NDLI: Recognition of quality control chart patterns based on back propagation neural network

Content Provider	IEEE Xplore Digital Library
Author	Bhattacharyya, B.K. Chakraborty, S.
Copyright Year	2009
Description	Author affiliation: Professor, Mechanical Engineering Department, Bengal Engineering & Science University, Shibpur, Howrah 711103 (Bhattacharyya, B.K.) \|\| Department of Production Engineering, Jadavpur University, Kolkata 700032 (Chakraborty, S.)
Abstract	In the off-line monitoring of the control characteristics of manufactured parts/products has usually been performed by establishing suitable quality control charts. The control charts as maintained would usually show various patterns and the analysis of such patterns would require human expertise so that suitable remedial actions can be taken. In the present paper, a maiden venture has to be taken to recognize various observable quality control chart patterns through the application of back propagation neural network technique. Various patterns like normal, cyclic, increasing/decreasing trend, upward/ downward shift etc. have been taken into consideration. Various known patterns have also been generated through the simulation and induction approach. The developed module has been tested and observed to be quite fast, accurate and flexible as it can be able to cope up with varying quality control chart patterns as encountered in real time manufacturing environment.
Starting Page	1124
Ending Page	1128
File Size	73478
Page Count	5
File Format	PDF
ISBN	9781424436712
DOI	10.1109/ICIEEM.2009.5344452
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Induction generators Humans Pattern recognition Neural Network Quality Control Charts Neural networks Quality control Control charts Back Propagation Manufacturing Process Disturbance Pattern analysis Monitoring Testing
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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