Continuous Flow Models of Manufacturing Systems: a Review

• Published in: CIRP annals Vol. 45; no. 1; pp. 441 - 444
• Main Authors: Brandimarte, P., Sharifnia, A., Von Turkovich, B.F.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 1996; Elsevier
• Subjects: Applied sciences; Exact sciences and technology; Modeling; Operational research and scientific management; Operational research. Management science; Optimization; Production Control; Scheduling, sequencing; Production Control; Modeling; Optimization; Production management; Scheduling; Review; Dynamic model
• ISSN: 0007-8506; 1660-2773; 1726-0604
• DOI: 10.1016/S0007-8506(07)63098-4

Production scheduling approaches in discrete manufacturing environments must cope with discrete material flows subject to different constraints in order to obtain a good solution. Despite the huge amount of literature on machine scheduling, most commercial schedulers take a myopic approach based on priority rules. Among the reasons behind this gap there are issues related to the complexity of optimized scheduling methods and the vulnerability to schedule disruptions. In the paper we review some approaches aimed at bridging the gap between optimization models and real time control. Such models are based on an approximation of the discrete material flow with a continuous flow. We review stochastic control models for repetitive production and mixed-integer programming models for batch manufacturing.