Developing a Multi-Agent System to Support Multi-Variant Production Ramp-Up Management - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Smart and Sustainable Manufacturing Systems Année : 2021

Developing a Multi-Agent System to Support Multi-Variant Production Ramp-Up Management

Résumé

In the Industry 4.0 era, with increased demands for customization, numerous companies struggle to accommodate changes in their businesses and to keep up with the pace of digital transformation. It follows that introducing new products or services based on an existing configuration or a new design is becoming more frequent. Managing the production ramp-up phase carefully is therefore emerging as one of the most critical steps in the product lifecycle. Although several general strategies and high-level frameworks are available in recent ramp-up management literature, data-backed tools and frameworks that deal with this question are scarce. This article aims to bridge this gap by developing a multi-agent system (MAS) supporting ramp-up management strategies assessment in multi-variant production contexts. An MAS relies on the concept of an agent, which is an autonomous entity operating in a society of agents in order to contribute to a general goal. This article studies the method used to develop an MAS and illustrates its applicability through a case study in the furniture sector. The article highlights the reusability and flexibility of the development method and the relevance of the MAS to decision-makers during ramp-up planning.
Fichier principal
Vignette du fichier
SSMS_2020_Full_2021-04-12_2.pdf (1.66 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

emse-03233783 , version 1 (08-11-2021)

Identifiants

Citer

Khaled Medini, David Romero, Thorsten Wuest. Developing a Multi-Agent System to Support Multi-Variant Production Ramp-Up Management. Smart and Sustainable Manufacturing Systems, 2021, 5 (1), pp.20200082. ⟨10.1520/SSMS20200082⟩. ⟨emse-03233783⟩
221 Consultations
203 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More