A statistical process control procedure with adjustments and monitoring

Statistical process control(SPC) and engineering process control(EPC) are based on di rectangle erent strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been needs for an integrated process control(IPC) procedure which combines the two strategies. This paper considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The disturbance model under consideration is an IMA(0,1,1) process with a step shift. The EPC part of the scheme adjusts the process whenever the predicted deviation exceeds bounds, which is referred to a bounded adjustment scheme. The SPC part of the scheme uses the exponentially weighted moving average of forecast errors to detect special causes. The e ciency of the control procedure is measured as the expected cost per unit time. Optimal control parameters of the IPC and adjustment-only(AO) procedures are obtained and compared to each other for a set of process and cost parameters. Also the IPC procedure is compared to the AO procedure for various cases of adjustment e rectangle ects under the presence of a special cause. It was shown that the IPC procedure is useful in improving the ec ciency of the control procedure.