4.7 Article

Dispatching method based on particle swarm optimization for make-to-availability

Journal

JOURNAL OF INTELLIGENT MANUFACTURING
Volume 33, Issue 4, Pages 1021-1030

Publisher

SPRINGER
DOI: 10.1007/s10845-020-01707-6

Keywords

Make-to-availability; Dispatching rule; Particle swarm optimization; Metaheuristic; Mean flow time; Setup time

Funding

  1. CNPq [407104/2016-0]
  2. FAPESP [2016/01860-1]
  3. CAPES [001]

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This study aims to develop a dispatching method for production orders in MTA based on the particle swarm optimization (PSO) metaheuristic. Computational simulation results showed that the PSO method achieved better performance in reducing mean flow time, setup time, and stock levels.
Make-to-availability (MTA) is a subtype of make-to-stock that emerged from production, planning, and control system, simplified drum-buffer-rope (S-DBR). The dispatching production order logic of the MTA does not consider the elements present in a wide range of manufacturing systems, such as sequence-dependent setup time. These characteristics generally creates difficulties in the S-DBR, thereby worsening performance indicators, such as mean flow time, setup time, and stock replenishment frequency. Given this research gap, the present study aims to develop a dispatching method for production orders in MTA, based on the particle swarm optimization (PSO) metaheuristic. The dispatching method aims to minimize the mean flow time, setup time, and stock levels in environments with a dependent setup time. To evaluate the performance of the new dispatching method, we used computational simulation to compare this method and the MTA dispatching logic. The results showed that the PSO for sequence achieved better performance, reducing the mean flow time, setup time, and stock level.

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