Today's industries are more than ever forced to lower their operational costs, especially during the ongoing economic recession where the whole existence of many businesses is endangered. This has created a need of increased information sharing between various decision-support systems. The target is to have full transparency and ensure that the overall result of individual optimization tasks is "globally optimal", i.e., that the decisions taken on different levels do not negate each other. This leads inevitably to more complex optimization systems as the models tend to cover larger problem entities in order to merge previously separated optimization targets or include earlier not considered aspects in order to avoid getting stuck into unfavorable local optima. Another complexity arises from the need of communication between the tasks-earlier isolated problems become networked, which means that the definition of optimization goals cannot be derived from local facts alone. This paper discusses some issues emerging from the integration of production scheduling and control. Some existing standards to support the integration challenge are presented, followed by an overview of recent research results. An interesting question is to what extent such an integration activity is the task of a scientist or a practitioner? The paper concludes by highlighting important open questions and raises some remaining challenges for the future.
- Decision layer integration
- Scheduling and control