Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/48158Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | VAN DEN BERGH, Jan | - |
| dc.contributor.author | ALONSO LUIS, Hugo | - |
| dc.date.accessioned | 2026-01-16T10:50:25Z | - |
| dc.date.available | 2026-01-16T10:50:25Z | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2026-01-05T13:40:19Z | - |
| dc.identifier.citation | Wallner, Günter; She, James; Burch, Michael; Liang, Hai-Ning (Ed.). VINCI '25: Proceedings of the 18th International Symposium on Visual Information Communication and Interaction, Association for Computing Machinery, (Art N° 24) | - |
| dc.identifier.isbn | 9798400718458 | - |
| dc.identifier.uri | http://hdl.handle.net/1942/48158 | - |
| dc.description.abstract | High-mix low-volume manufacturing relies heavily on human assembly is important. To reduce the effects of human mistakes and to limit training time in a high-employment market, companies are looking into ways to let technology support operators to not only guide assembly but also inspection of work. Inline inspection (with digital guidance) can decrease the costs of rework or scrap production. We evaluate a mostly transparent augmented reality overlay of a product’s digital twin to support assembly and inline inspection in a formative within-subjects study with six operators. To isolate interface effects from AI performance, progress tracking and inspection were simulated via a Wizard-of-Oz setup. We discuss the results of the evaluation and present lessons learned. | - |
| dc.description.sponsorship | This research was supported by VLAIO (Flanders Innovation & Entrepreneurship) and Flanders Make, the strategic center for the manufacturing industry in Flanders, within the ICON-project QUALMA (HBC.2022-0415) “Quality Assurance for Large Manual Assembly”. | - |
| dc.language.iso | en | - |
| dc.publisher | Association for Computing Machinery | - |
| dc.relation.ispartofseries | VINCI | - |
| dc.rights | CC BY 4.0 | - |
| dc.subject.other | Augmented reality | - |
| dc.subject.other | Digital work instructions | - |
| dc.subject.other | Artificial intelligence | - |
| dc.subject.other | HoloLens 2 | - |
| dc.subject.other | Information visualization | - |
| dc.title | Visualizing a Digital Twin for Operators in High-Mix Low-Volume Manufacturing using Augmented Reality | - |
| dc.type | Proceedings Paper | - |
| local.bibliographicCitation.authors | Wallner, Günter | - |
| local.bibliographicCitation.authors | She, James | - |
| local.bibliographicCitation.authors | Burch, Michael | - |
| local.bibliographicCitation.authors | Liang, Hai-Ning | - |
| local.bibliographicCitation.conferencedate | 2025, December 1-3 | - |
| local.bibliographicCitation.conferencename | VINCI 2025 | - |
| local.bibliographicCitation.conferenceplace | Linz, Austria | - |
| local.format.pages | 5 | - |
| local.bibliographicCitation.jcat | C1 | - |
| local.publisher.place | New York, NY, USA | - |
| dc.relation.references | [1] Joao Bernardo Alves, Bernardo Marques, Paulo Dias, and Beatriz Sousa Santos. 2021. Using augmented reality for industrial quality assurance: a shop floor user study. The International Journal of Advanced Manufacturing Technology 115, 1 (2021), 105–116. https://doi.org/10.1007/s00170-021-07049-8 [2] Aaron Bangor, Philip T. Kortum, and James T. Miller. 2008. An Empirical Evaluation of the System Usability Scale. International Journal of Human–Computer Interaction 24, 6 (2008), 574–594. https://doi.org/10.1080/10447310802205776 [3] Jonas Blattgerste, Patrick Renner, Benjamin Strenge, and Thies Pfeiffer. 2018. InSitu Instructions Exceed Side-by-Side Instructions in Augmented Reality Assisted Assembly. In Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference (Corfu, Greece) (PETRA ’18). Association for Computing Machinery, New York, NY, USA, 133–140. https://doi.org/10.1145/3197768.3197778 [4] Michela Dalle Mura and Gino Dini. 2021. An augmented reality approach for supporting panel alignment in car body assembly. Journal of Manufacturing Systems 59 (2021), 251–260. https://doi.org/10.1016/j.jmsy.2021.03.004 [5] Hitesh Dhiman, Gustavo Alberto Rovelo Ruiz, Raf Ramakers, Danny Leen, and Carsten Röcker. 2024. Designing instructions using self-determination theory to improve motivation and engagement for learning craft. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems. ACM, New York, NY, USA, 16 pages. https://doi.org/10.1145/3613904.3642136 [6] Jon A. Fernández-Moyano, Inmaculada Remolar, and Águeda GómezCambronero. 2025. Augmented Reality’s Impact in Industry—A Scoping Review. Applied Sciences 15, 5 (2025), 23 pages. https://doi.org/10.3390/app15052415 [7] Santina Fortuna, Loris Barbieri, Emanuele Marino, and Fabio Bruno. 2024. A comparative study of Augmented Reality rendering techniques for industrial assembly inspection. Computers in Industry 155 (2024), 104057. https://doi.org/10.1016/j.compind.2023.104057 [8] Dorothy Gors, Merwan Birem, Roeland De Geest, Corentin Domken, Vasilios Zogopoulos, Steven Kauffmann, and Maarten Witters. 2021. An adaptable framework to provide AR-based work instructions and assembly state tracking using an ISA-95 ontology. Procedia CIRP 104 (2021), 714–719. https://doi.org/10.1016/j.procir.2021.11.120 [9] Dorothy Gors, Jeroen Put, Bram Vanherle, Maarten Witters, and Kris Luyten. 2021. Semi-automatic extraction of digital work instructions from CAD models. Procedia CIRP 97 (2021), 39–44. https://doi.org/10.1016/j.procir.2020.05.202 [10] AIAG&VDA Handbook. 2019. Failure mode and effects analysis-FMEA handbook: design FMEA, process FMEA, supplemental FMEA for monitoring et system response. [11] Florian Jasche, Sven Hoffmann, Thomas Ludwig, and Volker Wulf. 2021. Comparison of Different Types of Augmented Reality Visualizations for Instructions. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 131, 13 pages. https://doi.org/10.1145/3411764.3445724 [12] Bui Minh Khuong, Kiyoshi Kiyokawa, Andrew Miller, Joseph J. La Viola, Tomohiro Mashita, and Haruo Takemura. 2014. The effectiveness of an AR-based contextaware assembly support system in object assembly. In 2014 IEEE Virtual Reality (VR). IEEE, 57–62. https://doi.org/10.1109/VR.2014.6802051 [13] Enrico Andrea Laviola, Michele Gattullo, Vito Modesto Manghisi, Michele Fiorentino, and Antonio Emmanuele Uva. 2022. Minimal AR: visual asset optimization for the authoring of augmented reality work instructions in manufacturing. The International Journal of Advanced Manufacturing Technology 119, 3 (2022), 1769–1784. https://doi.org/10.1007/s00170-021-08449-6 [14] Shufei Li, Pai Zheng, and Lianyu Zheng. 2021. An AR-Assisted Deep LearningBased Approach for Automatic Inspection of Aviation Connectors. IEEE Transactions on Industrial Informatics 17, 3 (2021), 1721–1731. https://doi.org/10.1109/TII.2020.3000870 [15] Shimin Liu, Shanyu Lu, Jie Li, Xuemin Sun, Yuqian Lu, and Jinsong Bao. 2021. Machining process-oriented monitoring method based on digital twin via augmented reality. The International Journal of Advanced Manufacturing Technology 113 (2021), 3491–3508. https://doi.org/10.1007/s00170-021-06838-5 [16] Emanuele Marino, Loris Barbieri, Fabio Bruno, and Maurizio Muzzupappa. 2024. Assessing user performance in augmented reality assembly guidance for industry 4.0 operators. Computers in Industry 157-158 (2024), 104085. https://doi.org/10.1016/j.compind.2024.104085 [17] Emanuele Marino, Loris Barbieri, Biagio Colacino, Anna Kum Fleri, and Fabio Bruno. 2021. An Augmented Reality inspection tool to support workers in Industry 4.0 environments. Computers in Industry 127 (2021), 13 pages. https://doi.org/10.1016/j.compind.2021.103412 [18] Benedikt G Mark, Erwin Rauch, and Dominik T Matt. 2021. Worker assistance systems in manufacturing: A review of the state of the art and future directions. Journal of Manufacturing Systems 59 (2021), 228–250. https://doi.org/10.1016/j.jmsy.2021.02.017 [19] Raf Menten, Gustavo Rovelo Ruiz, and Davy Vanacken. 2025. NexOz - A Wizard of Oz Approach to Facilitate the Integration of AI in Interactive Systems. In Engineering Interactive Computer Systems. EICS 2024 International Workshops, Luciana Zaina, José Creissac Campos, Davide Spano, Kris Luyten, Philippe Palanque, Gerrit van der Veer, Achim Ebert, Shah Rukh Humayoun, and Vera Memmesheimer (Eds.). Springer Nature Switzerland, Cham, 110–125. https://doi.org/10.1007/978-3-031-91760-8_8 [20] Microsoft. 2023. Mixed reality toolkit 3 developer documentation - MRTK3. Retrieved August 21, 2025 from https://learn.microsoft.com/en-us/windows/mixed-reality/mrtk-unity/mrtk3-overview/ [21] Leon Pietschmann, Michel Schimpf, Zhu-Tian Chen, Hanspeter Pfister, and Thomas Bohné. 2025. Enhancing User Performance and Human Factors through Visual Guidance in AR Assembly Tasks. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’25). Association for Computing Machinery, New York, NY, USA, Article 226, 8 pages. https://doi.org/10.1145/3706599.3720094 [22] Matthias Schröder and Helge Ritter. 2017. Deep learning for action recognition in augmented reality assistance systems. In ACM SIGGRAPH 2017 Posters (Los Angeles, California) (SIGGRAPH ’17). Association for Computing Machinery, New York, NY, USA, Article 75, 2 pages. https://doi.org/10.1145/3102163.3102191 [23] Serkan Solmaz, Rik Henderickx, Jan Van den Bergh, and Merwan Birem. 2024. Capturing the system requirements for adopting Industry 5.0 in quality inspection: an evidence-based approach. Procedia CIRP 128 (2024), 369–374. https://doi.org/10.1016/j.procir.2024.03.016 [24] Keishi Tainaka, Yuichiro Fujimoto, Taishi Sawabe, Masayuki Kanbara, and Hirokazu Kato. 2023. Selection framework of visualization methods in designing AR industrial task-support systems. Computers in Industry 145 (2023), 103828. https://doi.org/10.1016/j.compind.2022.103828 [25] Arthur Tang, Charles Owen, Frank Biocca, and Weimin Mou. 2003. Comparative effectiveness of augmented reality in object assembly. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Ft. Lauderdale, Florida, USA) (CHI ’03). Association for Computing Machinery, New York, NY, USA, 73–80. https://doi.org/10.1145/642611.642626 [26] Jan Van den Bergh, Jorge Rodríguez-Echeverría, and Sidharta Gautama. 2024. Towards a Smart Combination of Human and Artificial Intelligence for Manufacturing. In Design for Equality and Justice, Anna Bramwell-Dicks, Abigail Evans, Marco Winckler, Helen Petrie, and José Abdelnour-Nocera (Eds.). Springer Nature Switzerland, Cham, 20–30. https://doi.org/10.1007/978-3-031-61688-4_3 [27] Yue Yin, Pai Zheng, Chengxi Li, and Lihui Wang. 2023. A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformation. Robotics and Computer-Integrated Manufacturing 81 (2023), 21 pages. https://doi.org/10.1016/j.rcim.2022.102515 | - |
| local.type.refereed | Refereed | - |
| local.type.specified | Proceedings Paper | - |
| local.bibliographicCitation.artnr | 24 | - |
| dc.identifier.doi | 10.1145/3769534.3769549 | - |
| local.provider.type | CrossRef | - |
| local.bibliographicCitation.btitle | VINCI '25: Proceedings of the 18th International Symposium on Visual Information Communication and Interaction | - |
| local.uhasselt.international | no | - |
| item.contributor | VAN DEN BERGH, Jan | - |
| item.contributor | ALONSO LUIS, Hugo | - |
| item.accessRights | Open Access | - |
| item.fullcitation | VAN DEN BERGH, Jan & ALONSO LUIS, Hugo (2025) Visualizing a Digital Twin for Operators in High-Mix Low-Volume Manufacturing using Augmented Reality. In: Wallner, Günter; She, James; Burch, Michael; Liang, Hai-Ning (Ed.). VINCI '25: Proceedings of the 18th International Symposium on Visual Information Communication and Interaction, Association for Computing Machinery, (Art N° 24). | - |
| item.fulltext | With Fulltext | - |
| Appears in Collections: | Research publications | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| vinci_2025_paper.pdf | Published version | 1.67 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.