Effectiveness of machining equipment user guides: A comparative study of augmented reality and traditional media

Effectiveness of machining equipment user guides: A comparative study of augmented reality and traditional media


download PDF

Abstract. In the rapidly evolving landscape of manufacturing and material forming, innovative strategies are imperative for maintaining a competitive edge. Augmented Reality (AR) has emerged as a groundbreaking technology, offering new dimensions in how information is displayed and interacted with. It holds particular promise in the panel of instructional guides for complex machinery, potentially enhance traditional methods of knowledge transfer and operator training. Material forming, a key discipline within mechanical engineering, requires high-precision and skill, making it an ideal candidate for the integration of advanced instructional technologies like AR. This study aims to explore the efficiency of three distinct types of user manuals—video, paper, and augmented reality (AR)—on performance and acceptability in a material forming workshop environment. The focus will be on how AR can be specifically applied to improve task execution and understanding in material forming operations. Participants are mechanical engineering students specializing in material forming. They will engage in a series of standardized tasks related to machining processes. Performance will be gauged by metrics like task completion time and error rates, while task load will be assessed via the NASA Task Load Index (NASA-TLX) [1]. Acceptability of each manual type will be evaluated using the System Usability Scale (SUS) [2]. By comparing these various instructional formats, this research seeks to shed light on the most effective mediums for enhancing both operator performance and experience.

Augmented Reality, Instructions, Workload, Acceptability

Published online 4/24/2024, 9 pages
Copyright © 2024 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: GHOBRIAL Mina, SEITIER Philippe, LAGARRIGUE Pierre, GALAUP Michel, GILLES Patrick, Effectiveness of machining equipment user guides: A comparative study of augmented reality and traditional media, Materials Research Proceedings, Vol. 41, pp 2320-2328, 2024

DOI: https://doi.org/10.21741/9781644903131-255

The article was published as article 255 of the book Material Forming

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

[1] S. G. Hart and L. E. Staveland, “Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research,” in Advances in Psychology, vol. 52, Elsevier, 1988, pp. 139–183. doi: 10.1016/S0166-4115(08)62386-9
[2] A. Bangor, P. Kortum, and J. Miller, “Determining What Individual SUS Scores Mean: Adding an Adjective Rating Scale,” J. Usability Studies, vol. 4, no. 3, pp. 114–123, May 2009.
[3] E. Gandolfi, “Virtual Reality and Augmented Reality,” 2018, pp. 545–561.
[4] J. Butt, “Exploring the Interrelationship between Additive Manufacturing and Industry 4.0,” Designs, vol. 4, no. 2, p. 13, Jun. 2020. https://doi.org/10.3390/designs4020013
[5] M. Gonzalez-Franco, R. Pizzaro, J. Cermeron, K. Li, J. Thorn, W. Hutabarat, A. Tiwari, and P. Bermell-Garcia, “Immersive Mixed Reality for Manufacturing Training,” Front. Robot. AI, vol. 4, Feb. 2017. https://doi.org/10.3389/frobt.2017.00003
[6] J. K. Ostrander, C. S. Tucker, T. W. Simpson, and N. A. Meisel, “Evaluating the Use of Virtual Reality to Teach Introductory Concepts of Additive Manufacturing,” Journal of Mechanical Design, vol. 142, no. 5, p. 051702, May 2020. https://doi.org/10.1115/1.4044006
[7] M. Mogessie, S. D. Wolf, M. Barbosa, N. Jones, and B. M. McLaren, “Work-in-Progress—A Generalizable Virtual Reality Training and Intelligent Tutor for Additive Manufacturing,” in 2020 6th International Conference of the Immersive Learning Research Network (iLRN), San Luis Obispo, CA, USA: IEEE, Jun. 2020, pp. 355–358. doi: 10.23919/iLRN47897.2020.9155119
[8] C. Botto, A. Cannavo, D. Cappuccio, G. Morat, A. N. Sarvestani, P. Ricci, V. Demarchi, and A. Saturnino, “Augmented Reality for the Manufacturing Industry: The Case of an Assembly Assistant,” in 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Atlanta, GA, USA: IEEE, Mar. 2020, pp. 299–304. doi: 10.1109/VRW50115.2020.00068
[9] M. Sitko, B. Wesołowski, J. Adamus, Ł. Lisiecki, K. Piotrowska-Madej, and L. Madej, “Perceptive review of augmented reality applications and their outlooks in the forging industry,” cmms, vol. 20, no. 2, p. 72, 2020. https://doi.org/10.7494/cmms.2020.2.0656
[10] P. Seitier, P. Gilles, V. Boudier, M. Galaup, and P. Lagarrigue, “Getting started procedure of a NC machine simplified by the use of a mixed-reality training scenario,” MATEC Web Conf., vol. 368, p. 01018, 2022. https://doi.org/10.1051/matecconf/202236801018
[11] M. Ghobrial, P. Seitier, M. Galaup, P. Lagarrigue, and P. Gilles, “Simplification of an Additive Manufacturing Machine Implementation Using Its CAD Model and Mixed-Reality,” in Advances in Additive Manufacturing: Materials, Processes and Applications, T. Mabrouki, H. Sahlaoui, H. Sallem, F. Ghanem, and N. Benyahya, Eds., in Lecture Notes in Mechanical Engineering. , Cham: Springer Nature Switzerland, 2024, pp. 100–106. doi: 10.1007/978-3-031-47784-3_13