Graph approach for balancing a class of transfer lines

The optimal design of automatic transfer lines is considered. To this end, operations are partitioned into blocks. The operations of the same block are performed simultaneously, and different blocks of the same workstation are activated sequentially. Constraints related to the design of blocks and workstations, as well as precedence constraints related to operations, are given. The problem consists in minimizing the total number of workstations and blocks, while reaching a given cycle time and satisfying the above constraints. We develop an exact method which proceeds by setting the problem as a constrained shortest path problem. This method is efficient for small and medium size problems

Systèmes de production modernes. Tome 1 : Conception, gestion et optimisation

ISBN : 2-7462-1249-

Systèmes de production modernes. Tome 2 : Outils et exercices corrigés

ISBN : 2-7462-1250-

Complexity of Production Management in a Petri Net Environment

The objective of this paper is to show that Petri nets facilitate a comprehensive approach to production management and reduce the complexity of the problems involved at the expense of some constraints imposed on the decision making systems.The first part of the paper focuses on cyclic manufacturing systems. For this type of systems, it is always possible to propose an event graph model which represents both the physical and the decision making systems. We use such a model to propose a near-optimal scheduling algorithm that maximizes productivity while minimizing the work-in-process (WIP) in the deterministic case.The approach used for non-cyclic manufacturing systems is different in the sense that only the manufacturing processes (i.e. the physical part of the system) and the related constraints are modeled using Petri nets. We use such a Petri net model to propose a short-term planning process which results in a trade- off between the computation burden the level of resource utilization. the short-term planning models is then enhanced to obtain the scheduling model. The latter is used to develop an efficient scheduling algorithm that is able to satisfy the requirements imposed by short-term planning