AR for Material Management and/or Supply Chain Flow with Work Orders

Many industries track supply chains and juggle limited supplies of components, ingredients, or materials while planning work orders in a system. Combining data with AR displays could provide up-to-date information to users while on the job and assist in distributing human resources according to availability of materials. In the Industrial Internet of Things (IIoT), a facility or job site that is nearing the end of materials or has just received a shipment of materials can bring this status information into the AR-assisted user’s field of view with updated work orders, reducing delays and optimizing use of resources and distribution of workers.

This topic explores how to better share information about materials, equipment, and tools tracked in operations management software, and, when there are mission critical updates, how to display to a user current information about materials. The user may receive a new work order, be warned about material shortages, or be notified of a new assignment to move materials between locations, for instance. In the latter use case, the user may receive AR-assisted navigation support.

When an AR-assisted user is made aware of status of materials in the supply chain, they are prepared to adapt and feel more satisfied. In addition, there is the potential for back-end IIoT systems to track the user’s location before sending instructions with respect to material availabilities.

This research topic explores different approaches to communicating and visualizing levels of materials in an IIoT context to study usability and impacts on worker productivity and satisfaction. It also examines integration of data from connected pallets and packaging and users’ devices with operational software to automatically track processes, check in/check out, and make recommendations for users and managers.

Stakeholders

Operators of manufacturing, repair, maintenance facilities, quality managers, managers of factories, providers of repair and maintenance services, oil and gas, power and energy, medical practitioners, experience designers, enterprise IT, systems integrators specializing in IIoT or Industry 4.0

Possible Methodologies

An experimental environment using a range of connected or smart tools and procedures will provide the suitable environment for this research. Users of Industrial Internet of Things (IIoT) or Industry 4.0 systems will perform tasks under controlled conditions. Motion and time studies, quality inspection and other measurements of performance will be used to quantify impacts. Users will complete surveys about satisfaction and feedback on various visualizations.

Research Program

This research topic is broad in scope. It can include exploring different approaches to visualize data about tools to better understand and document or compare usability. This would benefit the industry by establishing Industry 4.0 best practices or guidelines. The research could also include making, with AR device pairing, those tools without sensors or that are not connected, more detectable and/or intelligent. This would expand the types and number of existing tools that would be tracked, without the cost of replacing tools that were developed prior to Industry 4.0 adoption. It also can examine integration of data from tools and users’ devices with operational software to automatically track processes and provide remote assistance, quality control and recommendations for users and managers. Further, this topic can be combined with studies of AR-enabled guidance, integration of AR with IoT, finding parts and supplies in a large space with AR, 3D user interfaces, live sensor visualization for other use cases, and other use cases in factory or field settings.

Miscellaneous Notes

Two AREA members with financial support from both industry and government [MxD (in US), the Manufacturing Technology Center (MTC), and the AMRC (in UK)] have the required experimental environments and have already begun studying the approaches in this topic.

Keywords

Logistics data processing, materials management, supply chain management, logistics, asset tracing, asset tracking, asset management, Industrial Internet of Things (IIoT), usability, perception, work orders, productivity, navigation, interactive systems and tools, Internet of Things, supply chain, time difference of arrival, warehouse automation, logistics data processing, pallets, supply chain management, manufacturing, mapping

Research Agenda Categories

Business, Technology, Use Cases, End User and User Experience

Expected Impact Timeframe

Medium

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:

• Kocisko, M., Teliskova, M., Baron, P., & Zajac, J. (2017). An integrated working environment using advanced augmented reality techniques. 2017 4th International Conference on Industrial Engineering and Applications (ICIEA)
• Han, Y., Lee, C., Kim, S., & Ko, S. (2019). System Architecture for Progressive Augmented Reality (poster). Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services
• De S Ribeiro, M. G., Mazuecos, I. L., Marinho, F., & dos Santos, A. N. G. (2019). Agile Explorations in AR. IECON 2019 – 45th Annual Conference of the IEEE Industrial Electronics Society
• Haque, R., Islam, M. M., Salma, S., Al Jubair, M. A., & Weng, N. G. (2020). Extracting Relevant Information Using Handheld Augmented Reality. Proceedings of the International Conference on Computing Advancements
• Quandt, M., Beinke, T., & Freitag, M. (2020). User-Centered Evaluation of an Augmented Reality-based Assistance System for Maintenance. Procedia CIRP, 93, 921-926

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

Author

Christine Perey

Last Published (yyyy-mm-dd)

2021-08-31

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