能量消耗与强度在MEΧ聚乳酸3D打印

IF 3.9 Q2 ENGINEERING, INDUSTRIAL Advances in Industrial and Manufacturing Engineering Pub Date : 2023-05-01 DOI:10.1016/j.aime.2023.100119
Nectarios Vidakis , Markos Petousis , Emmanuel Karapidakis , Nikolaos Mountakis , Constantine David , Dimitrios Sagris
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引用次数: 5

摘要

增材制造(AM)的成本效益和环境影响是当今最热门的两个与工艺相关的工业和研究课题。能源效率是一个强有力的主张,因此是对耐用和功能的3d打印工件的需求。这些矛盾的方面通常需要灵活性和妥协。特别是对于材料挤压(MEX) 3D打印,控制参数的多样性使得这种优化变得复杂。本研究探讨了七个通用和机器无关的控制因素(例如,光栅沉积角;定向角;层厚度;加密密度;喷嘴温度;床层温度和打印速度)对聚乳酸能量消耗对MEX 3D打印试件压缩响应的影响。为此,编译了一个三能级L27正交阵列。每次实验运行包括5个样品副本(按照ASTM D695-02a标准),总计135个实验。通过秒表法确定了材料的加工时间和能耗,通过压缩试验得到了材料的抗压强度、弹性模量和韧性。田口分析对每个控制参数对每个响应度量的影响进行了排序。打印速度和层厚是影响能耗最大的控制参数。此外,充填体密度和取向角是影响抗压强度的最主要因素。最后,编制并验证了七个控制参数下每个反应指标的二次回归模型(QRM)方程。因此,能源效率和机械强度之间的最佳解决方案现在是可能的,这是一个具有巨大技术和工业价值的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Energy consumption versus strength in MEΧ 3D printing of polylactic acid

The cost-effectiveness and the environmental impact of Additive Manufacturing (AM) are nowadays two of the hottest process-related industrial and research topics. Energy efficiency is a strong claim, and so is the demand for durable and functional 3D-printed workpieces. These contradictory aspects usually require flexibility and compromises. Especially for Material Extrusion (MEX) 3D printing, the plurality of the control parameters makes such optimizations complicated. This research explores the effect of seven generic and machine-independent control factors (e.g., Raster Deposition Angle; Orientation Angle; Layer Thickness; Infill Density; Nozzle Temperature; Bed Temperature, and Printing Speed) on energy consumption of Polylactic Acid over the compressive response of MEX 3D printed specimens. To make it possible, a three-level L27 orthogonal array was compiled. Each experimental run included five specimen replicas (after the ASTM D695-02a standard) summing up 135 experiments. The fabrication time and the energy consumption were determined by the stopwatch method, whereas the compressive strength, elasticity modulus, and toughness were derived with compressive tests. The Taguchi analysis ranked the impact of each control parameter on each response metric. The printing speed and the layer thickness were the most influential control parameters on energy consumption. Furthermore, the infill density and the orientation angle were found as the most dominant factors in the compressive strength. Finally, Quadratic Regression Model (QRM) equations for each response metric over the seven control parameters were compiled and validated. Hereto, the best settlement between energy efficiency and mechanical strength is now possible, an option with great technological and industrial merit.

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来源期刊
Advances in Industrial and Manufacturing Engineering
Advances in Industrial and Manufacturing Engineering Engineering-Engineering (miscellaneous)
CiteScore
6.60
自引率
0.00%
发文量
31
审稿时长
18 days
期刊最新文献
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