Jun 17 2019

Is TPS Both a Dessert Topping and a Floor Wax?

Darren Migita, MD

“TPS can be applied to any setting, as long as you can define your customer and product…” – Darren Migita MD– Seattle Children’s

Quoted by Jun Nakamuro on LinkedIn from a podcast.

 

 

Michel Baudin‘s comments: To be fair, Dr. Migita is a pediatrician with 20 years of experience. His podcast is about adapting TPS to health care, not to “any setting.” It is an interview, a format that can trip up anybody.

What I find remarkable throughout is that Migita does not hide behind the word “Lean.” He explicitly refers to Toyota and Taiichi Ohno and vigorously asserts that you can borrow ideas for car making to improve patient care.

This opening sentence in Jun Nakamuro’s quote, however, makes TPS sound like Shimmer, the product once advertised on Saturday Night Live as “both a dessert topping and a floor wax.” It almost kept me from listening further.

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By • Blog clippings • 0 • Tags: , , , ,

MadridSeminar4-22-2019

Jun 10 2019

How Industry 4.0 Contributes to Operational Excellence | Lecture notes from Jose Ignacio Erausquin | Madrid, 5/22/2019

Jose Igacio Erausquin

At the invitation of our Spanish partner Asenta, Michel Baudin gave a lecture in Madrid on the ways Industry 4.0 does or can contribute to operational excellence. Industry 4.0 was presented as a stack of technologies — from direct machine control to knowledge management — with each layer relying on the layers below. Following are the notes taken by Asenta’s Jose Ignacio Erausquin, organized by layer.

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By • Automation • 0 • Tags: , , , , , , ,

Mar 31 2019

Industry 4.0 versus Manufacturing Improvement (Part 1)

Elon Musk

There is a lesson that manufacturing leaders seem determined to learn the hard way: flooding factories with new technology does not improve their performance.

Roger Smith learned it at GM in the 1980s. Elon Musk, for all his other achievements, admitted by tweet to making the same mistake at Tesla last year.

To really improve manufacturing performance, you start with, as Crispin Vincenti-Brown put it, with “what happens when the guy picks up the wrench.” You work with that person to make the work easier, faster, safer, and less prone to deviations and errors. In doing this, you apply, as needed, technology you can afford that operators can work with.

This is hard work but it pays off. It is a key lesson learned from Toyota, TPS, and many companies that implemented it under the “Lean” label. But it’s an eat-your-vegetables message. The lure of a technological shortcut is irresistible.

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By • Information Technology • 17 • Tags: , , ,

Mar 25 2019

Are Robots Competing for Your Job? | Jill Lepore | The New Yorker

Christoph Niemann

“The robots are coming. Hide the WD-40. Lock up your nine-volt batteries. Build a booby trap out of giant magnets; dig a moat as deep as a grave. “Ever since a study by the University of Oxford predicted that 47 percent of U.S. jobs are at risk of being replaced by robots and artificial intelligence over the next fifteen to twenty years, I haven’t been able to stop thinking about the future of work,” Andrés Oppenheimer writes, in “The Robots Are Coming: The Future of Jobs in the Age of Automation” (Vintage). No one is safe. ”

Source: The New Yorker

Michel Baudin‘s comments:

In this article, Jill Lepore skewers the countless gurus who, for the past 100 years, have been predicting a future in which robots have eliminated all jobs, manufacturing or not. While Lepore does not go back that far, “Robot” is a word from science fiction, specifically Karel Čapek’s 1920 play Rossum’s Universal Robots. In this play, robots actually kill off humans.

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By • Automation • 1 • Tags: , ,

Mar 12 2019

More About the Math of the Process Behavior Chart

In statistics on time series with “moving” in their name, each value is correlated with past and future neighbors — that is, the series is autocorrelated. It affects the way you can use these statistics to detect anomalies and issue alarms.

The moving range in the XmR chart is a case in point. Its autocorrelation in the moving range chart is self-inflicted. It is autocorrelated by construction, regardless of whether the raw data themselves are.

Some raw data are autocorrelated. For example, when you issue a replenishment order for a part by pulling a Kanban from a bin, you are assuming that the demand for a coming period to match that of the period that just elapsed, with minor fluctuations. Implicitly, you are leveraging the autocorrelation of the part consumption across periods.

On the other hand, if a physical characteristic of a manufactured part is the sum of a constant and noise, then the noises are independent, and therefore uncorrelated. Taking moving ranges introduces an autocorrelation between consecutive values that is absent in the raw data.

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By • Data science • 7 • Tags: , , ,

Mar 2 2019

The Math Behind The Process Behavior Chart

Ever since asking Is SPC Obsolete? on this blog almost 6 years ago, multiple sources have told me that the XmR chart is a wonderful and currently useful process behavior chart, universally applicable, a data analysis panacea, requiring no assumption on the structure of the monitored variables. So I dug into it and this what I found.

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By • Data science • 45 • Tags: , ,

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