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<p>Additive manufacturing is one of the most popular technologies for various engineering applications. Specifically, fused deposition modelling (FDM) is a primary additive manufacturing method that can deposit the material in a layer-by-layer manner. However, the performance of FDM-fabricated parts is affected by process parameters, material properties, and fabrication methods. This review study presents a comprehensive review of fused deposition modelling (FDM), concentrating on application, process parameters, parameter optimization, modelling, performance metrics, and numerical simulation. The main points of additive manufacturing and FDM are reviewed, highlighting their benefits, like design flexibility, cost-effectiveness, and suitability for environmental impact. The challenges of material limitation, process parameter optimization, and mechanical properties are addressed through literature findings. Noteworthy developments in modelling and optimization methods such as Taguchi, response surface methodology, artificial neural networks, fuzzy logic, genetic algorithms, and machine learning are discussed. Future research directions include enhancing material range, enhancing quality metrics, and advancing additive manufacturing methods. This review aims to provide valuable insight into current FDM research and its potential for innovation and sustainability.</p>

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A review of current research and prospects of fused deposition modelling: application, materials, performance, process variables, parameter optimization, and numerical study

  • 期刊论文

  • 发表日期：

    2025年5月7日

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  • Yitayal Belew Siyoum,
  • Fikir Gashaw Kindie,
  • Mebratu Assefa Gebeyehu

摘要

Additive manufacturing is one of the most popular technologies for various engineering applications. Specifically, fused deposition modelling (FDM) is a primary additive manufacturing method that can deposit the material in a layer-by-layer manner. However, the performance of FDM-fabricated parts is affected by process parameters, material properties, and fabrication methods. This review study presents a comprehensive review of fused deposition modelling (FDM), concentrating on application, process parameters, parameter optimization, modelling, performance metrics, and numerical simulation. The main points of additive manufacturing and FDM are reviewed, highlighting their benefits, like design flexibility, cost-effectiveness, and suitability for environmental impact. The challenges of material limitation, process parameter optimization, and mechanical properties are addressed through literature findings. Noteworthy developments in modelling and optimization methods such as Taguchi, response surface methodology, artificial neural networks, fuzzy logic, genetic algorithms, and machine learning are discussed. Future research directions include enhancing material range, enhancing quality metrics, and advancing additive manufacturing methods. This review aims to provide valuable insight into current FDM research and its potential for innovation and sustainability.