Lean design and analysis of a milk-run delivery system: Case study

Abstract

Multiple discrete event simulation models are developed to represent a milk-run delivery system in an automobile emissions system production facility as part of a logistics system overhaul. The aim of this study is to analyze resupply configurations and variability in key model inputs in order to make recommendations based on supply train utilization and workstation starvation. This study includes three experiments that compare optimized routing, recommended routing, and on-demand resupply systems. Sensitivity analyses are conducted to measure the effects of various factors such as number of supply trains, travel speeds, and load and unload times to find the best combination of input parameters. The results of the proposed simulation models demonstrated potential impacts of a milk-run delivery framework on pull systems with limited transport capabilities, but diminished improvements on systems with multiple supply trains.