Abstract

Manufacturing process optimization is an ever-actual goal. Within this goal, machining parameters optimization is a very important task. Machining parameters strongly influence the manufacturing costs, process productivity and piece quality. Literature presents a series of optimization methods. The results supplied by these methods are comparable and it is difficult to establish which method is the best. For machining parameters optimization, this paper proposes a novel, simple and efficient method, without additional costs related to new software packages. This approach is based on linear mathematical programming. The optimization mathematical models are, however, nonlinear. Therefore, mathematical model linearization is required. The major and difficult problem is the linearization of the objective function. This represents the key element of the proposed optimization method. In this respect, the paper proposes an original mathematical procedure for calculating the part of the objective function that refers to the analytical integration of the tool life into the model. This calculus procedure was transposed into an original software tool. For demonstrating the validity of the method, a comparison is presented among the results obtained by certain optimization techniques. It results that the proposed method is simple and as good as those presented by the literature.

Highlights

  • For machining parameters optimization, the relationships among machining parameters, piece accuracy, process cost/productivity and technological resources must be mathematically modelled

  • Due to the advantages of this algorithm, the present paper proposes to present the method for using linear mathematical programming in solving nonlinear mathematical models, regarding machining parameters optimization

  • The present paper addresses the issue of machining parameters optimization

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Summary

Introduction

The relationships among machining parameters, piece accuracy, process cost/productivity and technological resources must be mathematically modelled. These relationships concern the restrictive technical conditions, as well as the chosen optimization criterion. The particularities of the models for machining parameters optimization should recommend the use of nonlinear mathematical programming [3]. Certain methods could be used in accordance with the particularities of the mathematical models, but there is no general valid method. The efficiency of these methods depends on choosing a starting solution These particularities and the nonlinearity of the mathematical models have determined seeking certain solutions outside the mathematical programming field, as well

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