Excellent service quality and high customer satisfaction is the key issue and challenge for today's service industry. Customer perception (satisfaction) and customer expectation (importance) determines the service quality performance. Questionnaires help service providers to realize their service quality performance, and the weighted average of customer satisfaction and the associated variance are commonly used indices reflecting customer expectation and customer percep tion. To evaluate, effectively and efficiently, service quality performance, this paper aims to portray customer expectation and customer satisfaction by assuming that the evaluation scales for expectation and satisfaction are between 0 and 1. This paper defines a customer satisfaction index and a customer expectation index based on the two parameters of a beta distribution, and the unbiased estimators for these two indices are provided. A standardized Service Quality Performance Matrix helps managers realize the service quality performance for important service elements with respect to the locations of the satisfaction index and the expectation index on the Service Quality Performance Matrix to propose adequate service quality improvement plans and strategies.

Process capability indices (PCIs) are powerful means of studying the process ability for manufacturing a product that meets specifications. Several capability indices including C p , C pu , C pl and C pk have been widely used in manufacturing industry to provide common quantitative measures on process potential and performance. The formulas for these indices are easily understood and can be straightforwardly applied. However, those process capability indices are inappropriate for asymmetric tolerances and could not be applied to evaluate multiprocess products. Based on C p , C pu , C pl and C pk , this research aims to develop one process capability analysis chart (PCAC) for precisely measuring an entire product composed of symmetric tolerances, asymmetric tolerances, larger-the-better and smaller-the-better characteristics. The process capability analysis chart evaluates the capabilities of multi-process products and provides chances for continuous improvement on the manufacturing process.

The electronics industry has heavily prioritized enhancing the quality, lifetime and conforming rate (conforming to specifications) of electronic components. Various methods have been developed for assessing quality performance. In practice, process capability indices (PCIs) are used as a means of measuring process potential and performance. Moreover, most PCIs have been developed or investigated under the assumption that electronic components have a lifetime with a normal distribution. However, PCIs for non‐normal distributions have seldom been discussed. Nevertheless, the lifetime of electronic components generally may possess an exponential, gamma or Weibull distribution and so forth. Under an exponential distribution, some properties of the PCIs and their estimators differ from those in a normal distribution. To utilize the PCIs more reasonably and accurately in assessing the lifetime performance of electronic components, this study constructs a uniformly minimum variance unbiased (UMVU) estimator of their lifetime performance index under an exponential distribution. The UMVU estimator of the lifetime performance index is then utilized to develop the hypothesis testing procedure. The purchasers can then employ the testing procedure to determine whether the lifetime of the electronic components adheres to the required level. Manufacturers can also utilize this procedure to enhance process capability.