Augmented reality for machine monitoring in industrial manufacturing: framework and application developmentShow others and affiliations
2023 (English)In: Procedia CIRP, E-ISSN 2212-8271, p. 1327-1332Article in journal (Refereed) Published
Abstract [en]
Enhancing data visualization on the shop floor provides support for dealing with the increasing complexity of production and the need for progressing towards emerging goals like energy efficiency. It enables personnel to make informed decisions based on real-time data displayed on user-friendly interfaces. Augmented reality (AR) technology provides a promising solution to this problem by allowing for the visualization of data in a more immersive and interactive way. The aim of this study is to present a framework to visualize live and historic data about energy consumption in AR, using Power BI and Unity, and discuss the applications' capabilities. The study demonstrated that both Power BI and Unity can effectively visualize near-real-time machine data with the aid of appropriate data pipelines. While both applications have their respective strengths and limitations, they can support informed decision-making and proactive measures to improve energy utilization. Additional research is needed to examine the correlation between energy consumption and production dynamics, as well as to assess the user-friendliness of the data presentation for effective decision-making support.
Place, publisher, year, edition, pages
Elsevier, 2023. p. 1327-1332
Keywords [en]
augmented reality, data pipelines, energy efficiency, user interface, Visualization
National Category
Computer Sciences Computer Systems Other Engineering and Technologies not elsewhere specified
Research subject
User Centred Product Design
Identifiers
URN: urn:nbn:se:his:diva-23628DOI: 10.1016/j.procir.2023.09.171Scopus ID: 2-s2.0-85184584712OAI: oai:DiVA.org:his-23628DiVA, id: diva2:1839822
Conference
56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023 Cape Town 24 October 2023 through 26 October 2023
Projects
EXPLAIN
Note
CC BY-NC-ND 4.0 DEED
© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 56th CIRP International Conference on Manufacturing Systems 2023.
Correspondence Address: T. Schmitt; Scania CV AB, Smart Factory Lab, Södertälje, Verkstadsvägen 17, 151 38, Sweden; email: thomas.schmitt@scania.com
This paper is produced as part of the EXPLAIN project, which is partly funded by the Swedish research and development agency Vinnova.
2024-02-222024-02-222024-09-04Bibliographically approved