USING ONLINE SENSORS IN STATISTICAL PROCESS-CONTROL

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 auto mated on-line sensors. In this paper, a two-phase procedure is propose d for combining an on-line sensor and a control chart to improve stati stical process control decisions. In phase 1 of this procedure, a prod uction process is monitored continually by a sensor. When a sensor war ning signal is observed, phase 2 takes place: A sample of items is dra wn from the process and inspected. If the sample mean is outside the p redetermined control limits, the process is stopped, and a search is i nitiated to determine the actual process status for possible necessary adjustment. If the sample mean is within the control limits, the proc ess continues. A mathematical model is formulated for jointly determin ing the sample size and the control limit of the control chart and a d ecision rule for sending out sensor warning signals. The model is base d on the assumption that there is only a weak relationship between the sensor measurement and the process condition. A solution algorithm ba sed on a numerical search is developed. A numerical example is used to show the advantage of the proposed model over the models based separa tely on the sensor and the control chart, and a sensitivity analysis i s used to show the effects of several important model parameters on th e optimal solution.