Abstract
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 CL is a popular means to assess the performance and potential of their processes, where L is the lower specification limit. This study will apply the large‐sample theory to construct a maximum likelihood estimator (MLE) of CL with the progressive first‐failure‐censored sampling plan under the Weibull distribution. The MLE of CL is then utilized to develop a new hypothesis testing procedure in the condition of known L.
Highlights
Managing and measuring the business operational process is widely seen as a means of ensuring business survival through reduced time to market, increased quality, and reduced costs
Process capability analysis has been widely applied in the field of quality control to monitor the performance of industrial processes
The lifetime performance index CL is utilized to measure product quality with the Weibull distribution based on the progressive first-failure-censored sampling plan
Summary
Managing and measuring the business operational process is widely seen as a means of ensuring business survival through reduced time to market, increased quality, and reduced costs. The lifetime performance index CL is utilized to measure product quality with the Weibull distribution based on the progressive first-failure-censored sampling plan. Progressive type II right censoring is a useful scheme in which a specific fraction of individuals at risk may be removed from the experiment at each of several ordered failure times see Fernandez. Under the assumption of Weibull distribution, the main aim of this paper will apply the large-sample theory to construct an MLE of CL with the progressive first-failure-censored.
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