The air temperature often declines nonlinearly in the cool-down stage of a curing process. This nonlinear decline is correlated to the cosmetic quality of the high-pressure hose products. However, it is difficult to model nonlinear profiles for effective statistical process control. In this paper, a novel and simple monitoring procedure is proposed to monitor nonlinear air temperature profiles through a simple piecewise method. A general statistical model is built based on the statistics generated from crucial profile segments. An algorithm is developed to implement the proposed method.
