Digital Solutions for Integrated and Collaborative Additive Manufacturing

Author:

Lu Yan1,Witherell Paul1,Lopez Felipe2,Assouroko Ibrahim3

Affiliation:

1. National Institute of Standards and Technology, Gaithersburg, MD

2. University of Texas at Austin, Austin, TX

3. Université de Technologie de Compiègne, Compiègne, France

Abstract

Software tools, knowledge of materials and processes, and data provide three pillars on which Additive Manufacturing (AM) lifecycles and value chains can be supported. These pillars leverage efforts dedicated to the development of AM databases, high-fidelity models, and design and planning support tools. However, as of today, it remains a challenge to integrate distributed AM data and heterogeneous predictive models in software tools to drive a more collaborative AM development environment. In this paper, we describe the development of an analytical framework for integrated and collaborative AM development. Information correlating material, product design, process planning and manufacturing operations are captured and managed in the analytical framework. A layered structure is adopted to support the composability of data, models and knowledge bases. The key technologies to enable composability are discussed along with a suite of tools that assist designers in the management of data, models and knowledge components. A proof-of-concept case study demonstrates the potential of the AM analytical framework.

Publisher

American Society of Mechanical Engineers

Cited by 4 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

1. A novel framework for identification of cyber-physical attacks in additive manufacturing;Progress in Additive Manufacturing;2024-07-21

2. History, Development, and Potential Benefits of the Additive Manufacturing Common Data Dictionary;Additive Manufacturing Design and Applications;2023-06-30

3. Surrogate-assisted global transfer optimization based on adaptive sampling strategy;Advanced Engineering Informatics;2023-04

4. Knowledge Management and Additive Manufacturing Technology: A Literature Review;Proceedings of the 20th European Conference on Knowledge Management;2019-09-05

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