As you think about your organization’s manufacturing quality efforts—what you’ve overcome and what you hope to accomplish in the future—there is something you need to know.
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You: What? Who? Me?
Me: Yes, you. No matter how long you’ve been playing this game (and I know many of you have been playing it as long as I have), you find that there are many pitfalls to implementing a statistical process control (SPC) system.
I’ve been doing this for about 30 years, and I’ve worked with and witnessed hundreds of SPC implementations. Many have been very successful, virtually transforming plants and corporate cultures. A few have been less than successful. And many—most, actually—occupy the murky middle ground between success and failure. These deployments are usually characterized by an interesting mix of localized support and excitement, coupled with an undercurrent of corporate indifference.
You: OK, I’m interested. Go on.
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Comments
SPC Mistakes
Everyone can and should learn and understand SPC. The problem is, thanks to Six Sigma Stupidity, most people have no idea of the fundamentals. SPC has been turned into such a mess it appears difficult.The number 1 problem is that people do not understand that control charts work for ANY distribution. They do NOT depend on normality. You should NEVER normalize data.
As Dr Wheeler points out, you don't need rules other than Rule #1. You don't even need p, pn, c and U charts ... just use the Swiss Army knife XmR. You don't need a computer to draw and use control charts.Anyone who follows Dr Wheeler's recommendations should have little trouble.
https://www.linkedin.com/pulse/six-sigma-psychology-part-2-tony-burns/
https://www.linkedin.com/pulse/blame-mr-bill-smith-tony-burns/
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