Statistical Process Control for Monitoring Nonlinear Profiles: A Six Sigma Project on Curing Process

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 article 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.

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