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Hybrid optimisation approach for sequencing and assignment decision-making in reconfigurable assembly lines

Isabela Maganha, Cristóvão Silva, Nathalie Klement, Amélie Beauville Dit Eynaud, Laurent Durville, Samuel Moniz

Year
2019
Citations
14

Abstract

Technological advances, promoted by the Industry 4.0 paradigm, attempt to support the reconfigurability of manufacturing systems and to contribute to adaptive operational conditions. These systems must be responsive to significant changes in demand volume and product mix. In this paper, a hybrid optimisation approach is suggested to solve sequencing and assignment problems of reconfigurable assembly lines, where mobile robots collaborate with human operators. The objectives are: i) to define a schedule of jobs, ii) to assign tasks to the mobile robots, and iii) to decide the allocation of robots to workstations, in order to minimise the number of robots required. Preliminary results show that the proposed methodology can make an efficient robot allocation under high demand variety. In addition to that, the hybrid optimisation approach can be adapted to other configurations of assembly systems, which demonstrates its applicability to solve problems in other contexts.

Keywords

ReconfigurabilityRobotScheduleComputer scienceVariety (cybernetics)Distributed computingWorkstationGenetic algorithmMathematical optimizationArtificial intelligence

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