Collaborative Research: CESER: EAGER: "FabWave" - A Pilot Manufacturing Cyberinfrastructure for Shareable Access to Information Rich Product Manufacturing Data

合作研究：CESER：EAGER：“FabWave”——用于共享访问信息丰富的产品制造数据的试点制造网络基础设施

• 批准号: 1812687
• 负责人: Binil Starly
• 金额: $ 19.12万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1812687&HistoricalAwards=false
• 关键词: Collaborative; Research; CESER; EAGER; FabWave

Advanced manufacturing research is dependent on access to large datasets of product models to enable product designers to learn from past errors, and to discover and develop new solutions. However, such datasets are typically archived in inaccessible repositories and may be poorly described and difficult to use by others. Current manufacturing research must shift from siloed repositories of product manufacturing data to a federated, decentralized, open and inter-operable approach. This transformation can be achieved by embedding cyber-capability in every physical end-point, be it on a desktop used by a product designer or within the control systems of a manufacturing machine. The goal of this project is to develop a pilot manufacturing-focused cyberinfrastructure called FabWave. FabWave will gather together digital data on product and manufacturing processes from diverse sources, in particular, three-dimensional (3D) computer aided design (CAD) models generated by academia and public community users, into a new rich dataset that, in turn, will be fully accessible to manufacturing researchers and others. FabWave's system design will be driven by the needs of the manufacturing research community, and the project will encourage its adoption by academic users, government labs and the public. FabWave will aim to lower the barriers for users to upload, share and download 3D product model data; it will also enable manufacturing science researchers to gain access to an information rich dataset for testing and evaluation of algorithms to advance manufacturing research and offer the capability for the community to build custom apps that provide services to the community. This infrastructure development project aligns with the NSF Harnessing Data for 21st Century Science and Engineering Big Ideas vision and can serve to improve US competitiveness in advanced manufacturing.The de novo cyberinfrastructure tools to be built in the FabWave project include: 1) Direct plugins within design software to allow easier capture of metadata and upload of 3D product models to the FabWave repository with limited human interaction; 2) a data-store with application programming interface (API) tools to allow users to write scripts to search through the repository for content specific to their research questions. Innovative use of the Inter-Planetary File System (IPFS) protocols along with next generation unstructured databases will serve to index and enable search services for Fabwave's users. the project will demonstrate use of FabWave for development of community facing third-party apps and libraries. Ultimately, the research community will have access to a rich source of product datasets created within research laboratories, within classes and through other open sourced projects. This data network, if expanded across universities, would accelerate advancements in cybermanufacturing, engineering systems design, and cyber-physical systems in manufacturing. In addition, FabWave will enable new areas of research in manufacturing information integration and informatics combined with reducing the barriers to exploring the science of manufacturing machine intelligence. This award is supported by the Division of Civil, Mechanical and Manufacturing Innovation and the Office of Advanced Cyberinfrastructure.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

先进制造研究依赖于对产品模型的大型数据集的访问，以使产品设计师能够从过去的错误中学习，并发现和开发新的解决方案。然而，这些数据集通常被存档在无法访问的存储库中，并且可能描述得很差，难以被其他人使用。当前的制造业研究必须从孤立的产品制造数据存储库转向联合、分散、开放和互操作的方法。这种转变可以通过在每个物理端点嵌入网络功能来实现，无论是在产品设计师使用的桌面上还是在制造机器的控制系统中。该项目的目标是开发一个名为FabWave的以制造业为重点的试点网络基础设施。FabWave将从不同来源收集有关产品和制造过程的数字数据，特别是学术界和公共社区用户生成的三维（3D）计算机辅助设计（CAD）模型，形成一个新的丰富数据集，反过来，制造业研究人员和其他人将完全可以访问该数据集。FabWave的系统设计将由制造研究社区的需求驱动，该项目将鼓励学术用户，政府实验室和公众采用。FabWave旨在降低用户上传、共享和下载3D产品模型数据的障碍;它还将使制造科学研究人员能够访问信息丰富的数据集，用于测试和评估算法，以推进制造研究，并为社区提供构建定制应用程序的能力，为社区提供服务。该基础设施开发项目符合NSF的“利用数据促进21世纪世纪科学和工程大创意"愿景，可以提高美国在先进制造业的竞争力。FabWave项目中将构建的全新网络基础设施工具包括：1）设计软件中的直接插件，可以更轻松地捕获元数据，并将3D产品模型上传到FabWave存储库，只有有限的人机交互; 2）具有应用程序编程接口（API）工具的数据存储，以允许用户编写脚本来在存储库中搜索特定于他们的研究问题的内容。星际文件系统（IPFS）协议的创新使用沿着下一代非结构化数据库将为Fabwave的用户提供索引和搜索服务。该项目将演示如何使用FabWave开发面向社区的第三方应用程序和库。最终，研究社区将可以访问在研究实验室、课堂和其他开源项目中创建的丰富的产品数据集。这个数据网络，如果扩展到整个大学，将加速网络制造，工程系统设计和制造中的网络物理系统的进步。此外，FabWave将使制造信息集成和信息学的新研究领域与减少探索制造机器智能科学的障碍相结合。该奖项由土木、机械和制造业创新部门以及高级网络基础设施办公室支持。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Provisioned Data Distribution for Intelligent Manufacturing via Fog Computing

• DOI: 10.1016/j.promfg.2019.06.158
• 发表时间: 2019
• 期刊: Procedia Manufacturing
• 作者: Riddhiman Sherlekar;B. Starly;P. Cohen

Development of a Pilot Manufacturing Cyberinfrastructure With an Information Rich Mechanical CAD 3D Model Repository

开发具有信息丰富的机械 CAD 3D 模型存储库的试点制造网络基础设施

• DOI: 10.1115/msec2019-2882
• 发表时间: 2019
• 期刊: ASME 2019 14th International Manufacturing Science and Engineering Conference
• 作者: Bharadwaj, Akshay;Xu, Yang;Angrish, Atin;Chen, Yong;Starly, Binil
• 通讯作者: Starly, Binil