Just-in-Time Scheduling in Modern Mass Production Environment
The main goal of just-in-time production planing is the reduction of the in-process inventory level. This goal may be achieved by completing the items as close to their further processing (or shipment) dates as possible. In the mass production environment, it is too costly to define and control due dates for individual items. Instead, the model proposed in Toyota is applied that assumes monitoring the actual product rate of particular products. The objective is to construct schedules with minimum deviation from an ideal product rate. In the approach aimed at minimization of the Product Rate Variation, the control process concentrates on product types, not individual items. In this chapter, we discuss the PRV model and scheduling algorithms developed to solve this problem with two types of objectives: to minimize the total or maximum deviation from the ideal product rate. We present algorithms proposed in the context of the just-in-time production scheduling as well as in other areas, adopted later to solve the PRV problem. One of the most interesting problems discussed in this context is the apportionment problem. Originally, the PRV problem was defined as a single machine scheduling problem. We show that some algorithms can be generalized to solve the parallel-machine scheduling problem as well.
KeywordsTransportation Diesel Gasoline Production Line
- 4.Balinski, M., Young, H.: Fair Representation: Meeting the Ideal of One Man, One Vote. Yale University Press (1982)Google Scholar
- 10.Józefowska, J., Józefowski, L., Kubiak, W.: Characterization of just in time sequencing via apportionment. In: H. Yan, G. Yin, Q. Zhang (eds.) Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems, International Series in Operations Research & Management Science, vol. 94, pp. 175–200. Springer US (2006)Google Scholar
- 12.Józefowska, J., Józefowski, L., Kubiak, W.: Dynamic divisor-based resource scheduling algorithm. In: Proceedings of the 12th International Workshop on Project Management and Scheduling. Tours, France (2010)Google Scholar
- 13.Kubiak, W.: Proportional Optimization and Fairness, International Series in Operations Research & Management Science, vol. 127. Springer, New York (2009)Google Scholar
- 17.Monden, Y.: Toyota Production Systems. Industrial Engineering and Management Press, Norcross (1983)Google Scholar