Optimization of Hybrid Thermoplastic Composite Production via Artificial Intelligence Approach


Creative Commons License

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

Automotive Composites Conference and Exhibition, Michigan, Amerika Birleşik Devletleri, 02 Kasım 2021

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Michigan
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

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.