Abstract
To stay competitive, manufacturing companies are developing towards Smart Production which requires the use of digital technologies. However, there is a lack of guidance supporting manufacturing companies in selecting and integrating a combination of suitable digital technologies, which is required for Smart Production. To address this gap, the purpose of this paper is twofold: (i) to identify the main challenges of selecting and integrating digital technologies for Smart Production, and (ii) to propose a holistic concept to support manufacturing companies in mitigating identified challenges in order to select and integrate a combination of digital technologies for Smart Production. This is accomplished by using a qualitative-based multiple case study design. This paper identifies current challenges related to selection and integration of digital technologies. To overcome these challenges and achieve Smart production, the concept of data value chain was proposed, i.e., a holistic approach to systematically map and improve data flows within the production system.
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References
Choi, T.-M., Kumar, S., Yue, X., Chan, H. L.: Disruptive technologies and operations management in the industry 4.0 era and beyond. Product. Oper. Manag. 31(1), 9–31 (2022)
Alavian, P., Eun, Y., Meerkov, S.M., Zhang, L.: Smart production systems: automating decision-making in manufacturing environment. Int. J. Prod. Res. 58(3), 828–845 (2020)
Tao, F., Qi, Q., Liu, A., Kusiak, A.: Data-driven smart manufacturing. J. Manuf. Syst. 48, 157–169 (2018)
Klingenberg, C.O., Borges, M.A.V., Antunes, J.A.V.: Industry 4.0 as a data-driven paradigm: a systematic literature review on technologies. J. Manufact. Technol. Manag. 32(3), 570–592 (2019)
Silva, J., Silva, F., Silva, D., Rocha, L., Ritter, Á.: Decision making in the process of choosing and deploying industry 4.0 technologies. Gestão Produção 29, (2022)
Sjödin, D.R., Parida, V., Leksell, M., Petrovic, A.: Smart factory implementation and process innovation. Res. Technol. Manag. 61(5), 22–30 (2018)
Gopalakrishnan, S., Bierly, P., Kessler, E.H.: A reexamination of product and process innovations using a knowledge-based view. J. High Technol. Managem. Res. 10(1), 147–166 (1999)
Müller, J.M., Kiel, D., Voigt, K.-I.: What drives the Implementation of Industry 4.0? the role of opportunities and challenges in the context of sustainability. Sustainability 10(1), 247 (2018)
Berger, S., Denner, M.S., Röglinger, M.: The nature of digital technologies - Development of a multi-layer taxonomy. In: 26th European Conference on Information Systems (2018)
Schuh, G., Anderl, R., Dumitrescu, R., Krüger, A., ten Hompel, M.: Industrie 4.0 Maturity Index: Managing the Digital Transformation of Companies. Munich (2020)
Kache, F., Seuring, S.: Challenges and opportunities of digital information at the intersection of big data analytics and supply chain management. Int. J. Oper. Prod. Manag. 37(1), 10–36 (2017)
Yin, R.K.: Case Study Research and Applications: Design and Methods. Sage, Los Angeles (2018)
Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3, 77–101 (2006)
Takeda, H., Veerkamp, P., Yoshikawa, H.: Modeling design process. AI Mag. 11(4), 37 (1990)
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Agerskans, N., Bruch, J., Chirumalla, K., Ashjaei, M. (2022). Enabling Smart Production: The Role of Data Value Chain. In: Kim, D.Y., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. APMS 2022. IFIP Advances in Information and Communication Technology, vol 664. Springer, Cham. https://doi.org/10.1007/978-3-031-16411-8_55
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DOI: https://doi.org/10.1007/978-3-031-16411-8_55
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