How to identify the constraint of a system? Part 2

When trying to find the system’s constraint, why not simply asking the middle management? At least when Theory of Constraint was young, our world spinning slower and processes simpler, the foremen usually had a common sense understanding of their bottleneck. They knew what machine to look after, and what part of their process to give more attention.

If you haven’t read part 1, catch up: How to identify the constraint of a system? Part 1

Even so they may not have discovered all 9 rules about managing a bottleneck by themselves, they intuitively applied some of them.

Nowadays the picture is blurred with complexity and frequent changes. Nevertheless, asking middle management can still give precious hints about bottlenecks. Ask what the more troublesome spot of the process is and from where / whom the downstream process steps are waiting for something. Chances are that many managers will point to the same direction.

This works for project management or (software) development as well. In those cases I would also ask who the superstar (programmer) is, the one everyone wants on his/her project and in every meeting. Chances are that that person turned into a constraint without even noticing it.

Now if the tip can be useful, refrain from rushing to conclusions from these answers and check for yourself. Many managers may tell you the same just because they all heard the same complaints in a meeting. A meeting where all managers meet…

Go to the gemba, look for Work In Progress

Let’s start the shop floor investigation searching for the bottleneck like it is described in the early text books.

Go to the gemba, follow the flow (which is easier and somewhat more natural than walking upstreams, but up to you to choose the preferred way) visually assess the work in progress (WIP) and inventories in front of the machines or work cells.

Usually the highest piles of Inventories or work in progress are sitting in front of the bottleneck and the following downstream process steps are starved from material or parts.

Yet if it would be that easy it would be no fun. The above works well in simple processes which are neat and tidy. Most often the inventories are scattered wherever it is possible to store something, FIFO (First In First Out) rules are violated and downstream processes, incentivized on productivity, work on whatever they can work on for the sake of good looking KPIs. Finding the bottleneck in such a chaos needs more than a visual check.

It is also possible that excess inventory and work in progress may be temporarily stored in remote warehouses and not in full sight, thus not visible.

Another pitfall is confusing work waves, periodically releasing parts or information, and real bottlenecks. An example could be a slow process which is not a true bottleneck but needs more than the regular shifts to catch up with its workload.

Imagine a slow machine (sM) amidst a process. The process upstream (P1) works 8 hours with best possible productivity and WIP piles up in front of sM. The downstream process (P2) works at best possible productivity and has some WIP in front of it.

At the end of the shift P1 and P2 are shut down. They both fulfilled their daily scheduled work. sM goes on for a second shift, processing the WIP in front of it.

By the end of the second shift, no more WIP (or very few) in front of sM and what was waiting in front of sM is now waiting after it, in front of P2. This is the picture the next early morning:

An observer, depending when he/she looked at the process, could have come to wrong conclusions about a bottleneck. Early morning it looks like the first machine of P2 is holding back the flow. In mid afternoon it is sM that is the culprit, when in reality there is no true bottleneck. sM has enough capacity provided it can work more than one shift.

Some would mention wandering bottlenecks, jumping from one place to another. This is something I will elaborate on in a separate post. Or series…

We are not done now with our bottleneck safari. To learn more, proceed to part 3.


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How to identify the constraint of a system? Part 1

A very common question once people get familiar with Theory of Constraints and the notion of bottlenecks and constraints is how to find them in a process. Identifying the constraint is key as the constraint, by its nature, controls the performance of the whole system.

The trouble with examples given in textbooks or case studies is that they are rather simple compared to finding the constraint in real life. This difficulty grew over time as processes got more complex, adding new layers of rules, standards and regulations. This complexity grew to an extend that many constraints remain elusive to people searching them, leading many people to be wrong when identifying “their” constraint.

Facing this kind of difficulties, readers asked me if a formal procedure to identify the constraint exists. I am not aware of such a procedure and from my experience the search for the constraint is much more like a detective’s job requiring investigation skills than applying a recipe. Some common patterns and similarities may exist, but every organization has some specificities that make the search for the constraint a special case. Therefore intuition and experience are definitely of great help.

In this series of post, I propose to review such investigations, that may help readers to transpose in their own situation, and eventually try to wrap up guidelines to identify constraints.

The usual suspects

First let’s review common bottleneck resources, keeping in mind that being a bottleneck is not synonymous of being a constraint and, as a general rule, a constraint is (and should be) a resource too long or too expensive to get more of it, or put differently turn it in a non-constraint.

A constraint was long said to be a very expensive piece of machinery or equipment which is too expensive as an investment to afford another one for additional capacity or which is not currently available.

Big stamping machines or presses, painting booth, heat treatment, surface treatment or sophisticated machine tools made good candidates for being bottlenecks and ultimately constraints.

Bad news is that things evolved, as we will see, and even if those bulky expensive or scarce equipment still make good candidates for the constraint status, they are not always the constraint.

For instance, I worked in a engineer-to-order company designing and manufacturing heavy mechanical equipment. The heat treatment was said to be the constraint and was managed by-the-book as a constraint.

After a short diagnostic, it turned out that heat treatment was not the constraint. It wasn’t because the true constraint was elsewhere in the process and those heat treatment operations could be subcontracted nearby at short notice and reasonable price. The subcontracting gave sprint capacity and provided relief whenever necessary. So heat treatment, even with long cycle times, was nothing really scarce nor excessively expensive.

Why was the heat treatment mistakenly thought to be the constraint? Because literature on the subject point this kind of process as usually being a bottleneck (remember: not enough capacity with regard to average demand placed on it). If indeed the workload often exceeded the capacity, the heat treatment was not the constraint. Failing to understand the difference between bottleneck and constraint led to a wrong conclusion.

Where was the real constraint? In engineering department where equipment are designed: people with specific skills that are long to learn.

More usual suspects

Very slow processes are usually also good candidates as bottlenecks: drying, curing, maturation, chemical or biological reactions, etc.

People with specific skills (as we have seen), knowledge, abilities, expertise, etc. that cannot easily be hired can also become constraints. So are some raw materials that are rare or dependent on harvest, climate, embargo, shortage, etc.

In some areas it is difficult to find some qualified workforce like welders, forklift drivers or specialists in some trade, which makes them constraints even so their profession is not so scarce at a larger scale.

When the constraint is not obvious nor easy to find, its identification becomes a matter of investigation. Investigation will start in part 2.


About the author, Chris HOHMANN

About the author, Chris HOHMANN

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You are entering unclear territory

This post is inspired by some pictures* in Mike Rother’s book “Toyota Kata”, very relevant in our actual changing times and complex situations. I really like the figures that remind that the journey towards a goal requires entering unclear territory at some point.

Unclear territory

Adapted from “Toyota Kata”, Mike Rother

Experience from the military tells that no plan, regardless how carefully it was planned, will survive contact with the enemy.

No plan survives contact with the enemy.
Helmuth von Moltke
https://en.wikiquote.org/wiki/Helmuth_von_Moltke_the_Elder

What this means is that unknown facts, unexpected events and dynamic complex interrelated relationships will interfere with the plan based on partial knowledge, biased perception and simplified hypotheses.

Plans are important because they allow to explore hypotheses and be prepared accordingly but most plans are useless as reality often unfolds differently as expected.

This is why, when starting a journey toward a significant change or a Lean transformation for example, the plan will probably last only for the few first steps, but barely further. Once the journey started, unexpected circumstances will reveal themselves and require adjustment.

This is similar to exploring a dark room with a flashlight**. Only a part of the room is visible and every move is done accordingly to visibility and noticed obstacles. As one moves forward the line of sight extends and the vision clears further one step at a time. New obstacles appear, requiring new adjustment, and so on. The path across the dark room is probably not straight, but must get past several obstacles.

The same happens while hiking. The goal is set, the map shows the terrain and the compass helps for the bearing. Yet the map may show the canyon, the river and the forest, but none of the boulders, the fallen trees across the path neither the recently flooded areas. Those obstacles will appear once the hikers come close. In this case too, the hikers have to adjust to circumstances and find alternate routes to reach their goal. The one they had in mind while planning the hike is no more relevant.

Leaders must be able to lead through unclear territories

Unclear territories of all sorts are more and more common. Even what we believed familiar ground can be disrupted overnight. Everything is going “VUCA”, meaning being increasingly Volatile, Uncertain, Complex and Ambiguous. More decisions must be taken, more frequently and often with incomplete data and only partial understanding of the situation.

Among all decisions, some – and hopefully few – will show unadapted, requiring new adjustments. Wandering in unclear territories is a new fate. Being able to make quick and good decisions in unclear territories is a necessary aptitude for aspiring leaders.

What are good decisions? Those enabling the organization to achieve its goal despite the obstacles and unexpected difficulties, those solving the problems to clear the way towards the goal or choosing alternate routes to get closer to the goal.
Therefore, having a clear Goal onto which aligning actions, projects and initiatives when going through unclear territory is mandatory.

Followers too must understand “unclear territories”

Unclear territory is not a concept for leaders only, the followers must understand it too. What does it mean? It means that once entering unclear territories:

  • leaders (managers, people in charge…) may get surprised by unexpected events and this does not make them bad leaders
  • leaders, managers, etc. don’t have all the answers to all difficulties and problems that arise along the journey
  • plans and projects sometimes have to be reoriented, which may look like poor management or a fantasy but isn’t
  • some invested efforts and actions must be abandoned due to new circumstances, it’s disappointing, but that’s life

One may wonder how to distinguish poor leadership from the necessities to adapt to new circumstances? I would suggest to prevent the question from arising by establishing a clear communication upfront, giving frequent and transparent updates and have everyone exploring the unclear territory by teamwork.


*Mike Rother “Toyota Kata: Managing People For Improvement, Adaptiveness, and Superior Results”, McGraw-Hill Professional, 2010. Pictures mentioned are page 8; 120; 124; 133; 163

**Flashlight metaphor, page 133


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What is autonomous maintenance (TPM)?

Autonomous maintenance is one of the 8 Total Productive Maintenance (TPM) pillars, it aims to give both competence and responsibility for routine maintenance, such as cleaning, lubricating, and inspection to operators.

The aims and targeted benefits of autonomous maintenance

The ultimate goal of Total Productive Maintenance is to enhance machines’ effectiveness. TPM is a participative approach, involving all stakeholders and taking into account all aspects of maintenance. In order to achieve this goal, TPM is split in 8 pillars or topics. Autonomous maintenance is one of the 8 and is about simple mundane tasks, but having their importance nevertheless. The expected outcomes are:

  • Operators’ greater “ownership” of their equipment
  • Increased operators’ knowledge of their equipment
  • Ensuring equipment is well-cleaned and lubricated
  • Identification of emergent issues before they become serious failures
  • Freeing maintenance personnel for higher-level tasks

Operators’ ownership

Operator’s ownership of their equipment is meant to close the divide between Production and Maintenance in cases where the first claim “my job is to produce” and the second “my job is to repair”. This is mainly the case when production staff is incentivized on production output and maintenance is jealous about keeping its technical skills and prerogatives.

What happens then is that production operators do not usually care much about the equipment and machines they use and are prone to trespass speed limits, for example.

As they are not supposed to do anything about the machine breaking down, they soon find out that breakdowns are opportunities for an extra break, hence an extra smoke, one more coffee and so on.

As a result, machines stops last longer as they should: waiting for maintenance staff to come, discover the cause of the trouble, fix it, waiting for the operators to come back and resume production.

It can go the other way when production is strongly incentivized on units produced: any stoppage or breakdown jeopardizes the bonus and is immediately resented when maintenance doesn’t fix the problem fast enough.

What TPM is trying to do: give operators a sense of ownership of their equipment in order for them to take care, use it well, help maintenance technicians to find the causes of breakdowns by summarizing what happened before, and so on.

In order to achieve this, training must be delivered to both production and maintenance staff, focusing on the required cooperation for the sake of overall performance improvement. It will be a win-win cooperation: operators enriching their jobs with technical aspects and maintenance technicians being freed of low-qualification tasks for a better use of their real technical expertise. However, this must be done step by step.

Increasing operators’ knowledge of their equipment

Operator will use their equipment and machines correctly if they are trained not only for the use, but also a bit further into technical details. When operators have a basic understanding of how a machine works, they may be able to discover some causes of malfunction by themselves and give precious indication to maintenance team. With this focus, downtime can be reduced as maintenance does not have to go through a full investigation. If operators show interest and abilities, they may be trained further, to a point they can help maintenance with repairs, preventive maintenance tasks, adjustments, etc.

In my years as production manager with Yamaha, we brought teams of ladies to take care of the maintenance of automatic electronic components insertion machines. These ladies started as operators without any technical background, only feeding the machines. Step by step we trained them to take care of simple cleaning tasks, then adjustments, later exchanging more and more complicated mechanisms and finally be involved in major repairs.

Ensuring equipment is well-cleaned and lubricated

Before dreaming of repairing complex equipment, the journey starts with more mundane but important tasks: cleaning and lubrication.

But it’s more than that. Autonomous maintenance is about passing over  to operators the basic cleaning of the machines, lubricating and oiling, tightening of nuts and bolts, etc.

With these new tasks, operators will soon be able to take over daily inspection, diagnosis of potential problems and other actions that increase the productive life of machines or equipment. With appropriate prior training, of course.

Identification of emergent issues before they become serious failures

Cleaning and lubrication by operators is not a trick to reduce manpower costs by pushing tasks to lesser qualified people. On the contrary: TPM considers daily cleaning as an inspection and operators as subject matter experts. Indeed, operators using the machines and equipment daily are the best qualified detectors of early signs of problems. While cleaning they can detect: wear, unusual noises, vibrations, heat, smell, leakage, change of color, etc.

Using the machines frequently, they know best what is “as usual” and what is unusual. Someone hired only to clean and lubricate machines without using them would not be able to notice the forerunning signs of potential big trouble.

This daily inspection is key to reduce breakdowns by keeping the machine in good condition and by warning early – before breakdown – in order to remedy swiftly to unusual forerunning signs.

Freeing maintenance personnel for higher-level tasks

Putting skilled professionals in charge of challenges matching their expertise is certainly more attractive than asking them “to clean up other’s mess”, as maintenance staff frequently complain. Therefore the reluctance to train production operators for simple tasks and hand those over should not be a big deal for maintenance techs.

Production management should also see the opportunity to have better technical support for improvement and repairs, as skilled technicians are made more available. Of course, this comes at the expense of some daily minutes devoted to take care about machines instead of producing parts. In the long run, this should be a good deal, because less breakdowns, less scrap, fewer minor stops and faster changeovers thanks to technical improvements will pay back in productive capacity.

Finally, for production operators, the deal is to enrich their job with more technical content. For those immediately claiming acquisition of new skills deserve a pay raise, they should first consider that taking care of machines and equipment they are in charge is a basic expectation, not an extra requirement. Time will be given to do the daily maintenance routine. For operators it’s a shift of occupation content a few minutes a day.

Now this said, the question of a raise is to be considered in the context.

About the author, Chris HOHMANN

About the author, Chris HOHMANN

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