Review of ANN technique for modeling surface roughness performance measure in machining process
The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as Statistical Regression technique, explicit models are developed that required comple...
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| Main Authors: | , , |
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| Format: | Book Section |
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Institute of Electrical and Electronics Engineers
2009
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| Subjects: | |
| Online Access: | http://eprints.utm.my/13089/ http://eprints.utm.my/13089/ http://eprints.utm.my/13089/ |
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| Summary: | The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as Statistical Regression technique, explicit models are developed that required complex physical understanding of the modeling process. With non conventional approaches or Artificial Intelligence techniques such as Artificial Neural Network, Fuzzy Logic and Genetic Algorithm based modeling, implicit model are created within the weight matrices of the net, rules and genes that is easier to be implemented. With the focus on surface roughness performance measure, this paper outlines and discusses the concept, application, abilities and limitations of Artificial Neural Network in the machining process modeling. Subsequently the future trend of Artificial Neural Network in modeling machining process is reported. |
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