The Application of Artificial Neural Network to Quality Control : Recognition of Nonrandom patterns
碩士 === 元智大學 === 工業工程研究所 === 83 === Control chart pattern recognition is an important aspect of statistical process control(SPC). The presence of unnatural patterns indicates that a process is affected by assignable causes, and corrective action...
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| Format: | Others |
| Language: | zh-TW |
| Online Access: | http://ndltd.ncl.edu.tw/handle/28873368578619879579 |
| Summary: | 碩士 === 元智大學 === 工業工程研究所 === 83 === Control chart pattern recognition is an important aspect of
statistical process control(SPC). The presence of
unnatural patterns indicates that a process is affected by
assignable causes, and corrective actions should be taken.
This paper describes one type of pattern recognition
procedure based on modural neural network architectures. The
pattern recognition procedure were developed to take the
advantage of the fact that a particular unnatural pattern is
often associated with a set of assignable causes. Th e
performances of the proposed pattern recognition procedure
were evaluated through Monte Carlo simulations on the basis of
appropriate performance measures. An extensive evaluation
indicates that the proposed pattern recognition procedure
could recgnize multiple unnatural patterns for which they
were trained. The results also indicat that modular network
performance is batter than that of backpropagation neural
network.
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