An investigation into sources of uncertainity within industrial supply chains : amplification, deterministic chaos & parallel interactions

The objective of this research was to investigate the generation of uncertainty within industrial supply chains. Since the late 1950's it has been recognised that the systems used internally within supply chains can lead to oscillations in demand and inventory as orders pass through the system. The uncertainty generated by these oscillations can result in late deliveries, order cancellations and an increased reliance on inventory to buffer these effects. Despite the best efforts of organisations to stabilise the dynamics generated, industry still experiences a high degree of uncertainty from this source. Greater understanding of the generation of uncertainty within the supply chain could result in improved management of the systems and consequently competitive advantage being gained by organisations. The investigation used simulation models of real industrial supply chains to identify possible sources of uncertainty. The complexity of the models was adjusted by increasing the number of echelons and the number of channels in the supply chain. One source of uncertainty investigated was the generation of deterministic chaos and a methodology was developed to detect and quantify this within the supply chain. Parallel interactions, which occur between suppliers in the same tier in the supply chain, were also modelled and quantified. In addition to demand amplification, which has been recognised as a source of uncertainty by both academics and industrialists, two additional sources of uncertainty were identified: namely deterministic chaos and parallel interactions. The relationship between these causes of uncertainty was established and the original concept of the "supply chain complexity triangle" is proposed. The "average prediction horizon" was calculated by the use of Lyapunov exponents and was used to quantify the amount of chaos experienced by supply chain members. This chaos was found to be dependent on the number of echelons, which also impacts on the amount of chaos experienced by all members of the supply chain, both up and down stream. Parallel interactions impact on all the members of the supply chain resulting in reduced performance. However, the number of channels in the supply chain modelled had little effect on the amount of chaos. Implications for reducing supply chain uncertainty either by managing or removing these effects is also discussed.