Skrzek Kinga, Mazgajczyk Emilia, Dybała Bogdan
Centre for Advanced Manufacturing Technologies (CAMT/FPC), Faculty of Mechanical Engineering, Wrocław University of Science and Technology, Łukasiewicza 5 St., 50-370 Wroclaw, Poland.
Materials (Basel). 2025 Jan 13;18(2):324. doi: 10.3390/ma18020324.
In the era of Industry 4.0, additive manufacturing (AM) technology plays a crucial role in optimizing production processes, especially for small- and medium-sized enterprises (SMEs) striving to enhance competitiveness. Selecting the appropriate material for AM is a complex process that requires considering numerous technical, economic, and environmental criteria. Fuzzy logic-based advisory systems can effectively support decision-making in conditions of uncertainty and subjective user preferences. This study presents a developed advisory system model that uses the Analytic Hierarchy Process (AHP) method and triangular and trapezoidal membership functions, enabling dynamic adjustment of criterion weights. The results demonstrated that the system achieved 85% alignment with user preferences, confirming its effectiveness. Future research may focus on integrating fuzzy logic with machine learning algorithms to further enhance the system's precision and flexibility.
在工业4.0时代，增材制造（AM）技术在优化生产流程中发挥着关键作用，特别是对于那些努力提高竞争力的中小企业（SMEs）而言。为增材制造选择合适的材料是一个复杂的过程，需要考虑众多技术、经济和环境标准。基于模糊逻辑的咨询系统能够在不确定性条件和主观用户偏好的情况下有效支持决策制定。本研究提出了一种开发的咨询系统模型，该模型使用层次分析法（AHP）以及三角形和梯形隶属函数，能够动态调整标准权重。结果表明，该系统与用户偏好的一致性达到了85%，证实了其有效性。未来的研究可能集中于将模糊逻辑与机器学习算法相结合，以进一步提高系统的精度和灵活性。
