Modeling information flows in the automotive supply chain-A simulation based sensitivity analysis of potential improvements
Abstract
This contribution investigates the impact of altering key aspects of a Vehicle Manufacturer’s (VM) and a first tier supplier’s scheduling activities with the objective of determining the scope for potential improvements in customer response of the whole supply chain. Specifically, a two-model production facility at a vehicle manufacturer is studied, with the input of a realistic demand pattern and the supplier reacting to the demand of components used in a random percentage of one of those models. The performance of the whole system is measured in terms of inventory, backlog and production adaptation costs, by simulating various scenarios. The analysis is based on the Taguchi Method and investigates the sensitivity of the various factors, using the ANalysis Of VAriances (ANOVA) procedure. Applying these methods, the major influences on the current supply chain performance is demonstrated, which are mainly related to the manufacturer’s scheduling practices, i.e. the levelling period used for volume forecasts and product mix ratio or the buffer error weighting.