the front of the hike and he relieves him of extra weight he has been carrying in his backpack. This balances the fluctuations and increases the kid’s productivity, which increased the throughput of the team.

Chapter Sixteen: Well, after the camping trip the boys arrive home to find the mother has disappeared. All the stress of his job was too much for her so she left. Now the kids and the job are all Alex’s responsibility. This was supposed to be a weekend for Alex and his wife, but when the hike came up it seemed to be the last straw for her.

Chapter Seventeen: Alex tries to portray his new revelation to his team at the plant. Nobody seems interested. But the walk in the woods becomes apparent when it is put to the test for an overdue order in the plant. Now even the production supervisor agrees. Now what?

Chapter Eighteen: In this chapter Jonah introduces Alex to the concept of bottlenecks and non-bottlenecks. Jonah defines these terms as follows. “A bottleneck is any resource whose capacity is equal to or less than the demand placed upon it. “A non-bottleneck is any resource whose capacity is greater than the demand placed on it.” Jonah explains that Alex should not try to balance capacity with demand, but instead balance the flow of product through the plant. Later, Alex and his team recognize the bottlenecks, the areas where capacity doesn’t equal demand, like the slow kid Herbie on the hike. With this discovery goes the ideas related to reorganizing the plant like Alex did with the hike. Production is a process and it cannot be moved around so easily. Many processes rely on the previous one to be able to complete the next. Alex would need more machines, which takes more capital, and division is not going to go for that.

Chapter Nineteen: Well, Jonah makes a visit to the plant. Jonah tells Alex that a plant without bottlenecks would have enormous excess capacity. Every plant should have bottlenecks. Alex is confused. What is needed is to increase the capacity of the plant? The answer is more capacity at the bottlenecks. More machines to do the bottleneck operations might help, but how about making them run more effectively. Jonah tells them that they have hidden capacity because some of their thinking is incorrect. Some ways to increase capacity at the bottlenecks are not to have any down time within the bottlenecks, make sure they are only working on quality products so not to waste time, and relieve the workload by farming some work out to vendors. Jonah wants to know how much it cost when the bottlenecks (X and heat treat) machines are down. Lou says $32 per hour for the X machine and $21 per hour for heat treat. How much when the whole plant is down? Around $1.6 million. How many hours are available per month? About 585. After a calculation, Jonah explains that when the bottlenecks are down for an hour, the true cost is around $2,735, the cost of the entire system. Every minute of downtime at a bottleneck translates into thousands of dollars of loss throughput, because without the parts from the bottleneck, you can’t sell the product. Therefore, you cannot generate throughput.

Chapter Twenty: Alex organizes the bottlenecks to work on only overdue orders from the most overdue to the least. He then finds his wife. She is at her parent’s house. Through their conversation it is learned that she still needs to be away from everybody, even the kids.

Chapter Twenty One: The crew works out some of the details for keeping the bottlenecks constantly busy. In the process they find that they need another system to inform the workers what materials have priority at non-bottlenecks. Red and green tags are the answer. Red for bottleneck parts to be worked on first as to not hold up the bottleneck machine, and green for the non-bottleneck parts. That concludes another week. The true test will be next week.

Chapter Twenty Two: Great, twelve orders were shipped. Alex is pleased, but he definitely needs more. He puts his production manager on it. His production manager rounds up some old machines to complement what one of the bottlenecks does. Things are looking up.

Chapter Twenty Three: They are becoming more and more efficient, but lag time arouse with the two bottlenecks because of workers being loaned out to other areas and not being at the bottlenecks when needed to process another order. It seems there was nothing to do while waiting for the bottleneck machine to finish the batch. Therefore, in keeping with the notion that everybody needs to stay busy, workers were at other areas between batches. Alex decides to dedicate a foreman at each location all the time. Then one of those dedicated foreman, the night foreman, discovers a way to process more parts by mixing and matching orders by priority, increasing efficiency by ten percent. Finally, one process being sent through a bottleneck could be accomplished through another older way and therefore free up time on the bottleneck.

Chapter Twenty Four: Now that the new priority system is in place for all parts going through the bottlenecks, inventory is decreasing. That’s a good thing right? But lower inventory revealed more bottlenecks. This intrigues Jonah so he’s coming to take a look.

Chapter Twenty Five: “There aren’t any new bottlenecks”, says Jonah. What actually has happened is a result of some old thinking. Working non-bottlenecks to maximum capacity on bottleneck parts has caused the problem. All parts are stacked up in front of the bottlenecks and others are awaiting non-bottleneck parts for final assembly. There needs to be balance. The red and green tags need to be modified. It seems as if the bottlenecks will again control the flow, by only sending them exactly what they need and when they need it.

Chapter Twenty Six: Ralf, the computer wiz, says he can come up with a schedule for bottleneck parts and when they should be released. This will alleviate any excess inventory in front of the bottlenecks, but what about the non-bottlenecks? Jonah says with the same data out of the bottlenecks to final assembly, you should be able to predict non-bottleneck parts as well. This will make some time, but there are enough parts in front of the bottlenecks to stay busy for a month.

Chapter Twenty Seven: There is another corporate meeting. Mr. Peach doesn’t praise Alex like Alex thinks he should. Alex decides to talk with him in private. Mr. Peach agrees to keep the plant open if Alex gives him a fifteen percent improvement next month. That will be hard because that relies heavily on demand from the marketplace.

Chapter Twenty Eight: Fifteen Percent!! Fifteen Percent!! Just then Jonah called to let Alex know that he will not be available to speak with in the next few weeks. Alex informs him of the new problem of more inventories and less throughput. Jonah suggests reducing batch sizes by half. Of course, this will take some doing with vendors, but if it can be done, nearly all costs are cut in half. Also, they get quicker response times and less lead times for orders. Sounds good.

Chapter Twenty Nine: Alex is propositioned with a test. They can greatly increase sales, current and future, if they can ship a thousand products in two weeks. Impossible without committing the plant to nothing but the new order? Wrong! How about smaller batch sizes. Cut them in half again. Then promise to ship 250 each week for four weeks starting in two weeks. The customer loved it.

Chapter Thirty: Seventeen percent!! That’s great, but it’s not derived from the old cost accounting model. The auditors sent down to the plant from Division find just 12.8% improvement. Most of it accounts from the new order. Which by the way, the owner of the company that placed the order came down personally to shake everybody’s hand in the plant and to give a contract to them for not a thousand parts but ten thousand. Anyway, tomorrow is the day of reckoning at division.

Chapter Thirty One: Well the meeting at Division started out rough. Alex thought he would be meeting with Mr. Peach and other top executives. Instead, he met with their underlings. He decides to try and convince them it doesn’t work. Just before leaving he decides to see Mr. Peach. It’s a good thing he did, because he just got promoted to Mr. Peach’s position. Now Alex has to manage three plants as the whole division. He calls Jonah desperately and asks for help. Jonah declines until he has specific questions.

Chapter Thirty Two: Alex has a nice dinner with his wife. Through the veal parmesan and cheese cake it is decided that Alex should ask Jonah how he can get other people to understand these techniques that his team has discovered without being condescending.

Chapter Thirty Three: Now is the time to assemble Alex’s team for Division. Surprisingly the accountant with two years to retirement is on board, but the production manager isn’t. He wants to be plant manager to continue their efforts. Everything is totally into place at the plant but more is needed for division.

Chapter Thirty Four: Alex is firmly engrossed with the problems of taking over the division. With advice from his wife he decides to enlist the help of his team at the plant. Every afternoon they will meet to solve the problem. After the first day it is obvious , they will need them all.

Chapter Thirty Five: The second day they are led in a discussion about the periodic table of elements, and how the scientists actually got a table of any sort. Maybe that is how they will solve the massive problems of division, by understanding how the scientists started with nothing and achieved order. A way to define them by their intensive order is needed.

Chapter Thirty Six: The team finally comes up with the process: Step one identify the system’s bottlenecks; Step two- decide how to exploit those bottlenecks; Step three- subordinate everything else to step two decisions; Step four- evaluate the systems bottlenecks; Step five- if, in a previous step, a bottleneck has been broken, go to step one. It seems so simple, just different.

Chapter Thirty Seven: The team decides to revise the steps: Step one identify the systems constraints; Step two decide how to exploit the systems constraints; Step three subordinate everything else to step two decisions; Step four evaluate the systems constraints; Step five- warning!!! If in the previous steps a constraint has been broken, go back to step one, but don’t allow inertia to cause a system constraint. It also has been discovered that they have been using the bottlenecks to produce fictitious orders in an effort to keep the bottlenecks busy. That will free up twenty percent capacity, which translates in to market share.

Chapter Thirty Eight: Talking with the head of sales. Alex finds out that there is a market order to fill the capacity. It’s in Europe, so selling for less there will not affect domestic clients. If it can be done, will open a whole new market. Then Alex ponders Jonah’s question, to determine what management techniques should be utilized. Alex determines how a physicist approaches a problem. Maybe this will lead to an answer.

Chapter Thirty Nine: Alex experiences a problem at the plant. It seems all the new orders have created new bottlenecks. After analyzing the problem, they agreed to increase inventory in front of the bottlenecks an tell sales to not promise new order deliveries for four weeks, twice as much as before. This will hurt the new relationship between sales and production, but it is needed. Production is an ongoing process of improvement, and when new problems arise they need to be dealt with accordingly.

Chapter Forty: Finally, struggling with the answer to Jonah’s question, Alex comes up with some questions on his own: What to change? What to change to? How to cause the change? Answering these questions are the keys to management, and the skills needed to answer them are the keys to a good manager and ultimately the answer to Jonah’s question.
]. In that book, Eliyahu Goldratt explains that the mindset in The Theory of Constraints (TOC) is that organizations are systems, which consists of resources, processes, and people. Within that context, a Constraint is defined as:

A constraint is anything that limits the system from achieving higher performance relative to its purpose.

In other words, most for-profit organizations exist to make money. A constraint (or bottleneck) within that context is anything that limits the organization from making more money. Put another way,

The weakest link in a chain determines the strength of the entire chain.

The Theory of Constraints is governed by 5 guiding steps:

Identify the system constraint.
Decide how to exploit the system’s constraint.
Subordinate everything else to the above decisions.
Elevate the system’s constraint.
Prevent Inertia – when the system’s constraint is broken, iterate back to step one and start over.

There are other elements important to our understanding of The Theory of Constraints:

What is the System?
What is the goal of the System?
How do we measure the purpose of the System?

From this expanded investigation, the idea of Throughput is explained, which is:

Throughput (T) = the rate at which the organization generates money through sales

and Operating Expense:

Operating Expense (OE) = all of the money the organization spends in order to turn inventory into throughput

Given the above, Profit is calculated thus:

Profit = T – OE

Now, let’s go back to the 5 Guiding steps:

Identify the System’s Constraint

In general, for most organizations, the system constraint will be located in either:

The Market: not enough sales
The Suppliers: not enough material
The Company: internal processes, people – not enough resources, capacity, or skill set.

Decide How to Exploit the System’s Constraint

The rate of throughput is determined by the system’s constraint. This fundamental fact can help us decide how to treat the constraint.

In general, as described in Step One, the constraint will be in the Market, Suppliers, or Internal.

If Internal: eliminate waste at the constraint; place inspection steps upstream from the constraint; and other methods to free-up the constraint from non-value activities.
If Suppliers: reduce scrap; eliminate or reduce work-in-process (WIP); work with suppliers on both information flow and material flow improvements.
If Market: improve quality; improve service; add features that build loyalty and delight.

For example, this post shows what a constraint looks like in a fast food operation.

Subordinate Everything to the Above Decisions

In this step, behavior change is the goal; this means organizational restructuring, behavior modeling from the key leadership, as well as broad communication on what, why, and how that describe the changes happening.

This step also introduces the idea of a Drum-Buffer-Rope, which is a method that supports Pull, instead of Push. More on this later.

In Conclusion

I’ve attempted to describe the fundamentals of the Theory of Constraints. This is my partially-best attempt, so if notice that I’ve missed some important aspects, please don’t hesitate to let me know in the comment section.

In the next post, I’ll attempt to describe the fundamentals of Lean Thinking (Lean Management). In the section after that, I’ll attempt to compare and contrast Lean with the Theory of Constraints and then present how to reconcile The Theory of Constraints and Lean Thinking and show how they can work harmoniously with each other.

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Lean and Theory of Constraints either/or?

admin — Fri, 28 May 2010 10:03:21 +0000

This article is part of a series on Lean and the Theory of Constraints. Here is the 3 part series:

I’m not a fan of dichotomous thinking – either / or.

For one, it’s formally a psychological disorder and, two, it’s neither practical nor true. As with most things in life, there is usually at least a third choice – in fact, there are many more choices, realistically.

So, when voices – loud voices – claim their business philosophy is better than such and such, I have to step back and evaluate: Isn’t there an alternative? Instead of “or”, isn’t there an “and”?

This is true for Lean Thinking, Six Sigma, Systems Thinking, and Theory of Constraints. Arguing which is better is a waste of time. The pragmatic approach is that there is good in all of them. Take what works, apply it appropriately for your business, and if the results are good and the approach was humane and good, then roll with it.

In this series on Lean and The Theory of Constraints, I’ll attempt at reconciling the two business philosophies and show how they can work together and help improve the organization.

History

The Theory of Constraints first emerged from Dr. Eliyahu Goldratt’s popular book “The Goal“. That book is now required reading in most business courses because it reads easily: it’s a business novel, but embedded in the novel is a strong message about constraints or bottlenecks and their impact on a business.

Lean Thinking was popularized by Womack and Jones in their landmark book “The Machine that Changed the World.” The term “Lean” was coined by a Bob Hartman, an MIT researcher who used that word to describe how Toyota did “everything with half of everything” – half the people, half the budget, half the space, with fewer quality problems and delivered in half the time than its competitors.

In the next section, I’ll highlight the fundamentals of Lean Thinking and The Theory of Constraints.

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