A generic deadlock-free reactive scheduling approach

Abstract

A hierarchical control system is proposed for automated flexible manufacturing cells (FMC) that operate in a job shop flow setting. The control system is made up of a higher level scheduler/reactive scheduler, which optimizes the production flow within the cell, and a lower level supervisor that implements the decisions of the scheduler on the shop floor. Previous studies have regularly considered the production scheduling and the supervisory control as two separate problems. This has led to: i) deadlock-prone optimized schedules that cannot be implemented in an automated setting, ii) deadlockfree optimized schedules that lack the means to be transformed into shop floor supervisors, or iii) supervisors that can safely drive the system with no consideration for production performance. The proposed control system combines mathematical models and an insertion heuristic to solve the deadlock-free scheduling problem in job shops, a deadlock-free reactive scheduling heuristic that can revise the schedules upon the occurrence of a wide variety of disruptions, and a systematic procedure that can transform schedules into readily implementable Petri net (PN) supervisors. The integration of these modules into one control hierarchy guarantees a correct, optimized and agile behavior of the controlled system. The performances of the mathematical models, the scheduling and the reactive scheduling heuristics were evaluated by comparison to performances of previous approaches. Experimental results showed that the proposed modules performed consistently better than the other corresponding approaches. The supervisor realization procedure and the overall control architecture were validated by simulation and

Stochastic flexible flow shop scheduling problem with limited buffers and fixed interval preventive maintenance: a hybrid approach of simulation and metaheuristic algorithms

“…Also, on SERVER atom, each SERVER can only process one PRODUCT at a time. Therefore, constraints related to assignment of jobs to only one machine at each stage will be achieved (constraints set by Equations (5) and (6)). Since the simulation model is a mimic of real systems, all constraints related to system availability will automatically be satisfied.…”

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