Content By Harish Jose

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By: Harish Jose

Shigeo Shingo is one of my heroes in industrial engineering. He had a great mind that thrived on curiosity. Today I am looking at Shingo’s Whys. This is in contrast to Taiichi Ohno’s 5 Whys method.

Ohno’s 5 Whys method is one of the tools in Toyota Production System to get to the root cause of an issue. When you see a problem, you ask, “Why did that problem happen?” When you get an answer to that question, you then ask, “Why did that problem No. 2 happen?” and so on until you get to the root cause. When you eliminate the root cause, the problem is solved.

This approach assumes a direct and linear cause-and-effect relationship. And depending on the user’s expertise and experience, you can get different results. A tool like 5 Whys is user-dependent and one-dimensional. It is appropriate for necessary causes; it may not be appropriate for sufficient causes. Its usefulness certainly diminishes as complexity increases.

Shingo’s Whys are not in relation to Ohno’s 5 Whys, but another set of questions, known as 5W1H. They are:
1. Who?
2. What?
3. Where?
4. When?
5. Why?
6. How?

Harish Jose’s picture

By: Harish Jose

In today’s column, I am looking at wu wei, which is an important concept detailed in the Chinese classic text, Tao Te Ching. This term is generally translated into English as wu = no, wei = action, or no action. There are other similar concepts in Taosim such as wu shin or no mind.

Alan Watts, the delightful English philosopher described wu wei as “not forcing”:
“The whole conception of nature is as a self-regulating, self-governing, indeed democratic organism. But it has a totality that all goes together, and this totality is the Tao. When we can speak in Taoism of ‘following the course of nature; following the way,’ what it means is more like this: Doing things in accordance with the grain. It doesn’t mean you don’t cut wood, but it means that you cut wood along the lines where wood is most easy to cut, and you interact with other people along lines which are the most genial. And this then is the great fundamental principle which is called wu wei, which is not to force anything. I think that’s the best translation. Some call it ‘not doing,’ ‘not acting, ‘not interfering,’ but ‘not to force’ seems to me to hit the nail on the head. Like don’t ever force a lock; you’ll bend the key or break the lock. You jiggle until it revolves.

Harish Jose’s picture

By: Harish Jose

As readers of my columns know, I am an ardent student of the Toyota Production System (TPS). One of the core philosophies of TPS is kaizen, often translated from Japanese as “continuous improvement.” It is the idea that one should continuously find ways to eliminate nonvalue-adding activities, and in the process develop oneself and others to get better at kaizen. The idea of kaizen begetting more kaizen.

Kaizen is a human capital enrichment philosophy. As Eiji Toyoda, Toyota Motor Corp.’s president from 1967 to 1982, said, “It is people that make things, and so people must be developed before work can start.”

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By: Harish Jose

In today’s column, I’m looking at Weber’s Law. It’s named after Ernst Heinrich Weber (born June 24, 1795, died Jan. 26, 1878), a German physician who was one of the pioneers of experimental psychology. I highly recommend the Numberphile YouTube video that explains this in detail.

A simple explanation of Weber’s Law is that we notice things more at a lower intensity than at a higher intensity. For example, the light from your phone in a dark room may appear very bright to you. At the same time, the light from your phone in a bright room may seem insignificant. This type of perception is logarithmic in nature. This means that a change from 1 to 2 feels about the same as a change from 2 to 4, or 4 to 8. The perception of change for an increment of one unit depends on whether you are experiencing it at a low intensity or a high intensity. At low intensity, a slight change feels stronger.

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By: Harish Jose

It has been a while since I have written about statistics, and I get asked a lot about a way to calculate sample sizes based on reliability and confidence levels. So today I am sharing a spreadsheet that generates an operating characteristic (OC) curve based on your sample size and the number of rejects. The spreadsheet (there's a link to it at the end of this article) should be straightforward to use. Just enter your own data in the required yellow cells.

A good rule of thumb is to use a 95-percent confidence level, which also corresponds to 0.05 alpha. The spreadsheet will plot two curves. One is the standard OC curve, and the other is an inverse OC curve. The inverse OC curve has the probability of rejection on the y axis, and the percent conforming on the x axis. These correspond to confidence level and reliability, respectively.

I will discuss the OC curve and how we can get a statement that corresponds to a reliability/confidence level from the OC curve.

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By: Harish Jose

Today I’m looking at design from a cybernetics viewpoint. My inspirations come from cybernetics and design theorists Ross Ashby, Stafford Beer, Klaus Krippendorff, Paul Pangaro, and Ranulph Glanville. I was curious about how the interface of a device conveys the message to the user on how to interact with it. For example, if you see a button, you are invited to press it. In a similar vein, if you see a dial, you know to twist it. By looking at the ideas of cybernetics, I feel that we can expand on this further.

Ross Ashby, one of the pioneers of cybernetics, defined “variety” as the number of possible elements (or states) of a system. A stoplight, for example, generally has three states—red, green, and yellow. Additional states are possible, such as blinking red, no light, or simultaneous combinations of two or three lights. Of all the possible states identified, the stoplight is constrained to have only three states. If the stoplight is not able to regulate traffic acting in tandem with similar stoplights, traffic gets congested and results in a standstill. Thus, we can say that the stoplight was lacking the requisite variety.

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By: Harish Jose

One of my favorite equations from Factory Physics, by Wallace Hopp and Mark Spearman (Waveland Press, third edition, 2011) is Kingman’s formula, usually represented as “VUT.”

The VUT equation is named after Sir John Kingman, a British mathematician:

The first factor represents variability and is a combination of variability factors representing arrival and service times (e.g., flow variability and process variability). The second factor represents utilization of the workstation or the assembly line. The third factor represents the average processing time in the workstation or the assembly line. The VUT equation shows that the average cycle time or wait time is proportional to the product of variability, utilization, and process time.

The most important lesson from VUT is: If a station increases utilization without making any other change, average work in process (WIP) and cycle time will increase in a highly nonlinear fashion.

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By: Harish Jose

After reviewing Mark Graban’s wonderful book, Measures of Success (Constancy, 2018), I started rereading Walter Shewhart’s books, Statistical Method From the Viewpoint of Quality Control (Dover reprint 1986, originally edited by W. Edwards. Deming), and Economic Control of Quality of Manufactured Product (Martino Fine Books, 2015 reprint). Both are excellent books for any quality professional.

One of the themes that stood out for me while reading the two books was the concept of cybernetics. This column is a result of studying Shewhart’s books as well as articles on cybernetics by Paul Pangaro.

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By: Harish Jose

I must confess up front that the title of this column is misleading. Similar to the Spoon Boy in the movie, The Matrix, I will say, “There is no lean problem or a Six Sigma problem. All these problems are our mental constructs of a perceived phenomenon.”

A problem statement is a model of the actual phenomenon that we believe is the problem. The problem statement is never the problem! It is a representation of the problem. We form the problem statement based on our vantage point, our mental models, and biases. Such a constructed problem statement is thus incomplete and sometimes incorrect. We don’t always ask for the problem statement to be reframed from the stakeholder’s viewpoint.

A problem statement is an abstraction based on our understanding. Its usefulness lies in the abstraction. A good abstraction ignores and omits unwanted details, while a poor abstraction retains them, or worse, omits valid details. Our own cognitive background hinders our ability to frame the true nature of the problem.

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By: Harish Jose

Today I’m looking at Factory Physics and the Toyota Production System (TPS). My main references for the post are the 1977 paper co-authored by ex-Toyota president Fujio Cho and key ideas from Factory Physics (Waveland Press, 2011).

One of my favorite definitions of lean comes from Wallace J. Hopp and Mark L. Spearman, who wrote Factory Physics. They defined lean as follows: “Lean is fundamentally about minimizing the cost of buffering variability.... Production of goods or services is lean if it is accomplished with minimal buffering costs.”