Integrating the use of statistical process control (SPC) with engineering process control (EPC) enhances the results of industrial processes. Often it is assumed that disturbances in an industrial process may be immediately found and removed. It is believed that these disturbances can be removed more quickly when one observes the triggered out-of-control signal of SPC schemes. But this detection, removal, and correction of the problems in the process is seldom quick or easy. Integrating industrial standard schemes of SPC and EPC, this study aims to detect and identify a disturbance and begin an adaptive control mode to compensate for the disturbances. Superior process control can be achieved through the application of the proposed integrated SPC and EPC schemes discussed in this paper.

The objective of our research is to develope for process manufacturing an inferential quality control system that combines theoretical and experimental knowledge of physical processes with the judgement and experience of experts in plant operations. In this paper, we propose a quality process model, and apply the model to the continuous electrical resistance annealing of copper wire. Theory is used to develop the relationship between the control variables and measurable characteristics of the process, and experimental information is used to develop the relationships that link the process characteristics to the quality characteristics specified by the customer. The approach is illustrated by the manufacturing process, the continuous annealing of copper wire.