Multi-objective Feed Optimization with Constant Cutting Force Constraints under Variable Cutting Depth

doi:10.3901/JME.2021.05.242

Abstract

Abstract: Aiming at the problem of low machining efficiency and poor surface quality caused by the constant feed set by craftsmen in CNC machining, a multi-objective feed optimization method based on constant cutting force constraints was proposed. Based on the cutting force prediction model, taking comprehensive consideration to improve the machining efficiency and surface quality of parts as the optimization goal, and taking the constant cutting force, machine parameters, machined surface quality and feeding smooth transition as the constraint conditions, the multi-objective feed optimization model is established. Then, the cutting force coefficients are calibrated by orthogonal cutting experiments, and the correctness and accuracy of the prediction model are verified by experiments. The original cutting force data was collected by trial cutting the workpiece, and the optimal target cutting force value was determined through experimental analysis. The optimization model is used to optimize the feed based on the controlled elitist non-dominated sorting genetic algorithm (Controlled NSGA-II). The experimental results verified the effectiveness of the multi-objective feed optimization model, which reached the goal of constant cutting force constraint, guaranteed the quality of the machining surface, improved the machining efficiency, achieved the process parameters optimization, and finally improved the application performance of the numerical system.

Key words: feed optimization, constant cutting force, multi-objective optimization, controlled NSGA-II

CLC Number:

TH162

ZHANG Yang, WU Baohai, XIA Weihong, ZHANG Ying, ZHAO Jing. Multi-objective Feed Optimization with Constant Cutting Force Constraints under Variable Cutting Depth[J]. Journal of Mechanical Engineering, 2021, 57(5): 242-250.

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