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

fYear

1993

fDate

18-19 May 1993

Firstpage

235

Lastpage

239

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;

fLanguage

English

Publisher

ieee

Conference_Titel

University/Government/Industry Microelectronics Symposium, 1993., Proceedings of the Tenth Biennial

Conference_Location

Research Triangle Park, NC

ISSN

0749-6877

Print_ISBN

0-7803-0990-1

Type

conf

DOI

10.1109/UGIM.1993.297059

Filename

297059