Formalizing sustainability knowledge inside manufacturing systems in the context of industry 4.0
Today’s manufacturing is going through changes due to digitalization and the industry 4.0 paradigm. In that sense, manufacturing systems are facing a transition from traditional systems to the ones more compatible with Industry 4.0. Digitalization is expanding itself all over the world and is conseq...
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| Tipo de documento: | dissertação |
| Data de publicação: | 2024 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/426159 |
| Acesso em linha: | https://hdl.handle.net/2117/426159 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Industry 4.0 Production management Indústria 4.0 Producció--Direcció i administració Àrees temàtiques de la UPC::Economia i organització d'empreses::Competitivitat i innovació |
| Resumo: | Today’s manufacturing is going through changes due to digitalization and the industry 4.0 paradigm. In that sense, manufacturing systems are facing a transition from traditional systems to the ones more compatible with Industry 4.0. Digitalization is expanding itself all over the world and is consequently followed by a huge amount and variety of generated data that need to be formalized. Therefore, manufacturing systems need tools and approaches that enable them to extract and form knowledge efficiently from the vast amount of data collected throughout the systems. Moreover, digitalization and smart manufacturing strive for sustainable development and a more sustainable-oriented performance at the industry level, as well as enhanced efficiency in manufacturing operations. In manufacturing, production planning and scheduling are critical for optimizing resources and productivity. Together, planning and scheduling form the backbone of manufacturing operations, maximizing productivity and efficiency. Integrating sustainability into these processes is crucial for minimizing waste, reducing energy consumption, and mitigating environmental impacts. By aligning scheduling and planning with sustainability goals, manufacturing can foster a more environmentally conscious and sustainable ecosystem. To that point, the objective of the thesis is to explore the knowledge management tools, such as ontologies, taxonomies or knowledge graphs, that would help towards a standardize representation of data in order to facilitate planning and scheduling activities within manufacturing contexts. Indeed, ontologies, taxonomies, and knowledge graphs serve as structured frameworks for organizing and representing information. These frameworks facilitate the management of data related to the improvement of systems, solutions to problems, enhance sustainability or improve collaboration among the supply chain parts. Moreover, by integrating sustainability criteria into these frameworks, organizations can optimize scheduling and planning activities to align with economic and environmental objectives and societal needs. In order to achieve the above-mentioned objective, a representative analysis of the current literature was performed. After careful considerations, 48 papers, including ontologies, knowledge graphs and taxonomies, related to the research question “How do ontologies/knowledge graphs/taxonomies contribute to scheduling and planning of manufacturing activities?”, were identified. An analysis was conducted through mapping and categorization of the 48 selected papers with respect to several criteria. Finally, a study of the 8 papers that included the full ontology in the text will be done, with a gap for a future work on how to integrate sustainability in these ontologies. |
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