This paper presents a supervisory generalized predictive control (GPC) by combining GPC with statistical process control (SPC) for the control of the thin film deposition process. In the supervised GPC, the deposition process is described as an ARMAX model for each production run and GPC is applied to the in situ thickness-sensing data for thickness control. Supervisory strategies, developed from SPC techniques, are used to monitor process changes and estimate the disturbance magnitudes during production. Based on the SPC monitoring results, different supervisory strategies are used to revise the disturbance models and the control law in the GPC to achieve a satisfactory control performance. A case study is provided to demonstrate the developed methodology.

Issue Section:
Technical Papers
Keywords:
statistical process control, process monitoring, predictive control, thin films, coatings, thickness control, ARMAX model, predictive control, statistical process control, supervisory strategies, thin film deposition
Topics:
Predictive control, Statistical process control, Thin films, Errors, Modeling
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