Multi-objective optimization of 3D printing parameters to fabricate TPU for tribological applications

Nirmal Garg, Paras Kumar
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Abstract

Nowadays, polymers frequently replace metals in several applications where comparable properties are desired due to the convenience of processing them as per the requirement. The present work intends to fabricate a thermoplastic polyurethane suitable for journal bearing application using fused deposition modelling (FDM) additive manufacturing method. The cylindrical samples were prepared for experiments using central composite design to examine the effect of FDM machine parameters (such as layer thickness, infill density, and printing speed) on response such as specific wear rate (SWR), coefficient of friction (COF) and hardness. Layer thickness was noticed to be the most significant parameter for the selected responses with a percentage contribution of ∼34% to 72%. Further, as observed from interaction plots the COF and SWR are lowest, and hardness is highest at highest infill density and lowest printing speed. To obtain an optimized set of FDM machine parameters for minimum SWR, COF and maximum hardness, genetic algorithm based multi-objective optimization is performed. The optimized values are SWR of 4.97 × 10−5 mm3/N-m, COF of 0.37 and hardness value of 37.
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多目标优化 3D 打印参数,制造用于摩擦学应用的热塑性聚氨酯
如今,由于可以根据要求方便地进行加工,聚合物在一些需要类似性能的应用中经常取代金属。本研究旨在利用熔融沉积建模(FDM)增材制造方法,制造出适合轴颈轴承应用的热塑性聚氨酯。采用中心复合设计法制备圆柱形样品进行实验,以检验 FDM 机器参数(如层厚度、填充密度和打印速度)对特定磨损率(SWR)、摩擦系数(COF)和硬度等响应的影响。图层厚度是对所选响应最重要的参数,其贡献率在 34% 至 72% 之间。此外,从交互图中可以看出,在填充密度最高、印刷速度最低的情况下,COF 和 SWR 最低,而硬度最高。为了获得最小 SWR、COF 和最大硬度的 FDM 机器参数优化集,进行了基于遗传算法的多目标优化。优化值为 SWR 4.97 × 10-5 mm3/N-m、COF 0.37 和硬度值 37。
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来源期刊
CiteScore
3.80
自引率
16.70%
发文量
370
审稿时长
6 months
期刊介绍: The Journal of Process Mechanical Engineering publishes high-quality, peer-reviewed papers covering a broad area of mechanical engineering activities associated with the design and operation of process equipment.
期刊最新文献
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