May 3 2013
See on Scoop.it – lean manufacturing
The use of Lean by Boeing engineers helps the company reach its goal of providing products that meet and exceed expectations for the U.S. Army.
The article discusses everything except manufacturing.
See on www.onlineamd.com
May 2 2013
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…”
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
May 1 2013
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.
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
May 1 2013
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.
May 3 2013
Lean Survival Strategies in the Textile Industry | Chain Reactions | Industry Week
See on Scoop.it – lean manufacturing
“The traditional lean approach […] omits the customer from the scenario—a rather glaring omission. The other approach, though, is extended lean, which goes beyond the plant level to include the customer and other supply chain partners. ‘Traditional lean works on processes within the plant,’ Lail says, ‘whereas extended lean connects the entire supply chain.’”
I am sure many others familiar with TPS and Lean will find the notion of a Lean approach that “omits the customer” as objectionable as I do. The gist of the article is that textile manufacturer Valdese Weavers survived by ignoring manufacturing and focusing instead on moving full truckloads.
This puts the Valdese Weavers experience in direct contradiction with that of companies that have seen the pursuit of transportation efficiency degrade ratther than enhance their overall performance, as documented, for example, in the work of Hau Lee.
See on www.industryweek.com
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By Michel Baudin • Press clippings 0 • Tags: Lean manufacturing, Manufacturing, Supply chain, Textile industry