Systems Integration between PLM Systems and AR

Significant AR experience development effort and time is dedicated to linking domain-specific data to AR engines and presentation systems. While many industries invest in AR scene development, the need is especially high in the manufacturing industry. Product Lifecycle Management (PLM) software systems curate design, manufacturing, and sustainment information related to a product system (ideally) throughout its entire lifecycle.

Leveraging such data across PLM systems for industrial AR has mainly become a platform-specific exercise. Commercial PLM software vendors provide industrial AR solutions that leverage their application programming interfaces (APIs) to help establish AR scenes. However, most large original equipment manufacturers (OEMs) operate in complex, global, and heavily distributed supply chains. In other words, in many cases, OEMs subscribe to every major commercial PLM software platform to handle the variety of data representations provided by their suppliers. This is especially important if the developers aim to truly create a digital twin of a product or production system.

This research topic will develop and test a standard data model that permits the vendor-neutral exchange of AR-critical data to produce updatable, sustainable, and maintainable AR scenes. One particular area of interest is understanding the proper handling of industrial animations. Though AR standards provide representations for presenting animations within AR scenes, for example, they do not directly relate to product system animations stored within PLM systems. Rather than relying on a particular PLM platform’s data representations, if such a data model was successfully developed, software developers would be able to exchange data across PLM software and to platform-agnostic AR engines more readily.

Stakeholders

OEM manufacturers, integrated solution and software developers, CAD/CAM providers, engineering design teams, PLM software publishers.

Possible Methodologies

This research topics could focus on testing existing PLM platforms and their AR-related competencies. Reporting on gaps bewteen the interfaces across related software tools will be a strong contribution. Existing standard data representations provide a strong starting point for investigation. Focusing on dealing with sustainment for digital twin models would cover lots of the use cases.

Research Program

OEMs with complex and heavily distributed supply chains should be a center point for the project. Program managers and technical advisors in such organizations understand the issue of cumbersome technical data packages. This research topic significantly overlaps with the Digital Model Interoperability research topic. [BB: issue with sentence grammar] There are distinct in that this research topic is specific to the manufacturing industry. The Digital Model Interoperability research topic relates more generally to 3D asset translation and can be applied to other domains, such as construction.

Miscellaneous Notes

There exist resources to help position research efforts. For example, the CAx Implementor Forum provides a number of test cases. The Khronos Group is continously updating glTF, the latest de-facto standard for lightweight model presentation. ASME Y14 is a working group that focuses on the standard presentaiton of GD&T annotations.

Keywords

Standards, data interoperability, digital twin, product lifecycle management, platform-agnostic AR solutions, application programming interfaces, distributed supply chains, manufacturing, sustainment, industrial Internet of Things, IIoT, ontologies (artificial intelligence), cost engineering, knowledge engineering, information management, project management, supply chains, team working, asset management, metadata, application programming interfaces, open source software, design engineering, systems engineering, cad/cam, quality management, supply chain management, manufacturing industries, product life cycle management, standardization, interoperability

Research Agenda Categories

Standards, Technology, Industries

Expected Impact Timeframe

Near

Related Publications

Using the words in this topic description and Natural Language Processing analysis of publications in the AREA FindAR database, the references below have the highest number of matches with this topic:

• Eckertz, D., Berssenbrügge, J., Anacker, H., & Dumitrescu, R. (2019). Work-in-Progress: Enhancing Collaboration Using Augmented Reality Design Reviews for Product Validation on the Example of Additive Manufacturing. Cyber-Physical Systems and Digital Twins, 244-254.
• Speicher, M., Hall, B. D., Yu, A., Zhang, B., Zhang, H., Nebeling, J., & Nebeling, M. (2018). XD-AR. Proceedings of the ACM on Human-Computer Interaction, 2(EICS), 1-24.
• Tobias Küster; Nils Masuch; Johannes Fahndrich; Gudrun Tschirner-Vinke; Jan Taschner; Markus Specker; Hendrik Iben. A Distributed Architecture for Modular and Dynamic Augmented Reality Processes. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).
• Bellalouna, F. (2020). Industrial Use Cases for Augmented Reality Application. 2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom).
• Zigart, T., & Schlund, S. (2020). Evaluation of Augmented Reality Technologies in Manufacturing – A Literature Review. Advances in Human Factors and Systems Interaction, 75-82.

More publications can be explored using the AREA FindAR research tool.

Author

Bill Bernstein

Last Published (yyyy-mm-dd)

2021-08-31

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