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Designing the most cost-effective process target using regression analysis: a case study

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image of Process Control and Quality

In many manufacturing settings, the determination of the optimum process target (mean) is one of the most important decision-making problems since it directly affects a process defective rate, material cost, scrap or rework cost, and the loss to the customer due to the deviation of a product performance from the customer-identified product target value. A quality loss function approach using conventional quality loss functions, such as step-loss and Taguchi loss functions, has been extensively used to determine the optimum process target mainly due to a mathematical convenience. When historical data concerning the costs associated with product performance are available, a quality loss function using a well-established statistical method, such as regression analysis, may be a more practical alternative procedure. This article shows how the regression-based quality loss function is developed and efficiently employed to determine the optimum process target. A case study is presented.

10.1163/156856601753392003
/content/journals/10.1163/156856601753392003
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/content/journals/10.1163/156856601753392003
2001-11-01
2016-12-07

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