Marcellus, Richard L.
M.S. (Master of Science)
Department of Industrial Engineering
Process control; Bayesian statistical decision theory; Sampling (Statistics)
This study compares Cumulative Sum charts and Bayesian process control based on statistical quantities and minimal expected cost. The production process model and the procedure for the design of the two models is examined. Following the theoretical development, a numerical analysis is performed for both models. In the analysis, the optimal policies are determined and the sensitivity of the policies to changes in the model parameters is explored. Comparison between the two models is also made to see their relative performance. The results of the numerical study indicate that Cumulative Sum charts and Bayesian process control are about the same in detecting a lack of control and that optimal Cumulative Sum charts and optimal Bayesian process control are equally effective based on the minimum expected cost criterion.
Jasmani, Zahari, "A comparative study of cumulative Sum charts and Bayesian process control" (1992). Graduate Research Theses & Dissertations. 112.
viii, 106 pages
Northern Illinois University
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