Category Archives: Management

On Variation and Some of its Sources


Virtually every component is made to be assembled with its counterpart(s) into sub-assemblies and final assemblies.

If individual pieces of a given component could be made identical to one another, then they would either all conform or all fail to conform to the component’s design requirements. If they conform, then we could pick a piece at random for use in a sub- or final-assembly. It would fit and function without fail, as intended.

But material varies, machine operation varies, the work method varies, workers vary, measurement varies, as does the environment. Such variation, especially in combination, makes it impossible to produce anything identical. Variation is a fundamental principle of nature. All things vary.

Variation affects the fit, the form and the function of a component. And, it is propagated along the assembly line such that the final product is at times a mixed bag of conforming and nonconforming widgets.

Material Consider 316 Stainless Steel. It is used to make medical devices. Manufacturers buy it from metal producers in sheet stock or bar stock.

If we measured the dimensional attributes of the received stock, e.g. its diameter or length, for several different purchase orders, we would see that they were not identical between orders. They vary. If we measured these attributes for pieces received in a single order, we would see that they were not identical between pieces of that order either. If we measured these attributes for a single piece at different points in its cross-section, we would see that they, too, were not identical. If we then zoomed in to investigate the crystalline structure of the stainless steel, we would see that the crystals were not identical in shape or size.

The elemental composition, in percent by weight, of 316 Stainless Steel is: 0.08% Carbon, 2.00% Manganese, 0.75% Silicon, 16.00-18.00% Chromium, 10.00-14.00% Nickel, 2.00-3.00% Molybdenum, 0.045% Phosphorous, 0.030% Sulfur, 0.10% Nitrogen, and the balance is Iron. We see that the amount of Chromium, Nickel, Molybdenum and Iron are specified as ranges i.e. they are expected to vary within them by design!

These are some of the ways a specific raw material used in the production of medical devices varies. Keep in mind that a medical device isn’t a single component but an assembly of several components likely made of different materials that will vary in just such ways as well. All this variation affects the processing (i.e. machining, cleaning, passivation, etc.) of the material during manufacturing, as well as the device performance in use.

Machine One piece of equipment used in the production of medical device components is the CNC (Computer Numerical Control) machine. Its condition, as with all production equipment, varies with use.

Take the quality of the lubricating fluid: it changes properties (e.g. its viscosity) with temperature thus affecting its effectiveness. The sharpness of the cutting tool deteriorates with use. A component made with a brand new cutting tool will not be identical to one made from a used cutting tool whose cutting edges have dulled. The cutting is also affected by both the feed-rate and the rotation-rate of the cutting tool. Neither of which remain perfectly constant at a particular setting.

What’s more, no two machines perform in identical ways even when they are the same make and model made by the same manufacturer. In use, they will almost never be in the same state as each other, with one being used more or less than the other, and consumables like cutting tools in different states of wear. Such variability will contribute to the variability between the individual pieces of the component.

Method Unless there is standardized work, we would all do the work in the best way we know how. Each worker will have a best way slightly different from another. Variation in best ways will find its way into the pieces made using them.

These days a production tool like a CNC machine offers customized operation. The user can specify the settings for a large number of operating parameters. Users write “code” or develop a “recipe” that specifies the settings for various operating parameters in order to make a particular component. If several such pieces of code or recipes exist, one different from another, and they are used to make a particular component, they will produce pieces of that component that vary from one to another.

When and how an adjustment is made to control parameters of a tool will affect the degree of variation between one piece and another. Consider the method where a worker makes adjustment(s) after each piece is made to account for its deviation from the target versus one where a worker makes an adjustment only when a process shift is detected. Dr. Deming and Dr. Wheeler have shown that tampering with a stable process, as the first worker does, will serve to increase the variation in the process.

All such variation in method will introduce variability into the manufactured pieces.

Man There are a great many ways in which humans vary physically from one another. Some workers are men, others are women. Some are short, others are tall. Some are young, others are older. Some have short fat fingers, others have long thin fingers. Some have great eyesight, others need vision correction. Some have great hearing, others need hearing aids. Some are right handed, others are left handed. Some are strong, others not so much. Some have great hand-eye coordination, others do not. We all come from diverse ethnic backgrounds.

Not all workers have identical knowledge. Some have multiple degrees, others are high school graduates. Some have long experience doing a job, others are fresh out of school. Some have strong knowledge in a particular subject, others do not. Some have deep experience in a single task, others have shallow experience. Some have broad experience, others have focused experience.

Last, but not least, we all bring varying mindsets to work. Some may be intrinsically motivated, others need to be motivated externally. Some may be optimists, others may be pessimists. Some want to get better everyday, others are happy where they are. Some like change, others resist it. Some are data driven, others use their instinct.

All this variation affects the way a job gets done. The variation is propagated into the work and ultimately manifests itself in the variation of the manufactured component.

Measurement We consider a measured value as fact, immutable. But that’s not true. Measuring the same attribute repeatedly does not produce identical results between measurements.

Just like production tools, measurement tools wear from use. This affects the measurement made with it over the course of its use.

And also just like production tools, the method (e.g. how a part is oriented, where on the part the measurement is made, etc.) used to make a measurement affects the measured value. There is no true value of any measured attribute. Different measurement methods produce different measurements of the same attribute.

So even if by chance two pieces were made identical we wouldn’t be able to tell because of the variability inherent in the measurement process.

Environment Certain environmental factors affect all operations regardless of industry. One of them is time. It is not identical from one period to the next. Months in a year are not identical in duration. Seasons in a year are different from one another. Daytime and nighttime are not identical to one another. Weekdays and weekends are not identical to one another.

Even in a climate controlled facility the temperature cycles periodically around a target. It varies between locations as well. Lighting changes over the course of the day. Certain parts of the workplace may be darker than others. Noise, too, changes over the course of the day: quiet early in the morning or into the night, and noisier later into the day. There is variation in the type of noise, as well. Vibration by definition is variation. It can come from a heavy truck rolling down the street or the motor spinning the cutting tool in a production machine. Air movement or circulation isn’t the same under a vent as compared to a spot away from a vent, or when the system is on versus when it is off.

The 5M+E (Material, Machine, Method, Man, Measurement, and Environment) is just one way to categorize sources of variation. The examples in each are just a few of the different sources of variation that can affect the quality of individual pieces of a component. While we cannot eliminate variation, it is possible to systematically reduce it and achieve greater and greater uniformity in the output of a process. The objective of a business is to match the Voice of the Customer (VOC) and the Voice of the Process (VOP). The modern day world-class definition of quality is run-to-target with minimal variation!

Our approach has been to investigate one by one the causes of various “unnecessaries” in manufacturing operations…
— Taiichi Ohno describing the development of the Toyota Production System

[1] Kume, Hitoshi. Statistical Methods for Quality Improvement. Tokyo, Japan: The Association for Overseas Technical Scholarship. 2000. Print. ISBN 4-906224-34-2

[2] Monden, Yasuhiro. Toyota Production System. Norcross, GA: Industrial Engineering and Management Press. 1983. Print. ISBN 0-89806-034-6

[3] Wheeler, Donald J. and David S. Chambers. Understanding Statistical Process Control. Knoxville, TN: SPC Press, Inc. 1986. Print. ISBN 0-945320-01-9

Some Thoughts on the Toyota Production System


The Toyota production system (TPS) was not designed.

The technique we call the Toyota production system was born through our various efforts to catch up with the automotive industries of western advanced nations…
— Taiichi Ohno, Foreword to Toyota Production System[1]

It grew out of “various efforts.” Often these efforts were “trial and error.” Experiments were run, lots of them. Some yielded desirable results, others did not. But lessons could be learned from every experiment—What worked? What didn’t? Why?

What made an outcome of an experiment desirable? What was the purpose of these efforts?

Above all, one of our most important purposes was increased productivity and reduced costs.

So how was productivity increased and costs reduced? Toyota guessed (or hypothesized) this could be done by “eliminating all kinds of unnecessary functions in the factories,” what we’ve come to term as waste. We all recognize there are many ways to produce the same result. However, some are less wasteful than others. They are efficient.

By attending to what is actually happening, by observing the real process, a worker could identify waste in various forms. Observation comes before understanding.

Our approach has been to investigate one by one the causes of various “unnecessaries” in manufacturing operations…

One by one!

If we take a minute to think about how many different operations—small and large, localized and cross-functional—take place in factories, we start to understand the scale of Toyota’s effort. That takes patience, discipline and perseverance i.e. grit. The image of a bee hive or a migrating wildebeest herd or a flock of starlings comes to my mind. There is no centralized design or control, nevertheless all members work with the same purpose.

…and to devise methods for their solution…

To eliminate the causes of different types of waste, i.e. the unnecessary functions in the factories, Toyota devised solutions such as kanban, just-in-time, production smoothing, and autonomation. These methods are outcomes of a way of thinking and being. Experimentation through trial and error. They are the means Toyota developed to achieve its purpose of increasing productivity and reducing costs. They could be spread within Toyota, but can they be used elsewhere? Many examples exist of attempts to incorporate them in companies here in the West. I’ve had a front row seat to many of them. Few, if any, show the type of sustained benefits seen by Toyota. Why is that? Context!

Although we have a slight doubt whether our Just-in-time system could be applied to the foreign countries where business climates, industrial relations, and many other social systems are different from ours, we firmly believe there is no significant difference among the final purposes of the firms and the people working in them.

All companies operate within an environment: business climates (e.g. the regulatory environment), industrial relations (i.e. how companies relate to their peers and their suppliers, their communities, and the natural environment), and social systems (such as local traditions and customs). These will necessarily affect the type and form of tools that emerge from experiments that (should) happen in support of a particular company’s purpose. By the way, contrary to Ohno’s point, and as irrational as it seems, not all companies have the same final purpose as Toyota—to increase productivity and reduce costs. Similarly, people in the West have different objectives, different worldviews, than those in the East.

The Toyota production system, and perhaps even lean, is a way of being in pursuit of certain purpose(s). They are not a set of tools to copy and deploy independent of and indifferent to the context where they are deployed. It shouldn’t surprise anyone that efforts to unthinkingly copy and apply them fail more often than succeed.

[1] Monden, Yasuhiro. Toyota Production System. Norcross, GA: Industrial Engineering and Management Press. 1983. Print. ISBN 0-89806-034-6

Some Observations and Thoughts on Design Controls

In my role as a quality engineer supporting product design and development at various medical device manufacturers I got practical experience with each company’s design and development process. As a matter of regulation[1], each medical device manufacturer has procedures that control the design of their products. Unfortunately, they are not particularly useful.

I’ve observed that the Quality function at these companies develops and deploys all the procedures that the Quality System regulations require[2]. However, professionals in the Quality function typically don’t have the subject matter expertise in a particular function such as product design and development or manufacturing to develop usable procedures for that function.

Here I share an example product design and development procedure typical of those I have seen deployed:

This type of process, laid out in the order of the text of the regulation, would suggest that product design and development is a sequence of steps executed in series.

At first glance it seems logical and sensible. First you catalog the user needs. Next you convert those user needs into design inputs (i.e. engineering requirements.) You then transform the design inputs through the design process into design outputs (i.e. drawings or prototypes.) Those design outputs are then verified (i.e. inspected and tested) against the design inputs. After that the design is validated by the user in the actual or simulated use environment. And finally, the design is transferred to manufacturing for mass production.

It wrongly suggests, albeit implicitly, that these steps also represent phases of design and development where a review is conducted after each block, and that a single traceability matrix, with columns corresponding to each block, is enough to capture the activity of the total design effort.

I have tried to figure out how this would work for a design involving multiple components that are assembled together, but I cannot find a way. This type of design for the product design and development process is fatally flawed as it doesn’t model the real nature of products which is often components/systems embedded within systems. Trying to map the total design effort into this format is like trying to fit a square peg in a round hole, an impossible and ultimately frustrating exercise.

Just because language is linear, in that ideas are expressed one after the other as the regulation does, doesn’t mean that the process being described is linear, too. In fact, the design and development process is most certainly not linear. It is deeply iterative with iterations built within iterations!

The FDA’s “Design Control Guidance for Medical Device Manufacturers”[3] provides an explanation of the iterative nature of the design and development process. The guidance includes a simplified process flow chart, but it does not adequately communicate the complexity that makes up the actual design and development process. The guidance even explicitly says so.

In practice, feedback paths would be required between each phase of the process and previous phases, representing the iterative nature of product development. However, this detail has been omitted from the figure…

The language of the guidance in the above paragraph unfortunately implies that each block of the waterfall design process is a phase. It clarifies this further on where it says:

When the design input has been reviewed and the design input requirements are determined to be acceptable, an iterative process of translating those requirements into a device design begins. The first step is conversion of the requirements into system or high-level specifications. Thus, these specifications are a design output. Upon verification that the high-level specifications conform to the design input requirements, they become the design input for the next step in the design process, and so on.

This basic technique is used throughout the design process. Each design input is converted into a new design output; each output is verified as conforming to its input; and it then becomes the design input for another step in the design process. In this manner, the design input requirements are translated into a device design conforming to those requirements.

While the regulation does not prescribe a method for designing and developing a product, the guidance does point in a particular direction. The best representation I could find that captures the direction in the guidance is this graphic adapted from “The House of Quality” by John Hauser and Don Clausing[4]:

The first “house” shows the “conversion of the requirements [Customer attributes] into system or high-level specifications [Engineering characteristics]”. The body of the house allows for the verification that “high-level specifications conform to the design input requirements”. The engineering characteristics then “become the design input for the next step in the design process, and so on.

It’s obvious from the linked houses and the guidance that verification is not a one time or single type of activity. It is performed at each step of the design and development process wherever inputs are converted to outputs. Implicit in this point is that the type of verification is unique to the particular step or phase of the design and development process.

Each house may be thought of as a phase of the design and development process. The houses offer natural breaks. The design process of the next phase, converting inputs into outputs, depends on the successful completion of the previous phase, so it is nearly impossible to move too far down the process as gaps will be immediately apparent!

Each house can be considered its own traceability matrix where every design output is tied to one or more design inputs. And because the houses are all linked to one another it is possible to trace an attribute of the manufactured product all the way back to the customer need it helps address.

While they may not have a firm conceptual understanding of the design and development process, and thus cannot explain it, I believe most engineers have an instinctual feel for it in practice. But a poorly designed design and development process creates unnecessary and insoluble problems for project teams. The teams I’ve been on have responded to such hurdles by running two parallel processes: one that is the practical design and development effort, and the other is the documentation effort—a hidden factory. I don’t think it’s possible to calculate the cost of such waste.

[1] 21 CFR Part 820.30 (a) Retrieved 2017-07-05
[2] QSR Required Procedures Retrieved 2017-07-05
[3] Design Control Guidance For Medical Device Manufacturers Retrieved 2017-07-05
[4] The House of Quality. Harvard Business Review, pages 63-77, Vol 66 No 3, May 1988.
[5] Product Design and Development, 5th Edition. McGraw Hill, 2016.

Whose Measurement is Right?

Every company I’ve worked for inspects the product it receives from its suppliers to determine conformance to requirements. The process is variously referred to as incoming inspection or receiving inspection.

Sometimes the receiving inspection process identifies a lot of product that fails to conform to requirements. That lot is subsequently classified as nonconforming material and quarantined for further review. There are many reasons why a lot of product may be classified as nonconforming. Here I wish to focus just on reasons having to do with measurement.

Once a company discovers nonconforming parts, it usually contacts its supplier to share that information. It is not unusual, however, for the supplier to push back when their data for the lot of product shows it to be conforming. So, how can a given lot of product be both conforming and nonconforming? Who is right?

We need to recognize that measurement is a process. The measured value is an outcome of this process. It depends on the measurement tool used, the skill of the person making the measurement and the steps of the measurement operation. A difference in any of these factors will show up as a difference in the measured value.

It is rare that a measurement process is the same between a customer and its supplier. A customer may use different measurement tools than its supplier. For example, where the customer might have used a caliper or micrometer, the supplier may have used an optical comparator or CMM. Even if both the customer and the supplier use the same measurement tool, the workers using that tool are unlikely to have been trained in its use in the same way. Finally, the steps used to make the measurement, such as fixturing, lighting and handling the part, which often depend on the measurement tool used, will likely be different, too.

Thus, more often than not, a measurement process between a supplier and a customer will be different. Each measured value is correct in its context—the supplier’s measurement is correct in its context, as is the customer’s measurement in its context. But because the measurement process is different between the two contexts, the measured values cannot be compared directly with one another. So it is possible that the same lot of product may be conforming per the supplier’s measurements and nonconforming per the customer’s measurements.

But why are we measuring product twice: once by the supplier and again by the customer? Measurement is a costly non-value adding operation, and doing it twice is excess processing–wasteful. One reason I’ve been told is this is done to confirm the data provided by the supplier. But confirmation is possible only if the measurement process used by the customer matches the one used by the supplier.

Besides, if we are worried about the quality of supplier data, we should then focus efforts on deeply understanding their measurement process, monitoring its stability and capability, and working with the supplier to improve it if necessary. With that we should trust the measurement data the supplier provides and base our decisions on it, and eliminate the duplicate measurement step during receiving inspection.

[1] Eliminate Waste in Incoming Inspection: 10 ideas of where to look for waste in your process Retrieved 2017-06-29

Above All, Don’t Wobble

In walking, just walk. In sitting, just sit. Above all, don’t wobble.
– Yúnmén

The companies I’ve worked for have been neurotic. They dither. When decisions are made they have an irrational and anxious quality about them.

My experience of work can be described as a shuddering paralysis. In an effort to take everything into account teams I’ve been on enter into an infinite regression of analysis that often takes us off course, delaying action. (I have been guilty of contributing to this.) However, the essence of a business is to act, to do.

When we do act, we don’t just act, but worry about whether that action is the best possible; we complain about all the flaws we find in the method; we even wonder whether the goal is the right goal. So our attention is split, bouncing between acting and thinking. Instead of moving gracefully toward our goal, we wobble. I wobble.

Perhaps Yúnmén wouldn’t mind if I rephrased his quote as “In planning, just plan. In doing, just do. Above all, don’t wobble.”

Human Error

Often, investigators identify the root cause of a problem as human error. But what exactly is human error?

An action may be judged as an error only in relation to a reference or standard. So first a standard on how to perform the task must exist. Sometimes such a standard is defined in a documented procedure. On occasion it may also be taught by a master to an apprentice on the job. Most times we just figure it out through a combination of past experience, current observations, and some fiddling. Human error, then, is action by a human that deviates from the standard.

When we judge the root cause of a problem as human error we’re making certain assumptions: 1] that a standard exists, and 2] the standard, if it exists, is adequate to the degree that mindfully following it produces the expected outcome.

Let’s grant that both the above assumptions are true, and even grant that the root cause of a problem was the failure of the worker to follow the standard. What, then, should the corrective action be that will prevent the recurrence of the problem? In my experience it has almost always been defined as “retraining”. But such a corrective action assumes that the worker failed to follow the standard because they don’t know it. Is this true? If not, retraining is pure waste and won’t do a damn thing to prevent the recurrence of the problem.

If a proper standard exists and the worker has been trained to it, then there must be some other reason for their failure to follow it. Skill-based errors (i.e. slips and lapses) can occur when the worker is unable to pay attention to or focus on performing the task they are otherwise familiar with. So it’s not a training issue. In my previous post I wrote about how willpower, our conscious awareness, is like a muscle. It can fatigue from use. As willpower is depleted the mind resorts to mental shortcuts or habits. This is how errors creep in.

We should not rely only on our ability to remain attentive and focused to ensure that the task is performed without failure. For that we must design tasks in such a way that failure is unlikely, if not impossible, to occur. Through design thinking we can develop tools, methods, and systems that help us perform better.

[1] Understanding human failure. Retrieved 2017-06-15

Personal Willpower, Communal Impact


We seem to make decisions in more impulsive ways than before. Many of us don’t seem to practice any reasonable amount of self-control. I feel this may be because most of us today just don’t have strong willpower.

Last year I read a book called “Willpower”[1] by Roy F. Baumeister and John Tierney. In it the authors liken willpower to muscle. And just like a muscle willpower can wear out from fatigue. When willpower is worn out, we behave more impulsively. How quickly we drain our willpower depends on how strong it is.

In using our willpower to make decisions we’re using our conscious mind or “System 2” as Daniel Kahneman refers to it in “Thinking, Fast and Slow”[2]. Conscious decision making or thinking is hard! It requires effort and uses a lot of energy in the process.

The body, however, has a limited store of energy. When we are low on energy, this conscious decision making process shuts down and decision making is shunted to the brain’s default decision making process or “System 1.” It doesn’t require much energy; it’s automatic and occurs outside of our conscious awareness. Many of the decisions we make in the default mode are driven by habit.

Conscious decision making generally produces reliable outcomes. We make better decisions with it. Not so with automatic decision making, which has been shown to be error-prone, often in systematic ways. So it’s important that we exercise our willpower; build it up, and make it stronger.

No one can make you exercise your body or mind. That’s a choice you make for yourself. But the results of your choice affects your behavior which in turn affects society. We live in communities and we have an obligation to them: to be the best version of ourselves.

[1] Baumeister, Roy F., John Tierney (2012). Willpower: Rediscovering the Greatest Human Strength.
[2] Kahneman, Daniel (2011). Thinking, Fast and Slow.

The Context for Concepts

In my last post I might have left the impression that conceptualizing the real place is bad or that we should avoid it. This is not a correct impression.

We cannot avoid conceptualizing the real place. It’s automatic; part of our biological structure and the structure of our language. Concepts are how we make sense of the real place. They provide insights into the real place. We need those insights to respond appropriately to the real place. But we shouldn’t lose sight of the fact that concepts are the mind’s representations of the real place and not the real place itself! We can call them images, idols, models, data, or symbols.

D. T. Suzuki[1] shared, “To point at the moon a finger is needed, but woe to those who take the finger for the moon…” Alfred Korzybski[2] wrote in Science and Sanity, “A map is not the territory it represents, but, if correct, it has a similar structure to the territory, which accounts for its usefulness.” George E. P. Box[3], in Statistics for Experimenters, put it pithily that “all models are wrong; some models are useful.” These reminders, to be consciously aware of the difference between the real place and our mind’s abstractions of it, is the thread that runs through science and religion.

Problems only arise when we hold onto a concept long after it has stopped representing the real place and a gap has developed between what is and what we conceptualize it to be. To know what is, we must first “go and see” the real place. Without that direct experience with the real place, we cannot hope to act in ways appropriate to it. This is my understanding of what Zen and lean teach.

[1] D.T. Suzuki
[2] Alfred Korzybski
[3] George E.P. Box

The Real Place

My study of Buddhist thought, and especially Zen, have so far taught me that I am often unaware of the real place. Decades of schooling and acculturation to society have taught me to ignore the real place in favor of concepts manufactured by the human mind; to create and be hypnotized by images and models. Right, wrong, god, devil, me, you, husband, wife, mother, father, boss, servant, friend, enemy, success, failure, good, bad, us, and them are all concepts. These are all creations of the mind. It gives them meaning. They’re not real.

Concepts are static–unchanging and easy to grab a hold of and cling to, while the real place is dynamic–ever changing; sometimes in predictable ways, most times in unpredictable ways. The real place offers nothing to grab on to; nothing to cling to. It is inevitable then that the two will eventually diverge from one another. I believe that that gap between what I see and what I think I see is the source of much, if not all, my suffering–frustration, anxiety, feelings of helplessness, exhaustion, and such. To experience the real place, I must let go of concepts, or rather I should not cling to them. Only then will my actions be appropriate or right for the real place.

Zen has been useful in ferrying me back to the real place every time my mind drifts to concepts.

My most direct experience of this gap, or at least one that I am most aware of, has been in the workplace. Data, charts, procedures, policies, concepts abound. Again, most, if not all, are disconnected from the real processes and systems. How work actually happens. However, like me, organizations remain mostly unaware of the disconnect. They thus suffer in a mire of internal conflict and frustration, too.

Lean can be useful to get organizations back to the real place.

PDCA During Product Development

I used the concept of the PDCA cycle (below) during a few new product introduction projects. The teams realized many tangible and intangible benefits from it.

Plan  The engineering concept for a part is converted into a detailed drawing. It provides a graphic representation of the part along with all its engineering requirements/specifications. Among other things, it defines the geometry, dimensions, tolerances, and material for the physical part. The drawing of the part acts as the plan for the manufacturer to follow when making the physical part.

Do  The manufacturer uses the drawing of the part (plan) to make the physical part (do).

(Note: If you outsource the manufacturing of the part, lead times could be as much as 14 weeks or 3+ months. So, it’s a good idea to involve the manufacturer in the planning phase of the part to address any foreseeable issues as early as possible.)

Check  The physical part is inspected (checked) against the drawing of the part (plan) e.g. as part of a first article inspection (FAI) or receiving inspection. Discrepancies between the physical part and its drawing are identified.

Act  Decisions are made for each discrepancy to determine whether the part must comply with the existing drawing specifications or whether the drawing specifications—typically the tolerances around an attribute—should be changed.

If it’s decided that the drawing specifications are to be changed, e.g. the tolerances for one or more attributes is to be loosened, then the drawing is revised. This results in another loop through the PDCA cycle with the new drawing or plan.