Statistical process control for monitoring nonlinear profiles: a six sigma project on curing process


Show simple item record Chang, Shing I. Tsai, Tzong-Ru Lin, Dennis K. J. Chou, Shih-Hsiung Lin, Yu-Siang 2012-07-27T20:10:40Z 2012-07-27T20:10:40Z 2012-07-27
dc.description.abstract Curing duration and target temperature are the most critical process parameters for high- pressure hose products. The air temperature collected in the curing chamber is represented in the form of a profile. A proper statistical process control (SPC) implementation needs to consider both numeric as well as profile quality characteristics. This paper describes a successful six sigma project in the context of statistical engineering for integrating SPC, a statistical method, to the existing practice of engineering process control (EPC) according to science. A case study on a real production curing process is thoroughly investigated. It is shown that the new findings could potentially result in significant energy savings. The solutions provided in this study can be generalized into other curing processes and applications subjected to both EPC and SPC. en_US
dc.relation.uri en_US
dc.rights This is an electronic version of an article published in Quality Engineering, 24(2), 251-263. Quality Engineering is available online at: en_US
dc.subject Autoclave en_US
dc.subject Bi-plot chart en_US
dc.subject DMAIC en_US
dc.subject Hotelling T2 chart en_US
dc.subject Profile analysis en_US
dc.subject Hotelling T-squared chart en_US
dc.title Statistical process control for monitoring nonlinear profiles: a six sigma project on curing process en_US
dc.type Article (author version) en_US 2012 en_US
dc.citation.doi doi:10.1080/08982112.2012.641149 en_US
dc.citation.epage 263 en_US
dc.citation.issue 2 en_US
dc.citation.jtitle Quality Engineering en_US
dc.citation.spage 251 en_US
dc.citation.volume 24 en_US
dc.contributor.authoreid changs en_US
dc.contributor.authoreid cls3415 en_US

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