Optimal process adjustment by integrating production data and design of experiments
Article first published online: 15 JUL 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Quality and Reliability Engineering International
Volume 27, Issue 3, pages 327–336, April 2011
How to Cite
Li, J., Xie, H. and Jin, J. (2011), Optimal process adjustment by integrating production data and design of experiments. Qual. Reliab. Engng. Int., 27: 327–336. doi: 10.1002/qre.1123
- Issue published online: 24 MAR 2011
- Article first published online: 15 JUL 2010
- process adjustment;
- design of experiments;
- sequential hypothesis testing
This paper proposes a method to improve the process model estimation based on limited experimental data by making use of abundant production data and to achieve the optimal process adjustment based on the improved process model. The proposed method is called an Estimation-adjustment (EA) method. Furthermore, this paper proves three properties associated with the EA, which guarantee the feasibility and effectiveness of using EA for integrating production and experimental data for optimal process adjustment. Also, the paper develops a sequential hypothesis testing procedure for implementing the EA. The properties and implementation of the EA are demonstrated in a cotton spinning process. Copyright © 2010 John Wiley & Sons, Ltd.