Automatic Routing Reconfiguration for Fault Tolerance in Smart Manufacturing Plants

This paper focuses on the parts routing problem in a reconfigurable manufacturing plant, in presence of potential faults and uncertainty on the job scheduling and duration. The plant is modeled as a directed graph, where the nodes represent either transportation modules or machines, and the edges represent the allowed transitions between adjacent nodes. The parts move across the plant along predefined sequences of nodes, therefore the system state tracks the progress of the parts along such sequences and the control inputs are the transitions to be activated to command the parts movement. Provided the sequences, the proposed method automatically generates feedback control rules for deadlock avoidance, which are employed by a path following strategy to compute the suitable control inputs, complying with given temporallogic constraints and avoiding deadlock states. Additionally, the approach is extended to deal with faults affecting the transportation modules via the selection of new feasible sequences and the online reconfiguration of the system state. Finally, the proposed approach is tested in highfidelity simulations, showing high computational efficiency and throughput.