Sustainable optimisation approaches for production planning and control to evolve towards industry 5.0
[EN] Industry 4.0 (I4.0) has led to a very high development potential in the optimisation of production planning and control problems in industrial companies. This study aims to analyse the existing scientific literature on the optimisation of planning, control and management problems, specifically...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/229306 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/229306 |
| Access Level: | acceso abierto |
| Palabra clave: | Production planning and control Optimisation Sustainability Industry 5.0 Industry 4.0 08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación |
| Sumario: | [EN] Industry 4.0 (I4.0) has led to a very high development potential in the optimisation of production planning and control problems in industrial companies. This study aims to analyse the existing scientific literature on the optimisation of planning, control and management problems, specifically in the production, operations and scheduling areas, to make industry more sustainable in accordance with the I4.0 context; that is, applying new digital technologies and I5.0 by integrating people into this digital transformation. Specifically, 77 research works were identified and analysed. The main findings conclude that the key setting of these optimisation problems lies in manufacturing contexts and highlight the use of modelling and solution techniques through mathematical programming and metaheuristics. These studies, which are mostly empirical, point out different software tools, and underline the use of MATLAB, optimisation with CPLEX, the Python programming language and simulation through AnyLogic. For I4.0 techniques, data analytics and big data, artificial intelligence, the Internet of Things, sensors and simulation and digital twins are the most studied. Proposals addressing worker ergonomics and a three-pillar approach to sustainability are particularly noteworthy. Finally, the main research gaps, challenges and trends for future research are recognised. |
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