Mohd Zain, Azlan and Haron, Habibollah and Sharif, Safian (2009) Review of ANN technique for modeling surface roughness performance measure in machining process. In: Proceedings - 2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009. Institute of Electrical and Electronics Engineers, New York, 35 -39. ISBN 978-076953648-4
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Official URL: http://dx.doi.org/10.1109/AMS.2009.78
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.
|Item Type:||Book Section|
|Additional Information:||2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009; Bandung, Bali; 25 May 2009 through 26 May 2009|
|Uncontrolled Keywords:||ANN, machining, modeling, surface roughness|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
T Technology > TJ Mechanical engineering and machinery
|Divisions:||Computer Science and Information System|
|Deposited By:||Liza Porijo|
|Deposited On:||18 Jul 2011 08:03|
|Last Modified:||18 Jul 2011 08:03|
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