Optimization of Hybrid Thermoplastic Composite Production via Artificial Intelligence Approach

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Öztürk E., Dönmez Çavdar A., Çavdar T., Mengeloğlu F.

Automotive Composites Conference and Exhibition, Michigan, United States Of America, 02 November 2021

  • Publication Type: Conference Paper / Full Text
  • City: Michigan
  • Country: United States Of America
  • Karadeniz Technical University Affiliated: Yes


Nowadays, "hybrid composites" containing multi-component additive / reinforcer instead of single matrix and single reinforcing element attract more attention in new product designs.  For the hybrid composite materials to be widely used in a critical load bearing application, they must undergo extensive fatigue tests. However, this situation increases the cost as it requires extensive test programs and a long process. This study is aimed to produce the desired quality the hybrid material without a large number of productions. Particle swarm optimization (PSO), an artificial intelligence technique based on heuristic algorithm, is used to determine the best formulation in a simulation environment for the hybrid composite. This study enables finding the rates of optimum usage for hybrid composite production containing two or more additives / reinforcing materials before production and lays the groundwork for research to be carried out in the correct working ranges. As a result, it is obtained to both reduce the cost and speed up the production process with a success over than 90% by making pre-simulations using artificial intelligent optimization algorithms.