Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/47601
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dc.contributor.authorEscallada, Oscar-
dc.contributor.authorGEURTS, Eva-
dc.contributor.authorSolmaz, Serkan-
dc.contributor.authorMazmela, Maitane-
dc.contributor.authorLasa, Ganix-
dc.date.accessioned2025-10-27T09:34:56Z-
dc.date.available2025-10-27T09:34:56Z-
dc.date.issued2025-
dc.date.submitted2025-10-06T14:38:47Z-
dc.identifier.citationIFAC-PapersOnLine, 59 (10) , p. 2563 -2568-
dc.identifier.urihttp://hdl.handle.net/1942/47601-
dc.description.abstractDeveloping a highly competent workforce is essential for meeting the evolving demands of modern manufacturing. In this context, evaluating traditional and innovative training methods plays a critical role in enhancing the effectiveness of assembly processes. With a range of options-such as on-the-job training, classroom training and eXtended Reality solutions-it is critical to identify the most appropriate training approach for different contexts. Therefore, we performed a literature review and visited manufacturing companies to gain an overview of metrics involved in the assessment of training methods. To support this, we developed a comprehensive framework that guides the selection of such approaches. Our research identified key factors that contribute to training, which are integrated into the framework. The framework is designed to evolve alongside technological and contextual changes, allowing for ongoing adjustments as new strategies emerge or existing ones improve, such as decreasing Virtual Reality costs or personnel limitations impacting traditional training. This adaptability ensures the framework remains a reliable resource for making informed training decisions, tailored to specific needs while accounting for an ever-changing industrial landscape.-
dc.description.sponsorshipThis research is funded by EITManufacturing DoctoralSchool, andbyFlandersMakethroughtheproject SKILLEDWORKFORCE.-
dc.language.isoen-
dc.rights2025 The Authors. This is an open access article under the CC BY-NC-ND license-
dc.subject.otherIndustry 40-
dc.subject.otherKnowledge management in production-
dc.subject.otherDecision-support for human operators-
dc.subject.otherTraining methods-
dc.subject.otherAssembly training-
dc.subject.otherIndustry 50-
dc.titleBridging Tradition and Innovation in Training: Evaluating and Comparing Training Methods Through a Comprehensive Framework-
dc.typeJournal Contribution-
local.bibliographicCitation.conferencedateJune 30-July 3-
local.bibliographicCitation.conferencename11th IFAC Conference on Manufacturing Modelling, Management and Control-
local.bibliographicCitation.conferenceplaceTrondheim-
dc.identifier.epage2568-
dc.identifier.issue10-
dc.identifier.spage2563-
dc.identifier.volume59-
local.bibliographicCitation.jcatA1-
dc.relation.referencesBacca Acosta, J.L., Baldiris Navarro, S.M., Fabregat Gesa, R., Graf, S., et al. (2014). Augmented reality trends in education: a systematic review of research and applications. Journal of Educational Technology and Society, 2014, vol. 17, n´um. 4, p. 133-149. Brynjolfsson, E. and McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & company. Burke, L.A. and Hutchins, H.M. (2008). A study of best practices in training transfer and proposed model of transfer. Human resource development quarterly, 19(2), 107–128. Daling, L.M. and Schlittmeier, S.J. (2024). Effects of augmented reality-, virtual reality-, and mixed reality– based training on objective performance measures and subjective evaluations in manual assembly tasks: a scoping review. Human factors, 66(2), 589–626. Doolani, S., Owens, L., Wessels, C., and Makedon, F. (2020). VIS: An immersive virtual storytelling system for vocational training. Appl. Sci. (Basel). Freina, L. and Ott, M. (2015). A literature review on immersive virtual reality in education: state of the art and perspectives. In The international scientific conference elearning and software for education, volume 1, 10–1007. Huang, G., Qian, X., Wang, T., Patel, F., Sreeram, M., Cao, Y., Ramani, K., and Quinn, A.J. (2021). AdapTutAR: An adaptive tutoring system for machine tasks in augmented reality. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. ACM. doi:10.1145/3411764.3445283. Ip, H.H. and Li, C. (2015). Virtual reality-based learning environments: Recent developments and ongoing challenges. In Hybrid Learning: Innovation in Educational Practices: 8th International Conference, ICHL 2015, Wuhan, China, July 27-29, 2015, Proceedings 8, 3–14. Springer. Kaplan, A.D., Cruit, J., Endsley, M., Beers, S.M., Sawyer, B.D., and Hancock, P.A. (2021). The effects of virtual reality, augmented reality, and mixed reality as training enhancement methods: A meta-analysis. Hum. Factors. Liu, X.W., Li, C.Y., Dang, S., Wang, W., Qu, J., Chen, T., and Wang, Q.L. (2022). Research on training effectiveness of professional maintenance personnel based on virtual reality and augmented reality technology. Sustainability, 14(21), 14351. doi:10.3390/su142114351. Palmas, F., Labode, D., Plecher, D.A., and Klinker, G. (2019). Comparison of a gamified and non-gamified virtual reality training assembly task. In 2019 11th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games). IEEE. doi:10. 1109/vs-games.2019.8864583. Pimminger, S., Kurschl, W., Panholzer, L., and Sch¨onb¨ock, J. (2021). Exploring the learnability of assembly tasks using digital work instructions in a smart factory. Procedia CIRP, 104, 696–701. doi:https://doi.org/10.1016/j.procir.2021.11.117. Psarommatis, F., May, G., and Azamfirei, V. (2023). The role of human factors in zero defect manufacturing: a study of training and workplace culture. In IFIP International Conference on Advances in Production Management Systems, 587–601. Springer. Rold´an, J.J., Crespo, E., Mart´ın-Barrio, A., Pe˜na-Tapia, E., and Barrientos, A. (2019). A training system for industry 4.0 operators in complex assemblies based on virtual reality and process mining. Robot. Comput. Integr. Manuf. Schwab, K. (2017). The fourth industrial revolution. Crown Currency. V´elaz, Y., Rodr´ıguez Arce, J., Guti´errez, T., LozanoRodero, A., and Suescun, A. (2014). The influence of interaction technology on the learning of assembly tasks using virtual reality. J. Comput. Inf. Sci. Eng. Westerfield, G., Mitrovic, A., and Billinghurst, M. (2015). Intelligent augmented reality training for motherboard assembly. Int. J. Artif. Intell. Educ. Wolfartsberger, J., Zimmermann, R., Obermeier, G., and Niedermayr, D. (2023). Analyzing the potential of virtual reality-supported training for industrial assembly tasks. Computers in Industry, 147, 103838. doi:https:// doi.org/10.1016/j.compind.2022.103838.-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.identifier.doi10.1016/j.ifacol.2025.09.431-
local.provider.typePdf-
local.dataset.doi10.1016/j.ifacol.2025.09.431-
local.uhasselt.internationalyes-
item.contributorEscallada, Oscar-
item.contributorGEURTS, Eva-
item.contributorSolmaz, Serkan-
item.contributorMazmela, Maitane-
item.contributorLasa, Ganix-
item.fullcitationEscallada, Oscar; GEURTS, Eva; Solmaz, Serkan; Mazmela, Maitane & Lasa, Ganix (2025) Bridging Tradition and Innovation in Training: Evaluating and Comparing Training Methods Through a Comprehensive Framework. In: IFAC-PapersOnLine, 59 (10) , p. 2563 -2568.-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
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