Using On-Line Sensors in Statistical Process Control
提出两阶段程序，将在线传感器与控制图结合，在传感器预警后抽样检测，以改进统计过程控制决策，并给出确定样本量、控制限和预警规则的数学模型。
As manufacturing technology moves toward more computerized automation, statistical process control (SPC) techniques must adapt to keep pace with the new environment and take advantage of the development in automated on-line sensors. In this paper, a two-phase procedure is proposed for combining an on-line sensor and a control chart to improve statistical process control decisions. In phase 1 of this procedure, a production process is monitored continually by a sensor. When a sensor warning signal is observed, phase 2 takes place: A sample of items is drawn from the process and inspected. If the sample mean is outside the predetermined control limits, the process is stopped, and a search is initiated to determine the actual process status for possible necessary adjustment. If the sample mean is within the control limits, the process continues. A mathematical model is formulated for jointly determining the sample size and the control limit of the control chart and a decision rule for sending out sensor warning signals. The model is based on the assumption that there is only a weak relationship between the sensor measurement and the process condition. A solution algorithm based on a numerical search is developed. A numerical example is used to show the advantage of the proposed model over the models based separately on the sensor and the control chart, and a sensitivity analysis is used to show the effects of several important model parameters on the optimal solution.