A Novel Approach to Aggregate Scheduling in Project-Oriented Manufacturing

In this paper we address medium-term scheduling in project oriented manufacturing systems. These systems may execute hundreds of thousands of manufacturing operations under various capacity and technological constraints within the typical 3-6 months long horizon. This challenges any branch of operation research or artificial intelligence. We suggest an aggregate scheduling approach to cope with this challenge in case of project-oriented environments, characterized by complex projects with strict individual deadlines. Dimensions of aggregation are time and tasks: the scheduling problem is solved with an aggregate time unit in the order of magnitude of one week. Furthermore, not individual manufacturing operations are scheduled, but so-called activities, aggregate units of work built of logical groups of discrete operations. We consider the aggregate scheduler as a part of a hierarchical production planning and scheduling system. It is not simply expected to generate schedules which are good enough in themselves, but also takes into considerations the effects of its decisions on lower levels, i.e., on job-shop schedules. The main contribution of the paper is a detailed analysis of the effects of decisions made during activity formation on the outcome of the overall scheduling process. Based on these investigations, we suggest an activity model which is quite different from those used by previous approaches. We consider the determination of the best suited activity models an optimization problem, and advise an algorithm to construct them. The paper is structured as follows. We start with a brief literature overview, followed by the presentation of our scheduling algorithm. The nucleus of the article focuses on the analysis of activity formation decisions. Finally, we describe our first experiences with our pilot system working on real industrial data, and draw the conclusions.