Statistical Process Control for Monitoring Nonlinear Profiles: A Six Sigma Project on Curing Process
- Quality Engineering
- April 2012
- Volume 24 Issue 2
- pp. 251-263
- Chang, Shing I.; Tsai, Tzong-Ru; Lin, Dennis K. J.; Chou, Shih-Hsiung; Lin, Yu-Siang
- Kansas State University, Manhattan, KA, Tamkang University, New Taipei City, Taiwan, Pennsylvania State University,University Park, PA, National Taiwan University of Science and Technology, Taipei, Taiwan
Curing duration and target temperature are the most criticalprocess parameters for high-pressure hose products. The air temperaturecollected in the curing chamber is represented in the form of a profile. Aproper statistical process control (SPC) implementation needs to considerboth numeric as well as profile quality characteristics. This article describesa successful Six Sigma project in the context of statistical engineering forintegrating SPC, a statistical method, to the existing practice of engineeringprocess control (EPC) according to science. A case study on a real productioncuring process is thoroughly investigated. It is shown that thenew findings could potentially result in significant energy savings. The solutionsprovided in this study can be generalized into other curing processesand applications subjected to both EPC and SPC.