Skip to main content
Article thumbnail
Location of Repository

Application of full factorial experiment in designing an ANN-based control chart pattern recognizer

By Ibrahim Masood and Adnan Hassan

Abstract

Automated recognition of control chart patterns for monitoring and diagnosing process quality has been an active area of research since the last 20 years. An artificial neural network (ANN) based models with back-propagation algorithm was known to have resulted the promising recognition accuracy. However, the performance of an ANN depends on a proper selection of the design parameters. In this paper, full factorial design of experiment (DOE) was utilized in investigating several parameters that influence the recognition accuracy of an ANN. This systematic method provided an optimal ANN design with satisfied recognition accuracy

Topics: T Technology (General)
Year: 2008
OAI identifier: oai:eprints.uthm.edu.my:2221

Suggested articles


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.