Agent-Based Simulation And System Dynamic Modelling Of Just-In-Time Manufacturing System

System dynamics is an approach to understanding the behavior of complex systems over time, and is increasingly finding application in industrial based material handling systems. System dynamics deals with internal feedback loops and time delays that affect the behavior of the entire system, and computer software is often used to simulate system dynamics models. In this work, the entities of the model are parts, kanban, and cycles. Parts are produced in the production sub-model and they are consumed in the consumption sub-model. Parts are shipped from the production sub-model to the consumption sub-model. In transit, they go through the plant sub model. Kanban controls the reordering of parts. Parts and kanban cards from the supplier sub-model are transported to the plant sub-model. Cycle entities signal the transport cycles and they only exist in the route sub-model; they specify the time to dispatch. Evaluation of manufacturing systems performance under the nine experimental conditions (three levels of manufacturing overhead by three levels of product mix complexity) shows no significant difference in cumulative net operating income when product mix complexity is low. Material Resource Planning System (MRP) begins to significantly outperform the other two manufacturing system alternatives at a medium demand setting for product mix complexity. This difference becomes more pronounced as product mix complexity is set at a high level. At this high setting, Just in Time Manufacturing System (JIT) begins to slowly outperform Mass Production System (MPS).JIT should be matched with other systems such as the Material Requirement Planning (MRP) so the whole system in the company can work smoothly. Continuing to use the MRP system without any modifications causes a burden with paperwork. JIT should operate to control activities that are related to the shop floor such as material control.