Process yield is the most common criterion used in the manufacturing industry for measuring process performance. A measurement index, called Spk, has been proposed to calculate the yield for normal processes. The measurement index pk establishes the relationship between the manufacturing specifications and the actual process performance, which provides an exact measure on process yield. Unfortunately, the sampling distribution of the estimated pk is mathematically intractable. Therefore, process performance testing cannot be performed. In this paper; we consider a normal approximation to the distribution of the estimated pk, and investigate its accuracy computationally. We compare the critical values calculated from the approximate distribution with those obtained using the standard simulation technique, for various commonly used quality requirements. Extensive computational results are provided and analyzed. The investigation is useful to the practitioners for making decisions in testing process performance based on the yield.
Quality & Quantity – Springer Journals
Published: Oct 18, 2004
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