The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Defining and assessing industry 4.0 maturity levels – case of the defence sector
Open accessAbstract
Firms do not currently fully appreciate the complex characteristics of Industry 4.0 and as a result are uncertain about what it represents for them. In this study, an assessment model is developed to measure the level of implementation of Industry 4.0 technologies, around three dimensions: ‘Factory of the Future’, ‘People and Culture’, and ‘Strategy’. The ‘Factory of the Future’ is the main dimension and is composed of eight attributes: Additive Manufacturing, Cloud, Manufacturing Execution System, Internet of Things and Cyber Physical Systems, Big Data, Sensors, e-Value Chains, and Autonomous Robots. The study uses a defence manufacturing firm to develop, test and validate the model and report on 12 partners. We concluded that the focal firm has an Industry 4.0 maturity level of 59.35, above the sector average of 55.58. This research contributes by empirically developing a model and providing an analysis of major firms in the Defence supply network.
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Cited by
Kamble, S., Gunasekaran, A., & Dhone, N. C. (2020) · International Journal of Production Research · doi:10.1080/00207543.2019.1630772 · Cited by 687
Sony, M., & Naik, S. (2020) · Production Planning & Control · doi:10.1080/09537287.2019.1691278 · Cited by 401
Digital transformation success under Industry 4.0: a strategic guideline for manufacturing SMEs
Ghobakhloo, M., & Iranmanesh, M. (2021) · Journal of Manufacturing Technology Management · doi:10.1108/jmtm-11-2020-0455 · Cited by 379
Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0
Kalsoom, T., Ramzan, N., Ahmed, S., & Ur-Rehman, M. (2020) · Sensors · doi:10.3390/s20236783 · Cited by 341
Industry 4.0 and the supply chain digitalisation: a blockchain diffusion perspective
Wamba, S. F., & Queiroz, M. M. (2022) · Production Planning & Control · doi:10.1080/09537287.2020.1810756 · Cited by 298
Metadata
- Authors
- Bibby, L., & Dehe, B.
- Venue
- Production Planning & Control
- Publisher
- Informa UK Limited
- Published
- 2018-09-10
- Volume
- 29
- Issue
- 12
- Pages
- 1030-1043
- ISSN
- 0953-7287 (ISSN-L)
- 1366-5871
- OpenAlex
- W2891416713
- Cited by
- 417
- References
- 68
- FWCI
- 29.07
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
