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Previous work studied a production system including multiple stations (or workshops) consisting of an entry station, a set of workstations, an exit station, and a central station, which could be arranged in any configuration. The central station was introduced into the production system to relax the environment. In this paper, the central station is eliminated. The entry station and all workstations have limited local buffers. A workstation can choose either a buffer or a kanban mechanism to control its work-in-process (WIP). The production system was modeled as a queueing network with blocking in a general configuration. A symmetrical decomposition approach was developed to analyze the production system. The simulation result shows that the decomposition approach works well. Comparison of the new production systems with modified production systems having a common buffer shows that the key for implementing just-in-time production systems is to reduce the uncertainty.
Previous work studied a production system including multiple stations (or workshops) consisting of an entry station, a set of workstations, an exit station, and a central station, which could be arranged in any configuration. The central station was introduced into the production system To relax the environment. In this paper, the central station is eliminated. The entry station and all workstations have limited local buffers. A workstation can choose either a buffer or a kanban mechanism to control its work-in-process (WIP). The production system was modeled as a queueing network with blocking in a general configuration. A symmetrical decomposition approach was developed to analyze the production system. The simulation result shows that the decomposition approach works well. Comparison of the new production systems with modified production systems having a common buffer shows that the key for implementing just-in-time production systems is to reduce the uncertainty.