The Future of Quality

-???????Dr Tony Burns, ?BE (Hon 1)?PhD (Chem Eng)

Published in Quality Digest, Jan 13, 2022. "The Ghost of Quality Future".

I’m a chemical engineer.?The fundamentals of the chemical engineering profession were laid down 150 years ago by Professor Osborne Reynolds.?While chemical engineering has seen many advances, such as digital process control and evolutionary process optimization, every engineer understands and uses Reynold’s work.?Most people have heard of the Reynolds Number, that plays a key role in calculating air and liquid fluid flows.?There are no fads.?Engineers use the fundamentals of the profession.

Fads, fads, fads

By contrast, in the past 70 years, “quality” has seen over 20 fads.?The fundamentals have been forgotten and corrupted.?Quality has been lost.?Quality managers engage in an endless pursuit of magic pudding that will fix all their problems.

Alarmingly, the latest “quality” fad, Agile, has nothing to do with quality!?It is a software development fad that evolved from James Martin’s Rapid Application Development (RAD) fad of the 1980’s.?This in turn grew into the Rapid Iterative Processing (RIP) fad.?When it comes to quality today, anything will do, no matter how unrelated.?

Before Agile we had Quality 4.0 and 5.0.?Again these fads had nothing to do with quality.?They were a mish-mash of whatever might catch the eye of a quality manager.?“Artificial Intelligence” ... how cool ... now who wouldn’t want some of that?; “the Internet of Things” ... trendy but it will do nothing for reducing variation; “3D printing” ... again trendy but it has nothing to do with quality.

The most ubiquitous and destructive fad of all has been Six Sigma.?It was created by a man who said "Six Sigma Champions are con men. ?All you have is smoke and mirrors”.?Ford for example, was one of the first to buy into the nonsense.?An 8 year survey of thousands of Six Sigma projects showed a disastrous average of 220,000 dpm after improvement for “successful” projects.?Yes, that’s 1 in 5 parts that are junk.

Need for Quality

Mass production dates back 2,200 years to China, but it wasn’t till the Industrial Revolution at the start of the 19th Century that it became common place.?Mass production brought with it the need for identical and interchangeable parts, along with control of manufacturing processes.?For example, in 1860’s in the American Civil War, interchangeability was key in using the Minié ball in both the US Springfield and British Enfield rifles.?The need for interchangeability of parts made good quality essential.

In 1870 the concept of the defect fully emerged with the development of the go-no-go gauge.?It was a step of great importance but lacking with regard to process improvement.?An item was either good, or it was trashed.?There was nothing in-between. ?Variation was just on-off. ?Quality was measured by counting defects.

The Fundamentals of Quality

The Osborne Reynolds of Quality was Professor Deming.?He drew greatly on those who came before, particularly Dr Shewhart and Professor Lewis.?Deming created the modern definition of quality – “On target with Minimum Variance”.?It was a massive advance on counting defects.?

Understanding Deming is key to building, maintaining and predicting good quality now and into the future.?He laid the basis for Quality as a profession, with his System of Profound Knowledge, his famous 14 points, 7 Deadly Diseases, Plan-Do-Study-Act and Operational Definition Methodologies.

Professor Deming emphasized the importance of being able to predict the behaviour of process into the future.?His key tool was the Shewhart Chart.

Economic Chart

While statistical methods had been available for over a century, these were poorly suited to processes.?In 1924 Dr Shewhart introduced his Control Chart.?Dr Shewhart talked much of economics.?His Control Chart was an economic chart, not a probability chart: “This state of control appears to be, in general, a kind of limit to which we may expect to go economically in finding and removing causes of variability”.??Dr Shewhart defined his control limits as “economic limits”.

Dr Shewhart added a key point “… in developing a control criterion we should make the most efficient use of the order of occurrences as a clue to the presence of assignable causes” (1931). This is not provided by classical statistics.?The Control Chart is unique in its use of the element of TIME.?Exactly the same data in a different time sequence gives totally different results.?

Even more importantly: “Statistical control is not mere application of statistics ... Classical statistics start with the assumption that a statistical universe exists, whereas SPC starts with the assumption that a statistical universe does not exist.” (1944). That is, Dr Shewhart’s Control Charts do not depend on the nature of underlying data distributions. ?They do not assume nor require normality.

Sadly, most people at the time and still today, don’t understand.?Hopefully this will change in the coming years.

Quality vs Traditional Statistics

The Shewhart Chart was a radical step forward.?It rattled the statistical establishment.?There was a fork in the road.?Dr Shewhart forged the new road of Quality while others continued down the path of traditional statistics.?

Dr Pearson called Dr Shewhart “illogical”, while others such as Dr Golomski described Dr Shewhart as a “hero”.?Professor Ishikawa was “greatly impressed with the depth of his philosophy”.?Dr Ott and Professor Deming recognised the brilliance of Dr Shewhart and continued to build on his work.?Later, Dr Chambers and Dr Wheeler built upon and further extended Dr Shewhart’s work.

One of the greatest contributions to Quality came from Dr Wheeler.?He proved Dr Shewhart’s assertion by testing 1143 different data distributions and proving that normality is not required for Process Behavior Charts.?He pointed out that we can never know the data distribution for a changing process ... and that we don’t need to know!

Misunderstanding Dr Shewhart

Many prominent figures at the time, such as Mr Juran esq, were dismissive and failed to understand Dr Shewhart.? Juran stated that it was “beyond the grasp of the unsophisticated user”.?Even by the 1980’s Juran still didn’t understand and was still referring to Control Charts as a 'test of statistical significance.’??Juran continued to produce charts of defects more appropriate to a century before.?

Today, most quality practitioners fail to understand Dr Shewhart and the Process Behavior Chart.??Popular authors such as: Mr Pyzdek, Mr Breyfogle, Mr Kubiak, Mr Monro, Mr Shankar, Mr Martin, Mr P Gupta, Dr Woodall and Professor D Montgomery all show a lack of understanding.?Popular authors such as Mikel Harry, do not even discuss this central aspect of Quality.?Harry’s Motorola workmate Bhote (1991) understood even less and referred to Control Charting as “a total waste of time”.

Hundreds of thousands of practitioners and clients have read these authors’ material and have been misled.?It was inevitable that quality suffered. ?This key tool, at the heart of Quality, has been corrupted.

Importance of Understanding

Future progress in Quality depends on people understanding these basics.?Instead, fads have proliferated, using up to 140 tools as course stocking filler fluff.?

Nothing has changed from when Professor Ishikawa pointed out that all that anyone needs is the wise use of the basic 7 tools.?More tools do not give better quality.

Keeping it simple greatly benefits clients.?It makes it easy for all employees to be involved in quality, as Professor Deming advocated.?Front line workers are the real process experts.?Involving them in Quality is not difficult, if done wisely.

Consequences of Not Understanding Dr Shewhart

Like many people, the popular author Professor Montgomery, falsely claims that Process Behavior Charts are probability charts.?Like so many faddists, he confuses specification and control limits. He throws in the nonsense term “three-sigma performance”.

There is no such thing as “three-sigma quality performance”.?The performance of a process is determined by its stability, that is, whether or not assignable causes are present. ?

Most people are confused about what quality means.?Hopefully better education in the coming decades will correct this.?Defects relate to the specification limits, not control limits.?Specification limits can be set anywhere, to produce any level of defects.?Control limits describe the behavior of the process.?

A process that is not in-control has one or more assignable causes acting and may produce any amount of defects.?Process Behavior Charts provide a warning to workers, as to when to investigate for such assignable causes.?When such an assignable cause is corrected, it may affect the entire process.?That is, it is not necessarily simply an ephemeral event.

Montgomery’s failure to understand the nature of Process Behavior Charts leads him to the ridiculous claim that that for 100 parts: "… about 23.7% of the products produced under three-sigma quality will be defective."?He fails to understand that the Process Behavior Chart is the Voice of the Process.?An in control process is predictable.?However, an out of control process makes no prediction whatsoever about the number of defects that may be produced.?The 23.7% figure is laughable.?Tokai Rika for example, produces 500,000 parts per month, fully in control.

Misuse of Probability

We might apply Montgomery’s probability approach to an automobile, with a typical 30,000 parts.?Suppose each of these parts were built to his claim of “excellence”, at 3.4 dpmo.?This would give a (1 - 0.9999966^30000 )?chance of having a defect.?In other words, every automobile manufactured would have a 9.7% chance of being a lemon.?That is, 9.7% of all cars would contain from 1 to many thousands of defects!?Clearly, Montgomery’s approach to defects and probabilities gives?very silly results.

Professor Montgomery suggests that at “six-sigma quality level … the process mean can shift by as much as 1.5 standard deviations off target … to produce about 3.4 ppm defective”.??Claiming 3.4 defects in the extreme tail of a non-existent distribution of an out of control process, is folly.?Shifting process means is a recipe for disaster.

Montgomery suggests that to improve things, we should let the mean float around a bit.?"If the mean is drifting around, and ends up as much as 1.5 standard deviations off target, a prediction of 3.4 ppm defective may not be very reliable, because the mean might shift by more than the “allowed” 1.5 standard deviations."?Montgomery fails to understand that if the mean is shifting, special causes are present. The process is out of control, and may produce any amount of defects, no matter where specification limits are set.

This highlights the huge need for re-education in the basics of Process Behavior Charts.?Hopefully in the future, people will study Professor Deming and Dr Shewhart rather than Professor Montgomery et al.

XmR

A major extension of Dr Shewhart’s work was made in 1942 by W. J. Jennett, with his invention of the XmR, single point moving range Control Chart.?However, it took another 50 years to be popularized.

The first great benefit of XmR charts is that it is easy.?Womack pointed out: “Assembly workers could do most of the functions of the specialists and do them much better because of their direct acquaintance with the conditions on the line”.?XmR charts are an action tool that any worker can use manually, without special software.

The second great benefit of XmR charts is that they can be used for count data, as well as variable data.??Dr Shewhart had no choice other than to use Specialty Charts, P, NP, C and U charts for count data. ??However, these charts each depend on 4 assumptions of a data distribution (binomial or Poisson respectively).?If these assumptions are not met, the chart gives incorrect results. ?XmR charts do not depend on a data model.?Dr Wheeler points out that when a Specialty Chart gives different results to an XmR chart, it is an indication that the assumptions for the specialty chart are not met and hence should not be used.?

The message for the future is clear.?Keep it simple, use XmR.

Philosophy of Quality

A less well known contribution made by Dr Shewhart was the philosophy of Quality.?He read philosopher Professor Lewis’s 471 page book, 14 times.?When Professor Deming said he had read it 7 times and still didn’t understand it, Dr Shewhart told him to read it again.?It led to Professor Deming’s System of Profound Knowledge.

Dr Shewhart is known for Shewhart Cycle.?He took The Scientific Method and applied it to processes, using his Control Charts.?Professor Deming turned this into his PDSA.?

Dr Shewhart also created what he called the “Operational Meaning”, later called the “Operational Definition” by Professor Deming.?This core tool should be learned and used by everyone but is rarely even mentioned:

1. What do you want to accomplish?

2. By what method will you accomplish your objective?

3. How will you know when you have accomplished your objective?

Using the Operational Definition – Covid-19

The question arises, when should use Shewhart Charts??Covid-19 data is a classic example.?There are many attempts to use Control Charts and even logarithmic Control Charts for Covid-19 data.

The first step of the Operational Definition is to ask “What do you want to accomplish?”?Folk trying to draw Control Charts for Covid-19 data have not asked this question.

What we want to know about Covid-19, is whether it is getting better or worse.?What we want to accomplish is a downward trend.?The best method to observe such trends is the Run Chart, or Bar Chart.

Control Charts cannot help answer this question.?All that a Control Chart can show is that the data is non-homogeneous. However we already know this because of the way the disease is spread from one person to many more people.?

Process Behavior Charts are ideal for bringing a process to its full potential and ensuring good quality into the future.?They are worthless for Covid-19 data.?"Any attempt to use a Process Behavior chart to analyze the daily Covid-19 values is a misapplication of the technique. It is conceptually equivalent to someone computing the average for a list of telephone numbers." - Dr Wheeler.?

“How will you know when you have accomplished your objective?”?We will know this when the Run Chart trends to zero.

The root cause for the ubiquitous misuse of Process Behavior Charts is courses failing to teach the fundamentals of Quality.??XmR Process Behaviour Charts make Quality easy for every employee.??The Operational Definition gives guidance in what to do.

“The best analysis is always the simplest analysis that will give the necessary insight” – Dr Wheeler.?In this case, the best tool is the forgotten Run Chart.?Today, there are about 140 quality tools.?Nothing has changed from when Professor Ishikawa pointed out you only need the basic 7, if used wisely.?More tools only add confusion.?They do not improve quality.

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The Future of Quality

Endless fads contribute nothing to quality.?There is no justification to stray from Professor Deming’s PDSA and his Operational Definition.?The Operational Definition is simple.?It cuts through the nonsense.

On one hand we have where Quality should go and on the other, where it will probably go.?At the current rate we should expect to see another dozen or so new quality fads in the next 40 years.?Just a few days ago I saw a consultant claiming there in clearly a need for “Agile TQM Lean Six Sigma”.?He obviously feels he has some client gullible enough to buy in.

Where should quality go??Quality should become a profession in the same way chemical engineering is a profession.?We need to eradicate fads and farce. ?Quality should get back to the fundamentals, laid down by the giants: Professor Deming, Professor Lewis, Professor Ishikawa, Dr Shewhart and Dr Wheeler.

The theme for future quality should be: “Keep it simple.?Back to basics.”

Finally, Dr Wheeler has made far greater contributions to Quality than any other living person.?In the near future he should be rewarded with an appropriate award.

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