A determination of the characteristic technological and economic parameters during metal cutting

A new non-deterministic optimization approach to the complex optimization Of cutting parameters during machining is proposed. It uses artificial neural networks to solve the cutting-conditions optimization problem. The developed approach is based on the "maximum production rate criterion" and incorporates four technological constraints. By selecting the optimum cutting conditions it is possible to reach a favourable ratio between low machining costs and high productivity, taking into account the given limitation of the cutting process. First, the problem of determining the optimum machining parameters is formulated as a multiple-objective optimization problem. Then, neural networks are proposed to represent manufacturers' preference structures. The experimental results show that the proposed algorithm for solving the non-linear-constrained optimization problems is efficient and can be integrated into intelligent manufacturing systems. To demonstrate the performance of the proposed approach, an illustrative example is discussed in detail. (C) 2004 Journal of Mechanical Engineering. All rights reserved.