X-bar andRcontrol chart interpretation using neural computing
作者:
A. E. SMITH,
期刊:
International Journal of Production Research
(Taylor Available online 1994)
卷期:
Volume 32,
issue 2
页码: 309-320
ISSN:0020-7543
年代: 1994
DOI:10.1080/00207549408956935
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This paper formulates Shewhart mean (X-bar) and range (R) control charts for diagnosis and interpretation by artificial neural networks. Neural networks are trained to discriminate between samples Prom probability distributions considered within control limits and those which have shifted in both location and variance. Neural networks are also trained to recognize samples and to predict future points from processes which exhibit long-term or cyclical drift. The advantages and disadvantages of neural control charts compared with traditional statistical process control are discussed.
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