Comparing the impact of different rescheduling strategies on the entropic-related complexity of manufacturing systems
Résumé
The primary objective of this paper is to compare five rescheduling strategies according to their effectiveness in reducing entropic-related complexity arising from machine breakdowns in manufacturing systems. Previous case studies carried out by the authors have guided computer simulation. Simulation performance is measured by: 1) Entropic-related complexity measures, which quantify: a) the complexity associated with the information content of schedules, and b) the complexity associated with the variations between schedules; and 2) Mean flow time. The results highlight two main points: a) the importance of reducing unbalanced machine workloads by using the least utilised machine to process the jobs affected by machine breakdowns, and b) low disruption strategies are effective at reducing entropic-related complexity, this means that applying rescheduling strategies in order to manage complexity can be beneficial up to a poin. The contribution of this paper is two-fold. First, it extends the application of entropic-related complexity to every schedule generated through rescheduling, whereas previous work only applied it to the original schedule. Second, recommendations are proposed to schedulers for improving their rescheduling practice in the face of machine breakdowns. Those recommendations vary according to the manufacturing organisations' product type and scheduling objectives.
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