A Novel Approach for Evaluating High-Quality Process Performance Based on the Quality-Yield Index  
Author Chien-Wei Wu


Co-Author(s) Armin Darmawan; Meng-Tzu Lin


Abstract In this research, a novel approach, called generalized confidence interval (GCI), is applied using the idea of generalized pivotal quantities to construct the confidence interval for the Q-yield index. To examine the performance of the proposed approach, a series of simulations are conducted and also compared with the existing method and three bootstrap methods in terms of coverage rate (CR) and the average value of lower confidence bound (LCB). Based on the findings, it can be concluded that the proposed GCI approach provides the most accurate results for constructing the LCB of the quality yield index. The proposed approach is therefore suggested in realworld scenarios to explore and evaluate process performance using the Q-yield index for the customer's high-quality requirement.


Keywords Generalized pivotal quantitiy; Coverage rate; Process yield; Quality loss function; Quality assurance
    Article #:  DSBFI23-121
Proceedings of 2nd ISSAT International Conference on Data Science in Business, Finance and Industry
January 8-10, 2023 - Da Nang, Vietnam