A Common Data Dictionary and Common Data Model for Additive Manufacturing

Author:

Kuan Alexander,Aggour Kareem S.,Li Shengyen,Lu Yan,Mohr Luke,Kitt Alex,Macdonald Hunter

Abstract

AbstractAdditive manufacturing (AM) leverages emerging technologies and well-adopted processes to produce near-net-shape products. The advancement of AM technology requires data management tools to collect, store, and share information through the product development lifecycle and across the material and machine value chain. To address the need for sharing data among AM developers and practitioners, an AM common data dictionary (AM-CDD) was first developed based on community consensus to provide a common lexicon for AM, and later standardized by ASTM International. Following the AM-CDD work, the development of a common data model (AM-CDM) defining the structure and relationships of the key concepts, and terms in the AM-CDD is being developed. These efforts have greatly facilitated system integrations and AM data exchanges among various organizations. This work outlines the effort to create the AM-CDD and AM-CDM, with a focus on the design of the AM-CDM. Two use cases are provided to demonstrate the adoption of these efforts and the interoperability enabled by the AM-CDM for different engineering applications managed by different types of database technology. In these case studies, the AM-CDM is implemented in two distinct formats to curate AM data from NIST—the first in XML from their additive manufacturing material database and the second in OWL from their 2022 AM bench database. These use cases present the power of the AM-CDM for data representation, querying, and seamless data exchange. Our implementation experiences and some challenges are highlighted that can assist others in future adoptions of the AM-CDM for data integration and data exchange applications.

Publisher

Springer Science and Business Media LLC

Reference20 articles.

1. Blakey-Milner B, Gradl P, Snedden G, Brooks M, Pitot J, Lopez E, Leary M, Berto F, du Plessis A (2021) Metal additive manufacturing in aerospace: a review. Mater Des 209(110008):1–33

2. Kumar R, Kumar M, Chohan JS (2021) The role of additive manufacturing for biomedical applications: a critical review. J Manuf Process 64:828–850

3. Saunders S (2021) GE Aviation Announces 100,000th 3D Printed Fuel Nozzle Shipped from Auburn Plant. 3Dprint.com. https://3dprint.com/284243/ge-aviation-announces-100000th-3d-printed-fuel-nozzle-shipped-from-auburn-plant/

4. Wilkinson MD, Dumontier M, IjJ A et al (2016) The FAIR guiding principles for scientific data management and stewardship. Sci Data 3(1):1–9. https://doi.org/10.1038/sdata.2016.18

5. Bonnard R, Hascoët JY, Mognol P, Zancul E, Alvares AJ (2019) Hierarchical object-oriented model (HOOM) for additive manufacturing digital thread. J Manuf Syst. https://doi.org/10.1016/j.jmsy.2018.11.003

Cited by 2 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