Selection of optimal material and operating conditions in composite manufacturing. Part II: complexity, representation of characteristics and decision making

Abstract

An automated procedure is proposed to select the optimum material and processing conditions for composite materials. The complexity of the part is estimated from the STL files of the CAD/CAM programs by evaluating the angles between the triangles, which cover the surface. A correction algorithm identifies the holes and calculates the complexity without considering the triangles at their surfaces if they will be drilled later. Using multiple neural networks represented the most important characteristics of the composite material manufacturing for the user. For each considered material one genetic algorithm is assigned to select the optimal operating conditions. The optimal material is selected by comparing the good qualities of each material after the optimization. The proposed procedure is very attractive for optimization of complex systems when multiple approaches and their several characteristics are considered.