Hostname: page-component-848d4c4894-xm8r8 Total loading time: 0 Render date: 2024-07-04T14:54:59.108Z Has data issue: false hasContentIssue false
  • English
  • Français

BARRIERS FROM A SOCIO-TECHNICAL PERSPECTIVE TO IMPLEMENT DIGITALISATION IN INDUSTRIAL ENGINEERING PROCESSES – A LITERATURE REVIEW

Published online by Cambridge University Press:  19 June 2023

Malin Hane Hagström ,
Dag Bergsjö  and
Henrik Wahrén
Malin Hane Hagström*
Affiliation:
Chalmers University of Technology
Dag Bergsjö
Affiliation:
Chalmers University of Technology
Henrik Wahrén
Affiliation:
Chalmers University of Technology
*
Hane Hagström, Malin, Chalmers University of Technology, Sweden, hanem@chalmers.se

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

With the paradigm shift towards Industry 4.0 and digitalisation, manufacturing engineers face several unexplored challenges; in the products for which they are designing production, in the equipment they are designing to realise production systems and in the digitalisation impact on engineering processes. Today's manufacturing system design processes are still based on traditional engineering methods and have difficulties to cope with increased complexity. The aim of this systematic literature review is to explore drivers and barriers to implement digitalisation in engineering processes from a socio-technical perspective. The identified general barriers were cyber security, lack of competence, lack of standards, large investments and resistance to change. For the engineering processes the main drivers were increased product complexity, servitisation, data driven design and engineering productivity, with the main barriers culture, excess amount of data, integration of tools. cyber security and data quality. The study shows the complexity of the challenge, and that it is not only the technology that is the top barrier. Further research is recommended to develop approaches of successful engineering digitalisation implementations.

Keywords

Design methodsIndustrial designHuman behaviour in designIndustry 4.0Manufacturing engineering digitalization
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 737 - 746
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Bakhtari, A. R., Waris, M. M., Sanin, C., & Szczerbicki, E. (2021). Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Process. Cybernetics and Systems, 52(5), 350–378. https://doi.org/10.1080/01969722.2020.1871226CrossRefGoogle Scholar
Blessing, L., & Chakrabati, A. (2009). DRM, a Design Research Methodology (1 ed.). Springer.CrossRefGoogle Scholar
Bucciarelli, L. L. (1994). Designing Engineers. MIT Press.Google Scholar
Buckl, S., Matthes, F., & Schweda, C. M. (2011, 2011//). Socio-technic Dependency and Rationale Models for the Enterprise Architecture Management Function. Advanced Information Systems Engineering Workshops, Berlin, Heidelberg.CrossRefGoogle Scholar
Calabrese, A., Dora, M., Levialdi Ghiron, N., & Tiburzi, L. (2020). Industry's 4.0 transformation process: how to start, where to aim, what to be aware of. Production Planning & Control, 1–21. https://doi.org/10.1080/09537287.2020.1830315Google Scholar
Cugno, M., Castagnoli, R., & Büchi, G. (2021). Openness to Industry 4.0 and performance: The impact of barriers and incentives. Technological Forecasting and Social Change, 168, 120756. https://doi.org/10.1016/j.techfore.2021.120756CrossRefGoogle Scholar
De Weck, O. L., Roos, D., Magee, C. L., Vest, C. M., & Moses, J. (2016). Engineering Systems: Meeting Human Needs in a Complex Technological World. MIT Press.Google Scholar
Eckert, C., Isaksson, O., Calandra, E., Coeckelbergh, M., & Hane Hagström, M. (2020). Data Fairy in Engineering Land: The Magic of Data Analysis as a Sociotechnical Process in Engineering Companies. Journal of Mechanical Design, 142(12).CrossRefGoogle Scholar
Fonseca, L. (2018). Industry 4.0 and the digital society: concepts, dimensions and envisioned benefits. Proceedings of the International Conference on Business Excellence, 12, 386–397. https://doi.org/10.2478/picbe-2018-0034CrossRefGoogle Scholar
Glass, R., Meissner, A., Gebauer, C., Stürmer, S., & Metternich, J. (2018). Identifying the barriers to Industrie 4.0. Procedia CIRP, 72, 985–988. https://doi.org/10.1016/j.procir.2018.03.187CrossRefGoogle Scholar
Hallstedt, S., Isaksson, O., & Öhrwall Rönnbäck, A. (2020). The Need for New Product Development Capabilities from Digitalization, Sustainability, and Servitization Trends. Sustainability, 12(23). https://doi.org/10.3390/su122310222Google Scholar
Hiebl, M. R. W. (2021). Sample Selection in Systematic Literature Reviews of Management Research. Organizational Research Methods, 1094428120986851. https://doi.org/10.1177/1094428120986851CrossRefGoogle Scholar
Horváth, D., & Szabó, R. Z. (2019). Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological Forecasting and Social Change, 146, 119–132. https://doi.org/10.1016/j.techfore.2019.05.021CrossRefGoogle Scholar
Huang, J., Gheorghe, A., Handley, H. A. H., Pazos, P., Pinto, A., Kovacic, S. F., Collins, A., Keating, C., Sousa-Poza, A., Rabadi, G., Unal, R., Cotter, T., Landaeta, R., & Daniels, C. (2020). Towards Digital Engineering - The Advent of Digital Systems Engineering. ArXiv, abs/2002.11672.CrossRefGoogle Scholar
Isaksson, O., Hallstedt, S., & Rönnbäck, A. (2018). Digitalisation, sustainability and servitisation: Consequences on product development capabilities in manufacturing firms. Proceedings of NordDesign 2018 Linköping Sweden.,Google Scholar
Kumar, S., Suhaib, M., & Asjad, M. (2020). Narrowing the barriers to Industry 4.0 practices through PCA-Fuzzy AHP-K means. Journal of Advances in Management Research.Google Scholar
Kumar, V., Vrat, P., & Shankar, R. (2021). Prioritization of strategies to overcome the barriers in Industry 4.0: a hybrid MCDM approach. Opsearch, 1–40.Google Scholar
Kügler, P., Schleich, B., & Wartzack, S. (2018). Consistent digitalization of engineering design – an ontology-based approach. DS 91: Proceedings of NordDesign 2018, Linköping, Sweden.,Google Scholar
Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242. https://doi.org/10.1007/s12599-014-0334-4CrossRefGoogle Scholar
Marques, M., Agostinho, C., Zacharewicz, G., & Jardim-Gonçalves, R. (2017). Decentralized decision support for intelligent manufacturing in Industry 4.0. JAISE, 9, 299–313. https://doi.org/10.3233/AIS-170436Google Scholar
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372. https://doi.org/10.1136/bmj.n71Google ScholarPubMed
Pedó, B., Brandalise, F. M. P., Viana, D. D., Tzortzopoulos, P., Formoso, C. T., & Whitelock-Wainwright, A. (2020, 2020/07/06). Digital Visual Management Tools in Design Management. Proc. 28th Annual Conference of the International Group for Lean Construction (IGLC), Berkeley, California, USA.CrossRefGoogle Scholar
Peetz, D. (2019). The Realities and Futures of Work. ANU Press.CrossRefGoogle Scholar
Petticrew, M., & Roberts, H. (2006). Systematic Reviews in the Social Sciences a Practical Guide. Blackwell Pub.CrossRefGoogle Scholar
Raj, A., Dwivedi, G., Sharma, A., Lopes de Sousa Jabbour, A. B., & Rajak, S. (2020). Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 224, 107546. https://doi.org/10.1016/j.ijpe.2019.107546CrossRefGoogle Scholar
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039CrossRefGoogle Scholar
Star, S. L. (2010). This is Not a Boundary Object: Reflections on the Origin of a Concept. Sci. Technol. Hum. Values, 35(5). https://doi.org/10.1177/0162243910377624Google Scholar
Stark, R., Kind, S., & Neumeyer, S. (2017). Innovations in digital modelling for next generation manufacturing system design. Cirp Annals-manufacturing Technology, 66, 169–172.CrossRefGoogle Scholar
Stornelli, A., Ozcan, S., & Simms, C. (2021). Advanced manufacturing technology adoption and innovation: A systematic literature review on barriers, enablers, and innovation types. Research Policy, 50(6), 104229. https://doi.org/10.1016/j.respol.2021.104229CrossRefGoogle Scholar