采用田口实验设计对fdm加工的聚乳酸的力学性能进行了实验分析和优化

Q3 Mathematics
M. Abouelmajd, A. Bahlaoui, I. Arroub, M. Zemzami, N. Hmina, M. Lagache, S. Belhouideg
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引用次数: 12

摘要

熔融沉积建模(FDM)是目前应用最广泛的增材制造工艺之一。预测不同3D打印参数对打印部件质量的影响是研究人员面临的关键挑战之一。采用实验技术的田口设计,研究了沉积速度、挤压温度和光栅方向三个FDM工艺参数对聚乳酸(PLA)零件的弯曲强度、刚度和断裂挠度的影响。结果表明,温度对PLA试样力学性能的影响最大,其次是速度和取向。确定了具有最佳力学性能的最佳成分。抗弯强度、抗弯刚度和断裂挠度的最佳预测响应分别为159.78 N、39.92 N/mm和12.55 mm。方差分析(ANOVA)得到的R2表明,实验结果与回归模型预测结果吻合较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental analysis and optimization of mechanical properties of FDM-processed polylactic acid using Taguchi design of experiment
Fused deposition modeling (FDM) is one of the most used additive manufacturing processes in the current time. Predicting the impact of different 3D printing parameters on the quality of printed parts is one of the critical challenges facing researchers. The present paper aims to examine the effect of three FDM process parameters, namely deposition velocity, extrusion temperature, and raster orientation on the bending strength, stiffness, and deflection at break of polylactic acid (PLA) parts using Taguchi design of experiment technique. The results indicate that the temperature has the highest impact on the mechanical properties of PLA specimens followed by the velocity and the orientation. The optimum composition offering the best mechanical behavior was determined. The optimal predicted response was 159.78 N, 39.92 N/mm, and 12.55 mm for the bending strength, bending stiffness, and deflection at break, respectively. The R2 obtained from analysis of variance (ANOVA) showed good agreement between the experimental results and those predicted using a regression model.
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来源期刊
CiteScore
2.00
自引率
0.00%
发文量
19
审稿时长
16 weeks
期刊介绍: The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).
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