Manufacturing 4.0 Operations Scheduling with AGV Battery Management Constraints

Moussa Abderrahim (1) , Abdelghani Bekrar (1) , Damien Trentesaux (1) , Nassima Aissani (2) , Karim Bouamrane (3)

1 LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201
2 Université d'Oran 2 Mohamed Ben Ahmed [Oran]
3 Université d'Oran 1 Ahmed Ben Bella [Oran]

The industry 4.0 concepts are moving towards flexible and energy efficient factories. Major flexible production lines use battery-based automated guided vehicles (AGVs) to optimize their handling processes. However, optimal AGV battery management can significantly shorten lead times. In this paper, we address the scheduling problem in an AGV-based job-shop manufacturing facility. The considered schedule concerns three strands: jobs affecting machines, product transport tasks’ allocations and AGV fleet battery management. The proposed model supports outcomes expected from Industry 4.0 by increasing productivity through completion time minimization and optimizing energy by managing battery replenishment. Experimental tests were conducted on extended benchmark literature instances to evaluate the efficiency of the proposed approach.

Mots clés: energy optimization; job-shop scheduling; transport constraints; automated guided vehicles; battery management

Domaines: Recherche opérationnelle [math.OC]; Automatique / Robotique

Moussa Abderrahim, Abdelghani Bekrar, Damien Trentesaux, Nassima Aissani, Karim Bouamrane. Manufacturing 4.0 Operations Scheduling with AGV Battery Management Constraints. Energies, 2020, 13 (18), pp.4948. ⟨10.3390/en13184948⟩. ⟨hal-03426790⟩