A neural network-based control scheme for monitoring start-up processes and short runs

作者：Garjani M^*; Noorossana R; Saghaei A

来源：International Journal of Advanced Manufacturing Technology, 2010, 51(9-12): 1023-1032.

DOI：10.1007/s00170-010-2672-9

• Statistical process control
• Artificial neural networks
• Short runs
• Q control charts
• Run length distribution

Traditional control charts are commonly used as a monitoring tool in long-run processes. However, such control charts, due to the need for phase I analysis, are not suitable for start-up processes or short runs. Q control charts have been developed to help monitor start-up processes and short runs. In this article, a back propagation network is proposed for detecting a mean shift in start-up processes and short runs. In-control run length distribution of the control scheme is estimated using simulation study to provide information about the possibility of a false alarm within a specified number of observations. Performance of the proposed control scheme is assessed using different performance measures. It is shown numerically that the proposed control scheme outperforms the CUSUM of Q charts in detecting small to moderate mean shifts.

• 出版日期2010-12