Dimensional Accuracy of Acrylonitrile Butadiene Styrene Material Produced by Additive Manufacturing Method


Bayraklilar M. S.

JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE, cilt.33, sa.5, ss.2531-2551, 2024 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 33 Sayı: 5
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s11665-023-08205-9
  • Dergi Adı: JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Chemical Abstracts Core, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2531-2551
  • Kocaeli Üniversitesi Adresli: Hayır

Özet

Mass customization is designing and manufacturing customized products with mass production efficiency and speed. Additive manufacturing (AM), one of the mass customization methods, is still expensive compared to mass production but continues to develop and become widespread daily. In addition, additive manufacturing has numerous limitations, such as slow print speed, less accuracy and repeatability, and limited material selection for a particular application. Therefore, this article determined the optimum parameters to improve dimensional accuracy in the AM method. The most common materials used in the additive manufacturing method are acrylonitrile butadiene styrene (ABS) and polylactic acid. Dimensional accuracy is one of the most critical parameters to meet quality standards in additive manufacturing, as in all production methods. Dimensional accuracy is the most critical parameter for smooth joining, especially for interlocking parts. The production parameters of an AM affect dimensional accuracy and the product's mechanical properties and surface quality. Optimal parameters vary to ensure dimensional accuracy in different ways. This study determined optimum parameters for dimensional accuracy, minimum filament consumption, and the production time of some basic shapes produced using ABS material by the FDM method. Cubic infill pattern, two shells, 50% infill pattern, and 0.2 mm wall thickness can be considered optimal for all shapes, although the optimal parameters for different shapes are different. Artificial neural networks (ANN) were used for the estimation of the experimental results. The estimations (R-2) made by ANN in this study are over 90%.