Abstract
Taguchi et al. (1989) proposed an effective on-line process control policy by minimizing the expected quality cost per item in a production process. The goal is to continually improve or regulate the process so that the quality characteristic stays as close to the target value as possible. Although Taguchi's method is easy to implement, it produces higher expected quality cost than other methods under certain cost and model structures. We propose an empirical procedure in this paper since the analytical solution of control scheme for stochastic models other than the integrated moving average process, IMA(1,1), is not available. The procedure combines the phase of modeling the measurements of quality characteristic by an ARIMA process, and the phase of obtaining a control scheme based on simulation. The performance of the empirical procedure is examined by comparing favorably its expected quality costs with that of Taguchi's procedure.
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