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Competences for Cyber-physical Systems in Manufacturing – First Findings and Scenarios
Open accessAbstract
This paper presents research findings on competence needs for Cyber-Physical Systems (CPS) in manufacturing. These are from studies of the German Federal Ministry of Education and Research's initiative for early identification of skill needs (FreQueNz) as well as the Office of Technology Assessment at the German Bundestag (TAB). The findings are partly statements on possible future developments as – at least according to the mentioned studies during their periods of inquiry – the degree of CPS implementation in enterprises has been fairly low. Further development of CPS competence needs depends on which combinations of technologies and work organization will come to prevail in the enterprises in the course of broader implementation. As this seems rather open, two of the studies distinguish at least two ideal scenarios with regard to possible directions of competence developments. Within the first scenario more and more decisions would be taken by IT which would control the production employees. These are expected to intervene into the process in case of malfunctions only but cannot develop the respective competences during the trouble-free process. Within the second scenario the technology would serve as decision-supporting system to employees still expected to optimize and able to intervene into the process. Starting from a maturity model of innovations, the presentation of research findings in this paper is linked to a thesis on the added value of stronger links between technology forecasting and early identification of skill needs. By such links early identification of skill needs could be focused at an early stage on topics which are considered by technology forecasting to have major potential. This could help reducing skill gaps at the diffusion stage of technological innovations.
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Citations
Cited by
Literature review of Industry 4.0 and related technologies
Oztemel, E., & Gursev, S. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-018-1433-8 · Cited by 2,143
Longo, F., Padovano, A., & Umbrello, S. (2020) · Applied Sciences · doi:10.3390/app10124182 · Cited by 687
Kinkel, S., Baumgartner, M., & Cherubini, E. (2022) · Technovation · doi:10.1016/j.technovation.2021.102375 · Cited by 316
Fantini, P., Pinzone, M., & Taisch, M. (2020) · Computers & Industrial Engineering · doi:10.1016/j.cie.2018.01.025 · Cited by 298
Maturity Assessment for Industry 5.0: A Review of Existing Maturity Models
Hein-Pensel, F., Winkler, H., Brückner, A., Wölke, M., Jabs, I., Mayan, I. J., Kirschenbaum, A., Friedrich, J., & Zinke-Wehlmann, C. (2023) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.12.009 · Cited by 215
Metadata
- Authors
- Dworschak, B., & Zaiser, H.
- Venue
- Procedia CIRP
- Publisher
- Elsevier BV
- Published
- 2014
- Volume
- 25
- Pages
- 345-350
- ISSN
- 2212-8271 (ISSN-L)
- OpenAlex
- W1992965933
- Cited by
- 161
- References
- 0
- FWCI
- 15.07
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Dworschak, B., & Zaiser, H. (2014). Competences for Cyber-physical Systems in Manufacturing – First Findings and Scenarios. Procedia CIRP. https://doi.org/10.1016/j.procir.2014.10.048
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.