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Industry 4.0 Management: Preliminary Design Implications

Published online by Cambridge University Press:  26 May 2022

R. Castagnoli*
Affiliation:
University of Turin, Italy
J. Stal-Le Cardinal
Affiliation:
CentraleSupélec, France
G. Büchi
Affiliation:
University of Turin, Italy
M. Cugno
Affiliation:
University of Turin, Italy

Abstract

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Industry 4.0 is expected to change competitiveness of manufacturing firms. However, to completely achieve this goal, firms should manage barriers and complexity issues that my hinder its adoption or its effects. For this reason, the study explores, through a literature review, whether and how design theory may be a supporting theory to manage Industry 4.0 adoption and implementation to maximise the opportunities and minimise the risks. The results shows that these research questions require a design approach to innovate not only adopting technologies but reinventing the business practices.

Type
Article
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), 2022.

References

Bi, Z., Zhang, W. J., Wu, C., Luo, C., & Xu, L. (2021). Generic Design Methodology for Smart Manufacturing Systems from a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems. Machines, 9(10), 208.Google Scholar
Breque, M., De Nul, L., Petridis, A. (2020), Industry 5.0: Towards a sustainable, human-centric and resilient European industry. Directorate-General for Research and Innovation, European Commission,Google Scholar
Büchi, G., Cugno, M., Castagnoli, R. (2020). Smart factory performance, Technological Forecasting and Social Change, 150, 119790.CrossRefGoogle Scholar
Cabanes, B., Hubac, S., Le Masson, P., & Weil, B. (2021). Improving reliability engineering in product development based on design theory: the case of FMEA in the semiconductor industry. Research in Engineering Design, 32(3), 309329.CrossRefGoogle Scholar
Castagnoli, R., Buchi, G., Cugno, M., & Stal-Le Cardinal, J. (2020). Managing Complexity in Industry 4.0 Based Systems: A Qualitative Analysis. In 11th Complex Systems Design & Management (CSD&M) Conference (pp. 111).Google Scholar
Chauhan, C., Singh, A., & Luthra, S. (2021). Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 285, 124809.Google 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.CrossRefGoogle Scholar
Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, 383394.CrossRefGoogle Scholar
Egger, G., Rauch, E., Matt, D. T., & Brown, C. A. (2017). (Re-) Design of a Demonstration Model for a Flexible and Decentralized Cyber-Physical Production System (CPPS). In MATEC Web of Conferences (Vol. 127, p. 01016). EDP Sciences.CrossRefGoogle Scholar
Eisenhardt, K. M. (1989). Building theories from case study research. Academy of management review, 14(4), 532550.CrossRefGoogle Scholar
Harlé, H., Hooge, S., Le Masson, P., Levillain, K., Weil, B., Bulin, G., & Ménard, T. (2022). Innovative design on the shop floor of the Saint-Nazaire Airbus factory. Research in Engineering Design, 118.CrossRefGoogle Scholar
Harlé, H., Le Masson, P., & Weil, B. (2021). A Model of Creative Heritage for Industry: Designing New Rules while Preserving the Present System of Rules. Proceedings of The Design Society, 1, 141150.CrossRefGoogle Scholar
Hatchuel, Armand, Le Masson, Pascal, Reich, Yoram, et Subrahmanian, Eswaran, “Design theory: a foundation of a new paradigm for design science and engineering,” Research in Engineering Design 29 (2017): 521.CrossRefGoogle Scholar
Hatchuel, A., Weil, B., & Le Masson, P. (2013). Towards an ontology of design: lessons from C–K design theory and Forcing. Research in engineering design, 24(2), 147163.Google 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, 119132.CrossRefGoogle Scholar
Hwang, D., Blake Perez, K., Anderson, D., Jensen, D., Camburn, B., & Wood, K. (2021). Design Principles for Additive Manufacturing: Leveraging Crowdsourced Design Repositories. Journal of Mechanical Design, 143(7).CrossRefGoogle Scholar
Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing the strategic initiative Industrie 4.0: Final report of the Industrie 4.0 Working Group. Forschungsunion: Berlin, Germany.Google Scholar
Le Masson, P, Hatchuel, A, Weil, B (2011) The Interplay Betwee creativity issues and design theories: a new perspective for design management studies? Creativity Innovation Management 20(4):217237.CrossRefGoogle Scholar
Margherita, E. G., & Braccini, A. M. (2021). Managing the fourth industrial revolution: A competence framework for smart factory. In The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success (pp. 389402). Springer, Cham.CrossRefGoogle Scholar
Mourtzis, D., Fotia, S., Boli, N., & Vlachou, E. (2019). Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study. International Journal of Production Research, 57(22), 69086921.CrossRefGoogle Scholar
Paul, J., & Criado, A. R. (2020). The art of writing literature review: What do we know and what do we need to know?. International Business Review, 29(4), 101717.CrossRefGoogle Scholar
Pessoa, M. V. P. (2020). Smart design engineering: leveraging product design and development to exploit the benefits from the 4th industrial revolution. Design Science, 6.Google Scholar
Plehn, C., Stein, F., & Reinhart, G. (2015). Modeling factory systems using graphs-ontology-based design of a domain specific modeling approach. In DS 80-4 Proceedings of the 20th International Conference on Engineering Design (ICED 15) Vol 4: Design for X, Design to X, Milan, Italy, 27-30.07. 15 (pp. 163172).Google Scholar
Raj, A., Dwivedi, G., Sharma, A., de Sousa Jabbour, A. B. L., & 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.CrossRefGoogle Scholar
Rauch, E., Dallasega, P., & Matt, D. T. (2018). Complexity reduction in engineer-to-order industry through real-time capable production planning and control. Production Engineering, 12(3), 341352.CrossRefGoogle Scholar
Reich, Y., & Subrahmanian, E. (2015). Designing PSI: an introduction to the PSI framework.Google Scholar
Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group, 9(1), 5489.Google Scholar
Sanderson, D., Chaplin, J. C., & Ratchev, S. (2019). A Function-Behaviour-Structure design methodology for adaptive production systems. The International Journal of Advanced Manufacturing Technology, 105(9), 37313742.CrossRefGoogle Scholar
Coghlan, D., & Shani, A. B. (2008). Collaborative management research through communities of inquiry: Challenges and skills. Shani AB (Rami), Mohrman SA, Pasmore WA, Stymne B., Adler N.(Eds.) Handbook of Collaborative Management Research, Thousand Oaks (CA): Sage.Google Scholar
Stentoft, J., Adsbøll Wickstrøm, K., Philipsen, K., & Haug, A. (2020). Drivers and barriers for Industry 4.0 readiness and practice: empirical evidence from small and medium-sized manufacturers. Production Planning & Control, 118.Google Scholar
Ullah, A. S. (2020). What is knowledge in Industry 4.0?. Engineering Reports, 2(8), e12217.CrossRefGoogle Scholar
Yin, R. K. (2009). Case study research: Design and methods (Vol. 5). sage.Google Scholar