Inference for the process performance index of products on the basis of power-normal distribution
學年 110
學期 1
出版(發表)日期 2021-12-23
作品名稱 Inference for the process performance index of products on the basis of power-normal distribution
作品名稱(其他語言)
著者 J. Zhu; H Xin; C Zheng; Tzong-Ru Tsai
單位
出版者
著錄名稱、卷期、頁數 Mathematics 10(1), p.35
摘要 The process performance index (PPI) can be a simple metric to connect the conforming rate of products. The properties of the PPI have been well studied for the normal distribution and other widely used lifetime distributions, such as the Weibull, Gamma, and Pareto distributions. Assume that the quality characteristic of product follows power-normal distribution. Statistical inference procedures for the PPI are established. The maximum likelihood estimation method for the model parameters and PPI is investigated and the exact Fisher information matrix is derived. We discuss the drawbacks of using the exact Fisher information matrix to obtain the confidence interval of the model parameters. The parametric bootstrap percentile and bootstrap bias-corrected percentile methods are proposed to obtain approximate confidence intervals for the model parameters and PPI. Monte Carlo simulations are conducted to evaluate the performance of the proposed methods. One example about the flow width of the resist in the hard-bake process is used for illustration.
關鍵字 bootstrap methods;maximum likelihood estimation;Monte Carlo simulation;process performance index;power-normal distribution;quality control
語言 en_US
ISSN 2227-7390
期刊性質 國外
收錄於 SCI Scopus
產學合作
通訊作者
審稿制度
國別 CHE
公開徵稿
出版型式 ,電子版
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