A Polynomial Algorithm For Balancing a Sequence of Operations in Reconfigurable Transfer Lines

Autor: Sylvie Norre, Laurent Deroussi, Nathalie Grangeon, Youssef Lahrichi
Přispěvatelé: Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), Ecole Nationale Supérieure des Mines de St Etienne-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), Grangeon, Nathalie, Ecole Nationale Supérieure des Mines de St Etienne (ENSM ST-ETIENNE)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: MIM 2019 (Manufacturing Modeling, Management and Control)
MIM 2019 (Manufacturing Modeling, Management and Control), Aug 2019, Berlin, Germany
HAL
Popis: International audience; We consider the problem of balancing reconfigurable transfer lines. The problem is quite recent and motivated by the growing need of reconfigurability in the industry. The problem consists into allocating a set of operations (necessary to machine a single part) to different workstations placed into a serial line. The workstations can contain multiple machines operating in parallel. The machines considered are mono-spindle head CNC machines which imply setup times between operations in order to perform tool changes. Therefore, the operations allocated to a workstation should be sequenced. Besides, accessibility, inclusion, exclusion and precedence constraints between operations are considered. In this article, we suggest a polynomial exact algorithm that balances the transfer line provided the overall sequence of the operations (called "giant sequence") is given. This balancing subproblem was dealt with in the literature by means of ILP and heuristics. We use this algorithm to solve the balancing problem independently from the overall sequence of operations by embedding it in a simple local search within the giant sequence space. Experimentation show significant improvement compared to literature.
Databáze: OpenAIRE