Design and implementation of a distributed part-routing algorithm for reconfigurable transportation systems

Abstract

The reconfigurability feature represents an instrumental characteristic for manufacturing systems that are required to frequently adapt the architecture and functionalities to match evolving production environment where changes of product variants and demand volumes frequently occur. Transportation systems embrace a major industrial application of the reconfiguration concept. Reconfigurable transportation systems (RTSs) are conceived as multiple independent modules to implement alternative inbound logistic systems’ configurations. Together with mechatronic interfaces and distributed control solutions, the full exploitation of reconfigurability strategies for transportation systems relies upon flexible production management policies. This enables the dynamic computation of part routings in RTSs after every reconfiguration and change in the way transportation modules are exploited. The current work proposes an innovative agent-based algorithm that combines global and local optimisation criteria to manage the part flow in RTS. The proposed approach is designed as fully distributed across transportation modules; based on current RTS’ topology and status, it ensures the autonomy in selecting routing decisions while embracing global and local evolving optimisation strategies. The benefits of the approach have been investigated with reference to a set of realistic RTS topologies exhibiting different routing options, in order to assess the algorithm under different part-routing conditions.

Keywords:

• reconfigurable transportation system
• part routing
• auctioning algorithm

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. http://jade.tilab.com – version 4.3.0.

Additional information

Funding

SUPSI-ISTePS authors are supported by EU FoF 2012 Project whiteR – white room based on Reconfigurable Robotic Island for Optoelectronics [contract 609228]. CNR authors are supported by MIUR Flagship Initiative [FdF-SP1-T2.1] Project Generic Evolutionary Control Knowledge-based mOdule (GECKO).