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Optimization of mixture ratios of raw materials in thermoplastic hybrid composites based on particle swarm optimization algorithm

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Abstract

In recent years, the high cost of searching and processing raw materials and the fact that raw material resources have come to the point of depletion force industry and science to seek different solutions. In addition, due to the necessity of increasing the quality, the tendency to composite production has increased. However, it is necessary to make improvements in parameters such as quality, time, and cost in composite production. The use of artificial intelligence technology in the production of composites is becoming more and more common. On the other hand, studies on the determination of raw material mixture ratios are not common. Such studies are usually carried out with experimental productions, which increases the production cost and prolongs the production process. In this study, it was studied on the proportional optimization of the mixture components of thermoplastic hybrid composite materials by using the particle swarm optimization algorithm. First, a dataset was created with the real values obtained from the experimental productions, and the raw material mixture ratios to be included in the mixture were determined by making simulation studies on this dataset. With these obtained ratios, new productions were made, and tests were applied on these productions. Test results have shown that the resulting products are more successful by over 95%. Thus, it has been proven that especially the use of artificial intelligence technology in the field of composites in pre-production stages such as raw material and mixture processes can both reduce the cost and increase the quality.

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Acknowledgements

We would like to thank Prof. Dr. Fatih Mengeloğlu and Büşra Avcı for their assistance during the experimental study and production phase.

Funding

The data used in this study were obtained within the scope of the project supported by TUBITAK (Scientific and Technological Research Council of Turkiye) [grant number 120O339].

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Authors and Affiliations

  1. Department of Computer Engineering, Artvin Çoruh University, 08000, Artvin, Turkey

    Ercüment Öztürk

  2. Department of Forest Industry Engineering, Karadeniz Technical University, 61080, Trabzon, Turkey

    Ayfer Dönmez Çavdar

  3. Department of Computer Engineering, Karadeniz Technical University, 61080, Trabzon, Turkey

    Tuğrul Çavdar

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  1. Ercüment Öztürk
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E.Ö.: Methodology, coding, investigation, writing—reviewing, validation, editing A.D.Ç.: Conceptualization, methodology, supervision reviewing and editing T.Ç.: Methodology, reviewing and editing, supervision.

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Correspondence to Ercüment Öztürk.

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Öztürk, E., Çavdar, A.D. & Çavdar, T. Optimization of mixture ratios of raw materials in thermoplastic hybrid composites based on particle swarm optimization algorithm. J Supercomput 81, 13 (2025). https://doi.org/10.1007/s11227-024-06555-2

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