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Indexed by:Journal Papers

Date of Publication:2020-08-01

Journal:JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Included Journals:EI、SCIE

Volume:282

ISSN No.:0924-0136

Key Words:Particle reinforced mental matrix composites (PRMMCs); Cutting temperature; Friction temperature; Analytical temperature model; Orthogonal cutting; Heat generation ratio

Abstract:There are huge disparities in the physical and mechanical properties between the two-phase materials of particle reinforced metal matrix composites (PRMMCs). Therefore, the heat generated by reinforced particles and metal matrix is different under the action of cutting and rubbing of the cutting tool. However, limited studies have been done using analytical method to predict the cutting temperature during cutting PRMMCs. The purpose of this paper is to establish an analytical model to predict cutting and friction temperatures for workpiece surface layer based on the moving heat source method during cutting varied PRMMCs. The material properties (i.e. particle volume fraction and average particle size) of PRMMCs, respective physical properties of reinforced particle and metal matrix, and accurate value of friction force were taken into consideration in the proposed model. The temperature field distribution for workpiece surface layer was acquired. This study proposed a new design method of experiment to accurately determine the friction force and temperature between tool flank-workpiece during cutting PRMMCs required in the analytical model. The parameters of the heat generation ratio for shear plane and tool flank-workpiece rubbing heat sources were proposed, which were appropriate for cutting temperature prediction for PRMMCs with different particle volume fraction and average particle size. The fraction of the heat generated by shear plane conducted into workpiece (heat partition ratio, BAs hear 1) was also identified. Conducting the orthogonal cutting experiment, the influence tendencies of the various parameters such as average particles size, particle volume fraction, cutting speed, uncut chip thickness and tool flank wear on cutting temperature during cutting PRMMCs were evaluated. With verification, the analytical results of the cutting and friction temperatures based on the proposed model captured an acceptable tendency with experimental results and yielded a prediction error being smaller than 16.0 %. The proposed model in this study was applicable to predict the cutting and friction temperatures of PRMMCs especially with high particle volume fraction and large average particle size.