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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/1762/1/ARTIFICIAL_INTELLIGENCE_TECHNIQUES_FOR_MACHINING.pdf |
| _version_ | 1825821157818892288 |
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| author | M. M., Rahman K., Kadirgama M. M., Noor |
| author_facet | M. M., Rahman K., Kadirgama M. M., Noor |
| author_sort | M. M., Rahman |
| collection | UMP |
| 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. |
| first_indexed | 2024-03-06T11:37:18Z |
| format | Conference or Workshop Item |
| id | UMPir1762 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:37:18Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | UMPir17622018-01-25T07:12:30Z 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. . (Published) |
| spellingShingle | TJ Mechanical engineering and machinery M. M., Rahman K., Kadirgama M. M., Noor Artificial Intelligence Techniques for Machining Performance: a Review |
| title | 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_short | Artificial Intelligence Techniques for Machining Performance: a Review
|
| title_sort | artificial intelligence techniques for machining performance a review |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/1762/1/ARTIFICIAL_INTELLIGENCE_TECHNIQUES_FOR_MACHINING.pdf |
| work_keys_str_mv | AT mmrahman artificialintelligencetechniquesformachiningperformanceareview AT kkadirgama artificialintelligencetechniquesformachiningperformanceareview AT mmnoor artificialintelligencetechniquesformachiningperformanceareview |