Reactive Scheduling in Real Time Production Control

Abstract

Reactive operation managenlent -Predictive, reactiveand proactive schedulingContinuous, steady improvement of manufacturing operation management from information technology (IT) perspective is a key requirement to manufacturing enterprises competing under the pressure of changing market demands.Manufacturing systems often operate in complex environments rife with uncertainty. The growing complexity of manufacturing operation management lies in the nonexpected tasks/events, nonlinearities, and a multitude of interactions which arise when attempting to control various activities in dynamic shop floors. This complexity and uncertainty seriously limit the effectiveness of conventional control and scheduling approaches. Reactive/proactive systems of shop floor control and scheduling with adaptive behaviour that is ensured by some embedded learning capability and based on real-time monitoring of executed processes, represent the viable alternative.The broad goal of manufacturing operation management, like other resource constrained, multi-agent planning/scheduling problems, is to achieve a co-ordinated efficient behaviour of manufacturing in servicing production demands while responding to changes in shop floors in a timely and cost-effective manner [164]. Operation scheduling, viewed a major issue of manufacturing operation management, has remained a complex co-ordination task despite the recent trends and efforts towards a structural rationalisation in manufacturing (e.g., through the implementation of group technology and JIT strategies). Quality of the operation scheduling process generally has a profound effect on the overall factory performance. Advance generation of the factory schedules is considered central to co-ordinate manufacturing activities in order to meet some organisational objectives, usually the three-pronged objective of producing parts of higher quality at lower cost within a shorter lead time. The generation of advance (predictive) schedules is also demanded for anticipating potential performance obstacles (e.g., resource contention), and for timely assuring physical preconditions (availability of all the needed resources, presetting of processes) to the execution of scheduled manufacturing activities, in order to minimise the disturbing effects on the overall manufacturing system operation.

Újraütemezési döntések támogatása diszkrét eseményszimuláció alkalmazásával

“…Ezeknek a zavaró tényezőknek vagy zavaroknak a bekövetkezése véletlenszerű, nem tervezhető így szinte biztos, hogy a tervezett és a végrehajtott ütemterv között eltérés alakul ki. Azt, hogy milyen mértékű eltérés esetén avatkozunk be és a beavatkozás során hogyan módosítjuk/változtatjuk az eredeti ütemtervet az alkalmazott -újraütemezési -technika és a környezet határozza meg [1], [2].…”

Development of a Simulation-Based Intelligent Decision Support System for the Adaptive Real-Time Control of Flexible Manufacturing Systems

“…Regarding these considerations, control of these environments plays an essential role at manufacturing systems. Control framework has been studied on FMSs in the literature and there are different methods for selecting the most appropriate control policies at each decision point [8][9][10][11][12][13][14][15]. These strategies deal with the allocation of jobs to multi-purpose machining centers which have to be made in a flexible way.…”

Coupling order release methods with autonomous control methods – an assessment of potentials by literature review and discrete event simulation

“…Proactive scheduling strategies try to avoid rescheduling by creating robust schedules, which e.g. anticipate disturbances by inserting idle times, for example Szelke & Monostori (1999). Autonomous control methods in this context possess characteristics of reactive scheduling.…”