Abstract
In practice, lifetime performance index CL has been a method commonly applied to the evaluation of quality performance. L is the upper or lower limit of the specification. The product lifetime distribution is mostly abnormal distribution. This study explored that the lifetime of commodities comes from exponential distribution. Complete data collection is the primary goal of analysis. However, the censoring type is one of the most commonly used methods due to considerations of manpower and material cost or the timeliness of product launch. This study adopted Type-II right censoring to find out the uniformly minimum variance unbiased (UMVU) estimator of the lifetime performance index CL and its probability density function. Afterward this study obtained the 100×(1-α)% confidence interval of the lifetime performance index CL as well as created the uniformly most powerful (UMP) test and the power of the test for the product lifetime performance index. Last, this study came up with a numerical example to demonstrate the suggested method as well as the application of the model.
Highlights
A number of studies related to process quality have pointed out that enhancing process quality can increase product lifetime as well as reduce the rate of process scrap and rework
This study explored that the lifetime of commodities comes from exponential distribution
Quite a few quality control engineers and experts in statistics have been dedicated to their studies on process capability indicators in terms of evaluation, analysis, and improvement [3, 31, 34,35]
Summary
A number of studies related to process quality have pointed out that enhancing process quality can increase product lifetime as well as reduce the rate of process scrap and rework. Under the assumption of exponentially complete data, the proposed lifetime performance index is presented as follows: CL. Construct interval estimators and hypothesis testing of the lifetime performance index based on progressive type II right-censored data. The product lifetime T comes from the exponential distribution with the mean λ, which is the probability density function (p.d.f.) of T as follows: fT (t). With the exponentially complete data, the lifetime performance index which Tong et al [28] suggested is denoted as Eq (1). Find the uniformly minimum-variance unbiased estimator (UMVUE) of the lifetime performance index.
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