Supply chain design and cost analysis through simulation

Abstract

This paper is grounded on a discrete-event simulation model, reproducing a fast moving consumer goods (FMCG) supply chain, and aims at quantitatively assessing the effects of different supply configurations on the resulting total supply chain costs and bullwhip effect. Specifically, 30 supply chain configurations are examined, stemming from the combination of several supply chain design parameters, namely number of echelons (from 3 to 5), re-order and inventory management policies (EOQ vs. EOI), demand information sharing (absence vs. presence of information sharing mechanisms), demand value (absence vs. presence of demand ‘peak’), responsiveness of supply chain players. For each configuration, the total logistics costs and the resulting demand variance amplification are computed. A subsequent statistical analysis is performed on 20 representative supply chain configurations, with the aim to identify significant single and combined effects of the above parameters on the results observed. From effects analysis, bullwhip effect and costs outcomes, 11 key results are derived, which provide useful insights and suggestions to optimise supply chain design.

Keywords:

• supply chain management
• supply chain design
• simulation model
• economical analysis
• design of experiments
• fast moving consumer goods

Notes

Note

1. For visualisation purpose, boundaries to the high/low quadrants of both costs and bullwhip effect were set at 12.5% of the maximum observed value.