Jul 6 2013
See on Scoop.it – lean manufacturing
In addition to the Tokyo headquarters visit I wrote about Friday, analysts and editors were also invited to Shanghai before leaving Asia to attend a plant tour of Canon’s Suzhou facility. The facility is located in the Jiangsu province, an hour and a half bus ride west of Shanghai.
See on whattheythink.com
Jul 3 2013
See on Scoop.it – lean manufacturing
Along with information about the history of Porsche’s turnaround since the early 1990s, this article contains strange statements about, for example, Lean Manufacturing being “Non-Quantitative,” which must make Ohno and Shingo turn over in their graves.
It also contains the doubtful statement that “the costs of warehousing excess inventory are a hundred of times more expensive than a delay caused by a missing part.” The point of Lean Logistics is not to trade-off full warehouses for shortages!
The real paradox of stock is that hoarding parts is ineffective at preventing shortages. The Lean Logistics approach is to keep inventories low but monitored with vigilance, and to respond quickly when floods, tsunamis, or earthquakes disrupt the supply chain.
The article further asserts that “Statistical Process Control” was central to Porsche’s effort, but gives not indication that it is even used. I don’t recall it being mentioned or seeing any trace of it in the Porsche plant in Leipzig two years ago.
See on cavqm.blogspot.co.uk
Jun 28 2013
See on Scoop.it – lean manufacturing
“Spanbild, a local market leader in the design, manufacture and construction of residential, rural and commercial buildings, today announced results of a project to apply lean principles throughout their manufacturing plants.”
A report on Lean implementation at a construction company in Christchurch, New Zealand, with government help.
See on www.voxy.co.nz
Jun 27 2013
Bodo Wiegand heads the Lean Management Institute, which is the German affiliate of the Lean Enterprise Institute. The following is a translation from German of the June, 2013 issue of his newsletter, Wiegand’s Watch:
When I was 12, my grandfather used to take me along on his “rounds,” as he called it.
We then had a foundry, where he did his “rounds” every day. Following my grandfather’s instructions to stay together, we walked hand in hand through the foundry operation itself, through mold and sand preparation, through the basement, etc. It took 1 ½ hours. Whenever something was wrong, he called Mr. Meier, Schmitz, or Schulte and asked “Why are there so many boxes?”, “Why is the cigarette there?” “Why is the aisle blocked?” “Why is the machine stopped?” “Why do we have a problem when casting?” When employees ran around without glasses or helmets, there was real trouble.
But even when something that should have been finished was not, or the clock was wrong, he intervened. At that time, I thought it capricious. Now I know how important personal protection gear is, and how important clocks and punctuality are.
His motto has always been: “If the clocks are wrong, no one can expect the people to be on time when you need them.With him there was absolutely no excuse for being late – but no one came late.
Back to the tour. He spoke with each supervisor, but only about problems – business but also human. Sometimes he stayed by a machine and listened. Then he called the head of maintenance, who usually said: “Yes, I’ve heard. We’ll take a look this week-end.” I was always deeply impressed and tried to listen . Yet I could hear nothing. I could hear any difference until my grandfather told me what I should hear and the difference with a machine that was working fine. Then I “heard” for the first and only time.
When became production manager in the forge, I remembered these tours and tried to think back to the individual details to hear and see. It took me a while before I could do this successfully.
The greatest praise I received in that position was from our maintenance manager, Mr. Hensing. When I called his attention to a noise that struck me as funny, he said: “It’s been a long time since anybody noticed.”
Well, why am I writing this? I have the feeling that we have forgotten how to hear and see, and to walk properly through the shop floor. I have a feeling that our supervisors and young managers have not learned to see, let alone hear or correctly make their rounds through operations, which implies seeing things and responding appropriately.
If I pass a cigarette butt on the ground or walk past a box with something in it that should not be there, then, as the saying goes: “What the boss tolerates or does not criticize is allowed”.
But if I want to change the mindset in my business and I am not an example, for example by tolerating waste, then I cannot expect employees to recognize and eliminate waste in their daily hard work. Therefore, I will not let this topic rest, and, to help, will make a virtual “Waste Walks” a centerpiece at the German Lean Summit of 24 to 26 October in Berlin to illustrate this topic from different angles.
Bodo Wiegand
Jul 9 2013
Betting on Lean, or …. Analytics versus Empowerment | Bill Waddell
See on Scoop.it – lean manufacturing
“Management is all about playing the odds. […] In operations, calculate lot sizes, generate forecasts and set quality standards with enough data and increasingly sophisticated algorithms and statistical methods and you will increase the chances of coming close enough. At least that is the theory, and the hope.
This is the basic premise of big data and ERP. With point of sale scanning, RFID, smart phones and all of the other data collecting technologies increasingly in use, the data to feed the engines is more and more available. The potential and the lure of the data driven, analytical approach to finding the center line and getting more decisions closer to correctness is growing.
The other approach is empowered people. Recognizing that management cannot be involved in every one of the individual customer interactions and operational, situational, tiny decisions, those calls are left to the people on the spot. They are expected to rely on their knowledge, understanding of company values and goals, and the information available to them in very real time to decide what to do.[…] The basic question is whether empowered people will get it right more often than big computer.”
In this article, Bill Waddell presents the data-driven approach to management decision making as contradictory to people empowerment. I do not see these as mutually exclusive.
In 1993, there was a group within Toyota’s logistics organization in the US that, based on weather data, thought that the Mississippi might flood the railroad routes used to ship parts from the Midwest to the NUMMI plant in California. Four days before the flood, they reserved all the trucking available in the Chicago area, for the daily cost of 6 minutes of production at NUMMI. When the flood hit, they were able to ship the parts by truck around the flood zone, and NUMMI didn’t miss a beat.
This is what a good data scientist does.
In Numbersense, Kaiser Fung points out that data analysis isn’t just about the data, but also about the assumptions people make about it. As an example, he points out the Republican polling fiasco of the 2012 election, as being due to the combination of flawed data collection and equally flawed modeling.
In other words, it’s not a computer that comes up with answers from data, but a human being, and the quality of these answers depends as much on the human analyst’s understanding of the underlying reality as it does on the ability to collect clicks from the web or transactions from point-of-sale systems.
Good data analysis does not require petabytes of data. In statistics, a small sample is 10 points; a large sample, 100 points. The difference matters because, with small samples, there are many convenient approximations that you cannot make. But 100 points is plenty for these approximations to work.
With millions of points, the tiniest wiggle in your data will show overwhelming significance in any statistical test, which means that these test are not much use in that context. To figure out what this tiny wiggle is telling you about reality, however, you still need to understand the world the data is coming from.
I don’t see an opposition between relying on people and relying on data, because, whether you realize it or not, you are never relying on data, only on people’s ability to make sense of it.
See on www.idatix.com
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By Michel Baudin • Blog clippings 0 • Tags: analytics, big data, data science, empowerment, Lean, statistics