Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6421810 | Applied Mathematics and Computation | 2014 | 16 Pages |
Process capability analysis has been widely applied in the field of quality control to monitor the performance of industrial processes. In practice, lifetime performance index (or the larger-the-better process capability indices (PCIs)) CL is a popular means to assess the performance and potential of their processes, where L is the lower specification limit. Moreover, record values often arise in industrial stress testing, meteorological analysis, hydrology, seismology, athletic events, and other similar situations. In this study, a two-stage maximum likelihood estimation applied to estimate lifetime performance index CL of non-normal processes. Further, this study will apply data transformation technology to construct a maximum likelihood estimator (MLE) of CL under the Burr XII distribution with the upper record values. The MLE of CL is then utilized to develop a hypothesis testing procedure in the condition of known L. Finally, we give simulation study and two examples to illustrate the use of the testing procedure under given significance level α.