Composite materials provide distinctive advantages in manufacture of advanced products because of attractive features such as high strength and light weight, but on the other hand machining of composite materials is difficult to carry out due to the anisotropic and non-homogeneous structure of composites and to the high abrasiveness of their reinforcing constituents. This typically results in damage being introduced into the workpiece and in very rapid wear development in the cutting tool. Conventional machining process such as drilling can be applied to composite materials, provided proper tool design and operating conditions are adopted. In this paper, A genetic algorithm (GA) based optimization procedure has been developed to optimize two factors, material removal rate; and delamination factor, using multi-objective function model with a weighted approach for the productivity, and superficial quality. An a posteriori approach was used to obtain a set of optimal solutions. An application sample was developed and its results were analyzed for several different production conditions. Finally, the obtained outcomes were arranged in graphical form and analyzed to make the proper decision for different process preferences. This paper also remarks the advantages of multi-objective optimization approach over the single-objective one.

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