May 2 2013

Toyota’s IT Vision at Industry Week’s Best Plants Conference | Chain of Thought

See on Scoop.it – lean manufacturing

“‘…Toyota Motor’s group leaders were complaining about the systems IT was delivering. They wouldn’t let them focus on being out on the production line. So IT’s focus became providing tools to allow group leaders to be more efficient…”

Michel Baudin‘s insight:

The article’s author is challenged about getting to the point but, when he eventually does, it is worth reading. What I found most original is IT focusing on the needs of group leaders, Toyota’s name for first-line managers, who oversee four to six teams of four to six operatiors each. It is a constituency is definitely underserved by IT in most manufacturing organizations and whose potential is underestimated.

Most companies expect little from first-line managers beyond expediting parts, tracking time and attendance, and disciplining workers to make their numbers. In fact, being both part of management and in direct contact with production operators on the shop floor puts them in a unique position as agents of change.

This is why TPS puts them in charge of smaller groups, with the expectation that they will spend time leading improvement projects and supporting the professional growth of their teams. Most IT groups pay more attention to the executive suite than to the shop floor, where, in particular, you are not just interacting with people through screens but also with machines through their controllers. This requires a different set of IT skills, and the article says that Toyota partnered with Rockwell Automation for this purpose.

See on mhlnews.com

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May 1 2013

GE and workers see different paths to improving productivity | GoErie.com

See on Scoop.it – lean manufacturing

Talk to a couple dozen past and present employees at GE Transportation and a pattern emerges.Many share a common view that the productivity the company wants to improve was a casualty of lean manufacturing and a reduction in an incentive-pay program that paid employees more as they produced more. But for reasons of its own — including concerns about safety and quality — the company isn’t looking to expand a program that was deliberately downsized.

Productivity, a measure of how much an employee produces during a given period of time, was on the table last week and will be again this week as negotiations continue between GE Transportation and Local 506 of the United Electrical, Radio & Machine Workers.

Michel Baudin‘s insight:

It is odd that the unions that fought so hard to eliminate piece rates in the 20th century should come out in favor of it now. Economically, piece rates, or volume rates make sense for manually shoveling dirt, but not much else.

See on www.goerie.com

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May 1 2013

How do I analyze historical consumption for 13,000 items?

Supply chain consultant Hadas Gur asked the following question:

I have data of demands for 13000 SKUs (consumptions from the last 5 years). 6000 of the observations are zeros.  I can’t recognize the distribution of the data . I have tried the q-q plot to find a match to any known distribution. What can I do in this case if I want to find the reorder point? Is it ok to use the reorder point formula which is in your post “Safety Stocks : Beware of Formulas” even though the distribution is not normal?

You do not give a context. Are those SKUs components supplied to a manufacturing company or retail items on supermarket shelves? The demand patterns may be radically different. In retail, for example, the demand for milk is the sum of the quantities bought by a large number of individual consumers acting independently, and the normal distribution is a likely fit. On the other hand, if you are supplying a model-specific part to a car manufacturer, it is unlikely to fit.

Do not try to apply the same approach to all 13,000 SKUs! For example, reorder point makes no senses for the 6,000 items that have had no demand in the past 5 years. You would want to investigate whether they should still be in the catalog and, if so, they are strangers and you need to organize to make or buy them when an order arrives.

For the others, I would suggest you explore the data rather than focus on fitting a distribution, starting with a Runner/Repeater/Stranger analysis. Then, starting with runners, investigate trends and seasonal variations. For repeaters, I would investigate ways to group them into families that make sense for what you are trying to do.

Do not use only the data. In order to understand what is possible, you need to visit the warehouses or distribution centers and understand how physical distribution distribution is organized, and the people involved.

Then consider a range of approaches for different items and item families, including just-in-sequence, Kanban, two-bin, reorder point, vendor-managed inventory, consignment, etc.  Examine how these approaches would have performed with the consumption pattern of the last 5 years. You can also simulate future demand.

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Apr 26 2013

Improving operations: How far can you go with common sense?

In the Lean Six Sigma discussion group on LinkedIn, Brian P. Sheets argues that ” the alphabet soup of acronyms describing the multitude of process improvement & management methodologies that have come and gone over the last 50 years […]  is just plain, old, common sense.”  The list he targets in this statement is Six Sigma, TQM, BPR, BPM, TOC, MBO, Kaizen, and Gemba Kaizen, and overlap the one I discussed earlier in this blog. To support his argument, he invokes not only the great work done in US manufacturing during World War II without these acronyms, but goes back all the way to Egypt’s pyramids.

I see things differently. The old days were not so great and we have learned a few new tricks in the 68 years since the end of World War II, as a result of which we are not only able to make better products, but we also use fewer people to make them, at a higher quality. There definitely is something to some of the ideas that have been packaged under various brands in that time, and it is definitely more than common sense.

What is common sense anyway? The common sense approach to a problem is the solution that would be chosen by an intelligent person without any specialized knowledge. It is what you resort to when faced with a new situation you are unprepared for, like the businessman played by Anthony Hopkins in The Edge, who is stranded in the Alaskan wilderness by a plane crash and has to kill a grizzly.

Once you have been working on something for a few years, however, you are supposed to have acquired specialized knowledge of it, and apply solutions that are beyond common sense. And these solutions are counter-intuitive to anyone without this experience. Lean manufacturing concepts like one-piece flow or heijunka are bewildering to beginners, because they have nothing to go by beyond their common sense.

“Common sense,” Descartes said, “is the most fairly distributed thing in the world, for each one thinks he is so well-endowed with it that even those who are hardest to satisfy in all other matters are not in the habit of desiring more of it than they already have.” After that, he proceeds to explain a method “to seek truth in science” and presents three applications of this method, the best known being analytic geometry. All of this is far beyond common sense.

For all these reasons, I am not too fond of invoking common sense in support of any new concept. What you really need is a rationale, and experimental proof through a small scale implementation.

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