Modeling of Supply Chain Contextual-Load Model for Instability Analysis

Simulation provides an alternative method for detailed analysis of the complex real world systems such as the supply chain. Given that a simulation model is well-suited for evaluating dynamic decision rules under ‘what-if ‘ scenarios, a few attempts have been made to develop simulation models to improve supply chain performances. The modelling of supply chains dynamics adopted to simulation approach has been reported by many authors including (Towill et. al., 1992), (Badri, 1999), (Bhaskaran, 1998), and (Sadeh et. al., 1999). More specifically, (Towill et. al., 1992) used influence diagrams to visualise the cause-andeffect relationship between the decision rule and the improvement of supply chain performances. The main purpose of the study is to create a best decision rule that will allow the decision maker to reduce lead times, compress the distribution channel and co-ordinate information flow throughout the supply chain. (Bhaskaran, 1998) conducted a simulation analysis of supply chain instability. He shows how supply chains can be analysed for continuous improvement using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors. (Badri, 1999) developed a simulation-based decision-support system for multi-product inventory control management to enhance the competitive advantage of a furniture manufacturing firm using the simulation language SLAMSYSTEM and some statistical models. He claimed that the model allows managers to examine different inventory systems and policies without resorting to unrealistic assumptions and methods or having to use complicated mathematical techniques. (Sadeh et.al., 1999) proposed an architecture that aims at providing a framework for coordinated development and manipulation of planning and scheduling solutions at multiple levels of abstraction across the supply chain. The architecture is configured around a blackboard architecture to allows for the easy integration of multiple planning and scheduling modules along with analysis and coordination modules.