Transfer Function Modeling of Processes With Dynamic Inputs

Article

West, David; Dellana, Scott; Jarrett, Jeffrey   (2002, ASQ)   East Carolina University, Greenville, NC; The University of Rhode Island, Kingston, RI

Journal of Quality Technology    Vol. 34    No. 3
QICID: 18233    July 2002    pp. 315-326
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Article Abstract

[This abstract is based on the authors' abstract.] In industrial process control applications, time series structures often complicate efforts to accurately position control chart limits. Autoregressive integrated moving average (ARIMA) modeling and other control charting methods have been recommended for monitoring process data with a time series structure. However, if assignable causes of variation exist in the process data used to fit the time series model, estimates of ARIMA model parameters may not be reliable and control limits may be misplaced. A transfer function model is considered to identify assignable causes of variation and to model dynamic relationships between process inputs and outputs. The model is applied to a dynamic wastewater treatment process to monitor biochemical oxygen demand output.

Keywords

Input/Output Analysis,Time series,Statistical process control (SPC)


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