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A Review on Application of Soft Computing Techniques in Machining of Particle Reinforcement Metal Matrix Composites

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Abstract

In this paper, a wide literature review of soft computing methods in conventional machining processes of metal matrix composites is carried out. The tool wear, cutting force along with surface quality are presented in the different types of machining processes and examined thoroughly. Summary of the different particular soft computing approaches in machining such as turning, milling, drilling and grinding operations are thoroughly discussed. Furthermore, this work put emphases on the optimization and modeling of the machining process. The study will emphasis on the most general methods used by researchers in literature for developing the statistical and mathematical modeling using soft computing approaches including, genetic algorithm, response surface methodology, fuzzy logic, artificial neural network, Taguchi method and particle swarm optimization. In last section the comprehensive open issues and conclusion are presented for application of soft computing techniques in machining of metal matrix composite performance prediction and optimization.

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  1. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, 150001, China

    Rashid Ali Laghari, Jianguang Li & Shu-qi Wang

  2. Department of Computer Science, Sindh Madressatul Islam University, Karachi, Pakistan

    Asif Ali Laghari

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Laghari, R.A., Li, J., Laghari, A.A. et al. A Review on Application of Soft Computing Techniques in Machining of Particle Reinforcement Metal Matrix Composites. Arch Computat Methods Eng 27, 1363–1377 (2020). https://doi.org/10.1007/s11831-019-09340-0

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