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An Approach to Model Lifecycle Management for Supporting Collaborative Ontology-Based Engineering

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Product Lifecycle Management. Leveraging Digital Twins, Circular Economy, and Knowledge Management for Sustainable Innovation (PLM 2023)

Abstract

To reduce costs and increase production capacity, and meet market demand in a sustainable manner, the aerospace industry is placing a growing emphasis on designing the entire product life cycle. This necessitates a novel approach to make a significant advancement and ensure competitiveness in the 21st century. One solution that has emerged is the utilization of Ontology-Based Engineering (OBE) methods, processes, and tools. However, implementing OBE has presented challenges related to modeling, such as effectively managing lifecycles, workflows, and the sharing and reuse of models. To address these challenges, the authors have proposed the Models for Manufacturing (MfM) methodology, which offers a novel way to model manufacturing systems with collaborative, extensible, and reusable characteristics. These characteristics align with the concept of Model Lifecycle Management (MLM). This article highlights the difficulties faced by the aerospace industry when adopting models based on the entire product lifecycle, drawing parallels to the adoption of 3D modeling in the nineties. Furthermore, it explores how the MLM system proposed by the authors can effectively address these issues.

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Acknowledgment

The authors would like to recognize colleagues from University of Sevilla, Airbus in Spain and France, and M&M Group for the support and contributions during the development of this work.

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Correspondence to Fernando Mas .

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Oliva, M., Arista, R., Morales-Palma, D., Szejka, A.L., Mas, F. (2024). An Approach to Model Lifecycle Management for Supporting Collaborative Ontology-Based Engineering. In: Danjou, C., Harik, R., Nyffenegger, F., Rivest, L., Bouras, A. (eds) Product Lifecycle Management. Leveraging Digital Twins, Circular Economy, and Knowledge Management for Sustainable Innovation. PLM 2023. IFIP Advances in Information and Communication Technology, vol 702. Springer, Cham. https://doi.org/10.1007/978-3-031-62582-4_16

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  • DOI: https://doi.org/10.1007/978-3-031-62582-4_16

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