Optimization of hybrid friction stir welding of PMMA: 3D-printed parts and conventional sheets welding efficiency in single- and two-axis welding traces

Author:

Petousis Markos,Mountakis Nikolaos,Vidakis NectariosORCID

Abstract

AbstractHerein, the feasibility of joining with the friction stir welding (FSW) process 3D-printed parts made of poly(methyl methacrylate) (PMMA) with extruded PMMA sheets is investigated. A full factorial design method is followed, with two control parameters, i.e., tool rotational and travel speed, and three levels each. The hybrid joints produced were subjected to tensile and flexural loading and the corresponding properties were optimized with statistical modeling tools. Regression analysis provided prediction models for the five output metrics. The temperature was monitored throughout the experimental process. Samples were inspected with optical and scanning electron microscopy and their morphological characteristics were correlated with the joining conditions. The optimized FSW parameters were used for joining PMMA 3D-printed parts with sheets with two-axis joining seams. The produced hybrid joints were more than sufficient in their mechanical properties. The highest welding efficiency achieved in the tensile tests was 1.36, by the sample welded with 900 rpm and 6 mm/min. The sample welded with the same conditions achieved also the highest welding efficiency in the flexural tests (0.98). The findings presented proven the efficiency of the hybrid PMMA joints studied and have direct industrial applications for efficient component production. Graphical Abstract

Funder

Hellenic Mediterranean University

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3