Nick, Gábor ORCID: https://orcid.org/0000-0003-1441-7109, Zeleny, Klaudia ORCID: https://orcid.org/0000-0003-4965-5457, Kovács, Tibor, Járvás, Tamás ORCID: https://orcid.org/0000-0003-0295-6092, Pocsarovszky, Károly and Kő, Andrea ORCID: https://orcid.org/0000-0003-0023-1143 (2024) Artificial intelligence enriched industry 4.0 readiness in manufacturing : the extended CCMS2.0e maturity model. Production and Manufacturing Research, 12 (1). DOI https://doi.org/10.1080/21693277.2024.2357683
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Official URL: https://doi.org/10.1080/21693277.2024.2357683
Abstract
The manufacturing industry faces solid global competition, uncertainties, rapid technological advances, and disruptive events, forcing it to rethink production operations and improve its digitisation efforts. Several Industry 4.0 (4IR) readiness and maturity models are known, but the increasing opportunities offered by AI are not, or only partially, included in these models. This research uses a literature review and expert interviews to explore the role of AI methods and applications in relation to digital twins in production, manufacturing, and logistics. Based on this study and in line with the development phases of the Connected Factories project, the Company CoMpaSs 2.0e (CCMS2.0e) 4IR maturity assessment model was developed, including an AI dimension. The model was tested with four real production cases. The main contribution is that companies can use the proposed model to assess their 4IR readiness in artificial intelligence and identify related intervention points for improvement.
Item Type: | Article |
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Uncontrolled Keywords: | digitization, digital twin, maturity model, artificial intelligence, industry 4.0 readiness |
Divisions: | Institute of Data Analytics and Information Systems Corvinus Doctoral Schools |
Subjects: | Industry |
DOI: | https://doi.org/10.1080/21693277.2024.2357683 |
ID Code: | 10100 |
Deposited By: | MTMT SWORD |
Deposited On: | 02 Jul 2024 09:10 |
Last Modified: | 02 Jul 2024 09:10 |
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