Abstract
ABSTRACT In practice, orders composed of different part/job types with varying quantities randomly arrive at a production area and they have a due date which designates the latest time before which all jobs in the order should be completed. Therefore, an order can only be fulfilled until all the jobs in that order are finished. This paper studies a pull production environment where there are five serial stations capable of processing different part types and part movement is controlled by a dual-card kanban system in order to reduce work-in-process inventory. Following the definition of a base model with given parameters, we discuss simulation-related experimental design features, performance criteria involving due-date-related ones, statistical analyses and design clusters. Statistical findings for each design cluster with predetermined input factors are interpreted.
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