An improved approach for process performance evaluation with the consideration of process yield and quality loss

Abstract

In recent years, several process capability indices have received considerable research attention and increased usage in evaluating process performance and purchasing decisions in manufacturing industries. In particular, the third-generation capability index C_pmk is constructed by taking process yield and quality loss into consideration. Unfortunately, the sampling distribution of the estimated C_pmk is complicated, making the establishment of the exact confidence interval very difficult. Thus, this study applies the concept of the generalised pivotal quantity (GPQ) to derive the generalised confidence interval (GCI) for the index C_pmk. To examine the performance and the effectiveness of the GCI approach, a series of simulations is undertaken. Three types of bootstrap methods are also implemented and compared with the proposed GCI approach. The results reveal that the proposed GCI approach is superior to the three bootstrap methods since the obtained coverage rates are very close to the nominal confidence level in most of our studied cases even for small sample sizes. Therefore, this article recommends the GCI approach for evaluating process performance in real applications.

Keywords:

• confidence interval
• performance evaluation
• process yield
• quality loss

Acknowledgements

An earlier version of this paper was presented at the 2011 International Conference on Business and Information, Bangkok, Thailand. This work was partially supported by the National Science Council of Taiwan under Grant No. NSC 100-2628-E-007-035-MY3 and the Ministry of Education, Taiwan under Grant No. 100N2073E1.