This paper presents an approach to scheduling production in a flexible manufacturing system (FMS) environment by employing intelligent grouping of parts which results in good schedules that are easily solvable. Scheduling production in a realistic setting represents a very hard managerial task defying exact solutions, except in very few instances. This article presents and tests a methodology which produces scheduling solutions for large problems with an average small deviation from the theoretical lower bounds. Since open-shop scheduling is the most frequently encountered scheduling discipline in FMS, we restrict the analysis to this setting. The methodology presented combines manufacturing concepts developed in the group technology context with insightful understanding of machine scheduling problems. With the increasing interest in FMS such an approach is both promising and timely.
- open shop
- threshold values
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Artificial Intelligence