A dynamic system model for proactive control of dynamic events in full-load states of manufacturing chains

Abstract

Risk management is a major concern in supply chains that have high levels of uncertainty in product demand, manufacturing process or part supply. The uncertainties frequently manifest as dynamic events that pose a threat to interrupting supply chain operation. Depending on the nature and severity of uncertainty, the impact of dynamic events can be distinguished into three categories: deviation, disruption, and disaster. Many studies in literature addressed modelling of deviation events. In this paper, a dynamic system model of supply chains is described which can be applied to managing disruptive events in full-load states of manufacturing chains. An example of disruptive events is given which arises from demand shocks in distribution channel. The procedure to construct full-load production functions of complex manufacturing nodes with internal queuing delay is described. Analytic optimal solution is derived for the dynamic model. Given an unordinary event of demand shock, this model can be used to determine if demand shock can be absorbed by a manufacturing chain and the level of contingent resources that must be synchronously activated in multiple nodes of the chain. This model can be used to reduce what could have been a disruptive event into a deviation event, thus enhancing risk management.