Multiproduct, multiechelon supply chain analysis under demand uncertainty and machine failure risk

Due to outgrowing competitiveness on the market, supply chain analysis and optimization become a matter of utmost importance in maximizing global system revenue and customer service levels. In this paper a discrete event simulation model is developed to address system analysis for a multiproduct, multiechelon biomass supply chain case study. The performance metrics considered are: percentage lost sales by product type, biomass pre-treatment facility utilization and downtime probability, average inventory level by product type at each level of the supply chain. The system is subject to machine failure and works under demand uncertainty. The study focuses on the way biomass demand variation and machine failure probability influence those metrics. The supply chain analysis shows that as biomass demand increases the service level deteriorates (the production plant is most affected by the increasing load). System performance can be improved using enhanced maintenance of the biomass pre-treatment plant (reducing downtime probability). System optimization leads to overall increase performance and increase service level.