Generalized fuzzy model for metal cutting data selection - Wong, S.V.; Hamouda, A.M.S.; El Baradie, M.A. (Elsevier Science, 1999)
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.