Taguchi Loss Function and Capability Analysis |
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Jay Arthur
Copyright © 2011
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Good News - Bad News We recently sent out a QI Macros ezine about analyzing manufacturing performance data (link to rubber ezine). Many readers asked an interesting question: if my data fits between the specification limits of the histogram, but the control chart is unstable, is that good or bad? The Good News
In other words, you just got lucky. The process may not deliver on the customer's requirement next time. The question is: Does it matter? Taguchi wondered about this as well and did some research. The Taguchi Loss Function The loss isn't linear. Taguchi theorized that the loss is proportional to the square of the distance from the target value.
The parabolic curve describes the cost to society as the product moves away from the target value (center between LSL and USL). Warranty Example To determine the problem, five transmissions were selected at random from both the Japanese factory and the American factory. Then, they took them apart and measured all of the specifications.
Here's my point:
Stabilize your process Reduce Variation Reduce the Loss Make sure you're in charge of who your customers return to year after
year. Hitting the goal posts isn't good enough any more. You have to hit
the target value most of the time. Your customers will love you for it. © 2008 Jay Arthur, the KnowWare® Man, works with managers who want to plug the leaks in their cash flow. Hire Jay Arthur to train your staff in his one-day Lean Six Sigma Workshop! Contact Jay at (888) 468-1537, support@qimacros.com. Rights to reprint this article in company periodicals is freely given with the inclusion of the following tag line: "© 2008 Jay Arthur, the KnowWare® Man, (888) 468-1537, support@qimacros.com."
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