標題: Estimating process yield based on S-pk for multiple samples
作者: Pearn, W. L.
Cheng, Ya Ching
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: process yield;multiple samples;process capability
公開日期: 1-Jan-2007
摘要: Boyles ( 1994) proposed a process measurement called S-pk, which provides an exact measure on the process yield for normal processes. Lee et al. ( 2002) considered an asymptotic distribution for the natural estimator of Spk under a single sample. In this paper, we extend the results for the case of multiple samples. We first compare the yield index S-pk with the most commonly used index, C-pk, and review some results of S-pk under a single sample. Next, we derive the sampling distribution for the estimator (S) over cap'(pk) of S-pk under multiple samples and find that for the same S-pk, the variance of (S) over cap'(pk) would be largest when the process mean is on the centre of specification limits. We calculate the lower bounds for various commonly used quality requirements under the situation with the largest variance of (S) over cap'(pk) for assurance purposes. To assess the normally approximated distribution of (S) over cap'(pk), we simulate with 10 000 replications to generate 10 000 estimates of (S) over cap'(pk), calculate their lower bounds, compare with the real (preset) S-pk and check the actual type I error. We also compute how many sample sizes are required for the normal approximation to converge to S-pk within a designated accuracy. Then, we present a real-world application of the one-cell rechargeable Li-ion battery packs, to illustrate how we apply the lower bounds to actual data collected from factories.
URI: http://dx.doi.org/10.1080/00207540600600122
http://hdl.handle.net/11536/11280
ISSN: 0020-7543
DOI: 10.1080/00207540600600122
期刊: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume: 45
Issue: 1
起始頁: 49
結束頁: 64
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