ESTONIAN ACADEMY
PUBLISHERS
eesti teaduste
akadeemia kirjastus
PUBLISHED
SINCE 1952
 
Proceeding cover
proceedings
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2022): 0.9
Advancement in production engineering education through Virtual Learning Factory Toolkit concept; pp. 374–382
PDF | 10.3176/proc.2021.4.02

Authors
Kashif Mahmood, Tauno Otto, Vladimir Kuts, Walter Terkaj, Gianfranco Modoni, Marcello Urgo, Giorgio Colombo, Geza Haidegger, Peter Kovacs, Johan Stahre
Abstract

The growing relevance of digitalization in production requires the enhancement of human skills and competences in the field of Information and Communication Technology (ICT). Higher education has to cope with this need by providing the necessary ICT skills to future industrial engineers, so that they have a good understanding of the complexity of industries in the 21st century. This paper presents the conceptual development and testing of a Virtual Learning Factory Toolkit (VLFT) that integrates digital tools used in production management with engineering education. The digital tools integrated into the VLFT can help students to exploit enabling technologies such as simulation and virtual reality in their manufacturing studies and practical projects with industrial companies. Moreover, digital tools were tested by using a structured workflow that consists of different learning activities related to manufacturing system configuration. Students practised the digital tools with the help of use cases in the form of joint learning labs, after which the students’ feedback was collected and analysed.

References

1. Terkaj, W. and Tolio T. The Italian flagship project: factories of the future. In Factories of the Future (Tolio, T., Copani, G. and Terkaj, W., eds). Springer, Cham, 2019, 3–35. 
https://doi.org/10.1007/978-3-319-94358-9_1

2. World Trade Organization (WTO). World Trade Statistical Review 2018. 
https://www.wto.org/english/res_e/statis_e/ statis_e.htm

3. Storrie, D. The future of manufacturing in Europe. Eurofound, 2019. 
http://eurofound.link/fomeef18002

4. Kangru, T., Riives, J., Mahmood, K. and Otto, T. Suitability analysis of using industrial robots in manufacturing. Proc. Est. Acad. Sci., 2019, 68(4), 383–388.
https://doi.org/10.3176/proc.2019.4.06

5. Mahmood, K., Karaulova, T., Otto, T. and Shevtshenko, E. Development of cyber-physical production systems based on modelling technologies. Proc. Est. Acad. Sci., 2019, 68(4), 348–355.
https://doi.org/10.3176/proc.2019.4.02

6. Abele, E., Chryssolouris, G., Sihn, W., Metternich, J., ElMaraghy, H., Seliger, G. et al. Learning factories for future oriented research and education in manufacturing. CIRP Ann. Manuf. Technol., 2017, 66, 803–826.
https://doi.org/10.1016/j.cirp.2017.05.005

7. Wagner, U., AlGeddawy, T., ElMaraghy, H. and Müller, E. The state-of-the-art and prospects of learning factories. Procedia CIRP, 2012, 3, 109–114.
https://doi.org/10.1016/j.procir.2012.07.020

8. Baena, F., Guarin, A., Mora, J., Sauza, J. and Retat, S. Learning factory: the path to Industry 4.0. 7th Conference on Learning Factories. Procedia Manuf., 2017, 9, 73–80.
https://doi.org/10.1016/j.promfg.2017.04.022

9. Tvenge, N. and Ogorodnyk, O. Development of evaluation tools for learning factories in manufacturing education. 8th Conference on Learning Factories. Procedia Manuf., 2018, 23, 33–88.
https://doi.org/10.1016/j.promfg.2018.03.157

10. Pokhrel, S. and Chhetri, R. A literature review on impact of COVID-19 pandemic on teaching and learning. High. Educ. Future, 2021, 8(1), 133–141. 
https://doi.org/10.1177/2347631120983481

11. Caggiano, A. and Teti, R. Digital factory technologies for robotic automation and enhanced manufacturing cell design. Cogent Eng., 2018, 5(1), 1–14.
https://doi.org/10.1080/23311916.2018.1426676

12. Terkaj, W., Gaboardi, P., Trevisan, C., Tolio, T. and Urgo, M. A digital factory platform for the design of roll shop plants. CIRP J. Manuf. Sci. Technol., 2019, 26, 88–93.
https://doi.org/10.1016/j.cirpj.2019.04.007

13. Virtual Learning Factory Toolkit (VLFT). TalTech, 2020. 
https://www.vlft.eu

14. Urgo, M. and Terkaj, W. Formal modelling of release control policies as a plug-in for performance evaluation of manufacturing systems. CIRP Ann. Manuf. Technol., 2020, 69(1), 377–380.
https://doi.org/10.1016/j.cirp.2020.04.007

15. Bertoli, M., Casale, G. and Serazzi, G. JMT: performance engineering tools for system modelling. ACM SIGMETRICS Perform. Evaluation Rev., 2009, 36(4), 10–15.
https://doi.org/10.1145/1530873.1530877

16. Terkaj, W. OntoGui: A graphical user interface for rapid instantiation of OWL ontologies. CEUR Workshop Proc., 2017, 2050.

17. Unity. Unity Technologies, 2021. https://unity.com

18. Virtual Learning Factory Toolkit. VEB.js., 2021. 
https://virtualfactory.gitbook.io/virtual-learning-factory-toolkit/tools/vebjs

19. ApertusVR. 
http://apertusvr.org

20. Virtual Learning Factory Toolkit. GitBook, 2021. https:// virtualfactory.gitbook.io/virtual-learning-factory-toolkit

21. Spronken-Smith, R., Walker, R., Batchelor, J., O’Steen, B. and Angelo, T. Evaluating student perceptions of learning processes and intended learning outcomes under inquiry approaches. Assess. Eval. Higher Educ., 2012, 37(1), 57–72.
https://doi.org/10.1080/02602938.2010.496531

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