PSS Pattern Concept for Knowledge Representation in Design Process of Industrial Product-service Systems

Autor: Luis Usatorre Irazusta, Elaheh Maleki, Alain Bernard, Yicha Zhang, Farouk Belkadi, Spyros Koukas
Přispěvatelé: Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), INASMET-Tecnalia (SPAIN), École Centrale de Nantes (ECN), University of Patras [Patras]
Jazyk: angličtina
Předmět:
Zdroj: Procedia CIRP
Procedia CIRP, ELSEVIER, 2017, 60, pp.428-433. ⟨10.1016/j.procir.2017.01.001⟩
TECNALIA Publications
Fundación Tecnalia Research & Innovation
ISSN: 2212-8271
DOI: 10.1016/j.procir.2017.01.001
Popis: To save time and cost in development process of new customized product-service systems, engineers need methodological guidelines and generic knowledge that help constructing specific solutions for new customers’ requirements and business opportunities. Despite the specific character of every PSS due to several customization issues, many characteristics are shared between PSS from the same product and/or service family. This paper proposes a knowledge-based methodology to support the PSS design process, extending the concepts of pattern and instance as main knowledge fragments. The main idea is to encapsulate in the pattern a conceptual definition of a collection of potential verified solutions, able to achieve a product-service with certain performance value with regard to a set of working conditions. These solutions are then filtered and refined by means of the PSS instance when answering one specific PSS demand. The presented results were conducted within the project “ICP4Life” entitled “An Integrated Collaborative Platform for Managing the Product-Service Engineering Lifecycle”. This project has received funding from the European Union’s Horizon 2020 research and innovation program.
Databáze: OpenAIRE