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Article type: Research Article
Authors: Fougères, A.-J.a; * | Ostrosi, E.b
Affiliations: [a] ECAM Rennes, Campus de Ker Lann - Bruz, Rennes, France | [b] Université de Bourgogne Franche-Comté, UTBM, Pôle Industrie 4.0, Pôle ERgonomie et COnception des Systèmes ERCOS/ELLIADD EA4661, Belfort, France
Correspondence: [*] Corresponding author. Email: alain-jerome.fougeres@ecam-rennes.fr.
Abstract: Cloud-based design and manufacturing is a dynamic service-oriented network where a set of CAD products is manufactured in virtual digital cells under certain constraints. This paper assumes that these CAD products can be modelled by a set of holonic fuzzy agents and defined from a set of fuzzy feature agents which themselves can be defined by a set of fuzzy face agents. Integrating the uncertainty in the modelling of the feature-product-workcenter-cell network by holonic fuzzy agents, this paper proposes an approach to address adaptive virtual manufacturing cell formation in cloud-based manufacturing. These cells are thus supported by digital technology. Intelligent manufacturing features, modelled as holonic fuzzy feature agents, are defined in CAD product models. Subsequently, the distributed capabilities of resources in cloud manufacturing are evaluated through holonic fuzzy agents, and the holonic structure of adaptive virtual manufacturing cells is formed by these agents. The software agent paradigm brings its reactivity, its dynamicity, its agility, and, thus, its adaptability to the holonic structure. The presentation of a scenario causing different changes in workcenters (e.g., unavailability of machines or addition of new products) illustrates the behaviour of holonic fuzzy agents during the reconfiguration of the virtual manufacturing cells holonic structure, thereby demonstrating the adaptive capacity of this kind of holonic structure.
Keywords: Intelligent manufacturing, adaptive virtual manufacturing cell, multiagent, holonic fuzzy agent
DOI: 10.3233/JID190009
Journal: Journal of Integrated Design and Process Science, vol. 23, no. 1, pp. 77-102, 2019
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