3D Printing of Nonplanar Layers for Smooth Surface Generation

Daniel Ahlers, Florens Wasserfall, N. Hendrich, Jianwei Zhang
{"title":"3D Printing of Nonplanar Layers for Smooth Surface Generation","authors":"Daniel Ahlers, Florens Wasserfall, N. Hendrich, Jianwei Zhang","doi":"10.1109/COASE.2019.8843116","DOIUrl":null,"url":null,"abstract":"Additive manufacturing processes are inherently subject to discretization effects. For most technologies, stairstepping artifacts impair the surface quality of 3D printed objects, especially when the surface slope is close to horizontal.In this paper we propose a novel Fused Deposition Modeling (FDM) slicing approach that combines nonplanar and planar layers, increasing printing quality and resulting in smoother, stronger object surfaces. Our slicing algorithm automatically detects which parts of the object should be printed with nonplanar layers and uses a geometric model of the printhead and extruder to generate collision-free toolpaths.Our open source implementation is based on the popular Slic3r tool and can be used on all common three-axis 3D printers. We present typical printing results and compare surface quality as well as slicing and printing times with traditional and adaptive planar slicing.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"86 1","pages":"1737-1743"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2019.8843116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 53

Abstract

Additive manufacturing processes are inherently subject to discretization effects. For most technologies, stairstepping artifacts impair the surface quality of 3D printed objects, especially when the surface slope is close to horizontal.In this paper we propose a novel Fused Deposition Modeling (FDM) slicing approach that combines nonplanar and planar layers, increasing printing quality and resulting in smoother, stronger object surfaces. Our slicing algorithm automatically detects which parts of the object should be printed with nonplanar layers and uses a geometric model of the printhead and extruder to generate collision-free toolpaths.Our open source implementation is based on the popular Slic3r tool and can be used on all common three-axis 3D printers. We present typical printing results and compare surface quality as well as slicing and printing times with traditional and adaptive planar slicing.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于光滑表面生成的非平面层3D打印
增材制造过程本身就受到离散化效应的影响。对于大多数技术来说,台阶式工件会损害3D打印对象的表面质量,特别是当表面坡度接近水平时。在本文中,我们提出了一种新的融合沉积建模(FDM)切片方法,该方法结合了非平面和平面层,提高了打印质量,并产生了更光滑、更坚固的物体表面。我们的切片算法自动检测物体的哪些部分应该用非平面层打印,并使用打印头和挤出机的几何模型来生成无碰撞的工具路径。我们的开源实现基于流行的Slic3r工具,可以在所有常见的三轴3D打印机上使用。我们给出了典型的打印结果,并比较了传统和自适应平面切片的表面质量、切片和打印时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A proposed mapping method for aligning machine execution data to numerical control code optimizing outpatient Department Staffing Level using Multi-Fidelity Models Advanced Sensor and Target Development to Support Robot Accuracy Degradation Assessment Multi-Task Hierarchical Imitation Learning for Home Automation Deep Reinforcement Learning of Robotic Precision Insertion Skill Accelerated by Demonstrations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1