Optimal process capability analysis for process design

Abstract

Conventional process capability analysis is used to measure and control the quality level of a production process in real exercises for on-line quality management. There has been a deficiency in this type of management; namely, the defects which occur in the production process are only passively detected and modified afterwards. Additionally, conventional process capability expression has difficulty distinguishing between alternatives for process selection among possible candidates before process realisation. There is, therefore, considerable motivation for developing a process capability expression which can be used to evaluate alternatives at the beginning of the process design, i.e., off-line application. The conventional C_pm expression is built up by measuring mean deviation and process variances for on-line application. However, if C_pm is used for the process capability analysis for process design, an erroneous C_pm value is found and an inappropriate process design is ended. Thus, the proposed process capability expression revised from the conventional C_pm in consideration of the balance between tolerance cost and quality loss has been developed. This development is the main contribution of this research and, with this development, the appropriate mean and tolerance values can be determined simultaneously prior to the real production process so as to maximise the proposed process capability value. The production is then processed with the pre-determined mean and tolerance values in a real production process. The expectation after process realisation is that the produced responses will be the best of all the alternatives in terms of quality and cost, and that the process capability value obtained after the real production process will be close to the proposed process capability value maximised prior to the real production process.

Keywords:

• process capability analysis
• process mean
• process tolerance
• quality loss
• tolerance cost
• process design

Acknowledgments

This research was carried out in the Design, Quality, and Productivity Laboratory (DQPL) at the Department of Industrial Engineering and Systems Management of Feng Chia University, Taichung, Taiwan, ROC, under grant no. 97-2221-E-035-058 supported by the National Science Council of the Republic of China. I would like to give thanks to my research assistants, Chien-Ping Chung, a Ph.D. student, and, Hsin-Hung Cheng, Cheng-Yun Chen, Po-Chiuan Lin, M.S. students at the I.E. Department.

I would also like to thank the positive suggestions from the editor and reviewers for improving this paper significantly. In particular, I would like to show my deep appreciation for the advice from my colleague.