Generalized fuzzy model for metal cutting data selection

Metal cutting data selection is complex and cannot be easily formulated to meet design specification by any mathematical model. Optimized Machinability data is obtained from a skilled machine tool operator's experience and intuition. A rule-based expert system and materials database have been i...

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Main Authors: Wong, S.V., Hamouda, A.M.S., El Baradie, M.A.
Format: Article
Language:English
Published: Elsevier Science 1999
Online Access:http://psasir.upm.edu.my/id/eprint/116735/
http://psasir.upm.edu.my/id/eprint/116735/1/116735.pdf
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author Wong, S.V.
Hamouda, A.M.S.
El Baradie, M.A.
author_facet Wong, S.V.
Hamouda, A.M.S.
El Baradie, M.A.
author_sort Wong, S.V.
building UPM Institutional Repository
collection Online Access
description Metal cutting data selection is complex and cannot be easily formulated to meet design specification by any mathematical model. Optimized Machinability data is obtained from a skilled machine tool operator's experience and intuition. A rule-based expert system and materials database have been incorporated into many CAD/CAM systems in order to obtain optimal machining parameters. Fuzzy logic is a better tool to describe the strategy and action of the skilled operator when selecting the metal cutting data. A first prototype of such a system was developed by the present authors. This paper further describes development of fuzzy models and their feasibility. Development of several models for different cutting tools is presented and discussed. The models are validated with the Machining Data Handbook. The feasibility of a generalized fuzzy model for all the cutting tools is also presented.
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spelling upm-1167352025-07-07T04:40:02Z http://psasir.upm.edu.my/id/eprint/116735/ Generalized fuzzy model for metal cutting data selection Wong, S.V. Hamouda, A.M.S. El Baradie, M.A. Metal cutting data selection is complex and cannot be easily formulated to meet design specification by any mathematical model. Optimized Machinability data is obtained from a skilled machine tool operator's experience and intuition. A rule-based expert system and materials database have been incorporated into many CAD/CAM systems in order to obtain optimal machining parameters. Fuzzy logic is a better tool to describe the strategy and action of the skilled operator when selecting the metal cutting data. A first prototype of such a system was developed by the present authors. This paper further describes development of fuzzy models and their feasibility. Development of several models for different cutting tools is presented and discussed. The models are validated with the Machining Data Handbook. The feasibility of a generalized fuzzy model for all the cutting tools is also presented. Elsevier Science 1999 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/116735/1/116735.pdf Wong, S.V. and Hamouda, A.M.S. and El Baradie, M.A. (1999) Generalized fuzzy model for metal cutting data selection. Journal of Materials Processing Technology, 89-90. pp. 310-317. ISSN 0924-0136 https://linkinghub.elsevier.com/retrieve/pii/S0924013699001272 10.1016/S0924-0136(99)00127-2
spellingShingle Wong, S.V.
Hamouda, A.M.S.
El Baradie, M.A.
Generalized fuzzy model for metal cutting data selection
title Generalized fuzzy model for metal cutting data selection
title_full Generalized fuzzy model for metal cutting data selection
title_fullStr Generalized fuzzy model for metal cutting data selection
title_full_unstemmed Generalized fuzzy model for metal cutting data selection
title_short Generalized fuzzy model for metal cutting data selection
title_sort generalized fuzzy model for metal cutting data selection
url http://psasir.upm.edu.my/id/eprint/116735/
http://psasir.upm.edu.my/id/eprint/116735/
http://psasir.upm.edu.my/id/eprint/116735/
http://psasir.upm.edu.my/id/eprint/116735/1/116735.pdf