Artificial Intelligence Techniques for Machining Performance: a Review

This paper reviews the approaches of artificial neural network (ANN) on machining performance. ANN considered as a successful approach to modelling the machining process for predicting performance measures through the development of an expert system. An expert system is an interactive intelligence p...

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Main Authors:	M. M., Rahman, K., Kadirgama, M. M., Noor
Format:	Conference or Workshop Item
Language:	English
Published:	2010
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/1762/ http://umpir.ump.edu.my/id/eprint/1762/1/ARTIFICIAL_INTELLIGENCE_TECHNIQUES_FOR_MACHINING.pdf

id	ump-1762
recordtype	eprints
spelling	ump-17622018-01-25T07:12:30Z http://umpir.ump.edu.my/id/eprint/1762/ Artificial Intelligence Techniques for Machining Performance: a Review M. M., Rahman K., Kadirgama M. M., Noor TJ Mechanical engineering and machinery This paper reviews the approaches of artificial neural network (ANN) on machining performance. ANN considered as a successful approach to modelling the machining process for predicting performance measures through the development of an expert system. An expert system is an interactive intelligence program with an expert-like performance in solving a particular type of problem using knowledge base, inference engine and user interface. The approaches of ANN in past years with respect to cutting forces, surface roughness of the machined work piece, tool wear and material removal rate were reviewed. Results from literatures indicated that the ANN has the ability in generalizing the system characteristics by predicting values close to the actual measured ones. 2010 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1762/1/ARTIFICIAL_INTELLIGENCE_TECHNIQUES_FOR_MACHINING.pdf M. M., Rahman and K., Kadirgama and M. M., Noor (2010) Artificial Intelligence Techniques for Machining Performance: a Review. In: National Conference in Mechanical Engineering Research and Postgraduate Studies (2nd NCMER 2010), 3-4 December 2010 , UMP Pekan, Pahang. .
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery M. M., Rahman K., Kadirgama M. M., Noor Artificial Intelligence Techniques for Machining Performance: a Review
description	This paper reviews the approaches of artificial neural network (ANN) on machining performance. ANN considered as a successful approach to modelling the machining process for predicting performance measures through the development of an expert system. An expert system is an interactive intelligence program with an expert-like performance in solving a particular type of problem using knowledge base, inference engine and user interface. The approaches of ANN in past years with respect to cutting forces, surface roughness of the machined work piece, tool wear and material removal rate were reviewed. Results from literatures indicated that the ANN has the ability in generalizing the system characteristics by predicting values close to the actual measured ones.
format	Conference or Workshop Item
author	M. M., Rahman K., Kadirgama M. M., Noor
author_facet	M. M., Rahman K., Kadirgama M. M., Noor
author_sort	M. M., Rahman
title	Artificial Intelligence Techniques for Machining Performance: a Review
title_short	Artificial Intelligence Techniques for Machining Performance: a Review
title_full	Artificial Intelligence Techniques for Machining Performance: a Review
title_fullStr	Artificial Intelligence Techniques for Machining Performance: a Review
title_full_unstemmed	Artificial Intelligence Techniques for Machining Performance: a Review
title_sort	artificial intelligence techniques for machining performance: a review
publishDate	2010
url	http://umpir.ump.edu.my/id/eprint/1762/ http://umpir.ump.edu.my/id/eprint/1762/1/ARTIFICIAL_INTELLIGENCE_TECHNIQUES_FOR_MACHINING.pdf
first_indexed	2023-09-18T21:54:59Z
last_indexed	2023-09-18T21:54:59Z
_version_	1777414019286564864

Artificial Intelligence Techniques for Machining Performance: a Review

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