Abstract:

Difficulty in raw material supply and rapid consumption of natural resources have made it necessary to turn to composite production, which is an alternative method. Accordingly, there has been an increase in research and industrial use of composite materials in recent years. The main reasons for this are the difficulties in obtaining raw materials, the cost and time factor. On the other hand, another important reason why composites are preferred is that they have a higher strength-density ratio than other materials, they are more durable and lighter. Composite materials require high technology production in order to keep homogeneous structure, high quality, and production costs at an acceptable level. In the composite production stages, thermoplastic and filler reinforcement mixtures are applied with extremely complex processes. Optimizing such formulations requires a lot of experimental production but incurs high costs. As a result, it is essential to reduce these high costs and produce with optimized mixing ratios. In this study, the Gray Wolf Optimization algorithm (GWO), an artificial intelligence method was used as a solution. It has been observed that optimum production recipes and production process parameters can be obtained with the GWO algorithm. In order to produce hybrid thermoplastic composites, the raw material ratios in all possible mixtures were prepared in a simulation environment and the problem was tried to be solved with an approach based on finding the best solution, and it was aimed to produce the desired quality product for experimental use without the need for a large number of productions.

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