A Multi-Site Scheduling System

The objective of multi-site scheduling is to support the scheduling activities of a global scheduler and schedulers in distributed production plants in a cooperative way. A global schedule generated on a global level must be translated into detailed schedules as part of the local scheduling process. In case of disturbance, feedback between the local and global levels is essential. Previous methods focused on local production sites, in most cases without coordination. In this work we present an approach that considers the adequate modeling and processing of scheduling on the global and local level together with the coordination of the scheduling activities on the scheduling levels. The Multi-Site Scheduling Problem Scheduling problems can be found in several different application areas, e.g. the scheduling of production operations in manufacturing industry, computer processes in operating systems, truck movements in transportation, aircraft crews, etc. The main task of scheduling is the temporal assignment of activities to resources where a number of goals and constraints have to be regarded. Scheduling covers the creation of a schedule of the activities over a longer period (predictive scheduling) and the adaptation of an existing schedule due to actual events in the scheduling environment (reactive scheduling) (Smith 1992, Kerr and Szelke 1995). But scheduling has also a very important interactive dimension because we always find humans within the scheduling process who have to decide, interact or control. Several decisions have to be taken by the human scheduler (the user of the scheduling system), e.g. introducing new orders, cancel orders, change priorities, set operations on specific schedule positions, and these decisions have to be regarded within the scheduling process (Hsu et al. 1993). Scheduling problems are usually treated in a single plant environment where a set of orders for products has to be scheduled on a set of machines (Dorn and Froeschl 1993, Sauer and Bruns 1997, Smith 1992, Zweben and Fox 1994). However, within many industrial enterprises the production processes are distributed over several manufacturing sites, which are responsible for the production of various parts of a set of final products. Usually, there is no immediate feedback from the local plants to the logistics department and communication between the local schedulers takes place without any computer-based support. Figure 1 illustrates the hierarchical two-level structure of multi-site scheduling reflecting the organizational structure often found in business. On the global level requirements are generated for intermediate products manufactured in individual locations. Local scheduling (at individual locations) deals with the transformation into concrete production schedules which represent the assignment of operations to machines. On both levels predictive, reactive as well as interactive problems are addressed, not only to generate schedules but also to adapt them to the actual situation in the production process. This scenario can easily be adapted to other application areas e.g. distributed software development or other projects. The complexity of real-world scheduling as well as multi-site scheduling scenarios is mainly determined by • the requirements imposed by numerous details of the particular application domain, e.g. alternative machines, cleaning times, set-up costs, etc., • the dynamic and uncertain nature of the manufacturing environment, e.g. unpredictable set-up times, machine breakdowns, etc., • conflicting organizational goals, e.g. minimize work-inprocess time, maximize resource utilization, and • the need of interaction with a human scheduler. Due to the distribution of production processes to different plants some specific problems arise: • Complex interdependencies between production processes that are performed in different plants, have to be regarded, e.g. temporal relations between intermediate and final products, e.g. if an intermediate product that is manufactured in plant A is needed in plant B, the same item can be manufactured in different plants (possibly at different costs), the transport of parts between different plants needs transportation capacities and is timeand costintensive.