Title :
Training artificial neural networks for statistical process control
Author :
Jacobs, Derya A. ; Luke, Stephen R.
Author_Institution :
Dept. of Eng. Manage., Old Dominion Univ., Norfolk, VA, USA
Abstract :
The use of artificial neural networks (ANNs) in statistical process control (SPC) is studied. An ANN is developed in order to determine the status of a process. The objective of the network is to be able to classify the incoming X-Bar values by indicating the status of the process with the appropriate rule. The network is presented with ten values which can be out of control, as described by any of the selected rules. The resulting output is the representation of that particular rule. Several simulations are performed. The features of ANNs which make them desirable for SPC applications are summarized
Keywords :
expert systems; learning (artificial intelligence); manufacturing computer control; neural nets; statistical process control; ANN; SPC; X-Bar Shewhart charts; artificial neural networks; expert systems; manufacturing; simulations; statistical process control; training; Artificial neural networks; Computer aided manufacturing; Control charts; Diagnostic expert systems; Humans; Jacobian matrices; Management training; Manufacturing processes; Process control; Signal processing;
Conference_Titel :
University/Government/Industry Microelectronics Symposium, 1993., Proceedings of the Tenth Biennial
Conference_Location :
Research Triangle Park, NC
Print_ISBN :
0-7803-0990-1
DOI :
10.1109/UGIM.1993.297059
