Conflicting Optimization Goals in Manufacturing Networks: A Statistical Analysis Based on an Idealized Discrete-Event Model

Abstract

Performance optimization is a crucial issue in present-day manufacturing systems. Here, we reconsider the problem of conflicting optimization goals, with a focus on low inventory levels and short throughput times. Based on an idealized discrete-event model of a complex small-scale manufacturing network, the impact of different production strategies as well as order policies on both quantities is carefully examined and systematically compared. Qualitative similarities of different scenarios regarding inventory levels and throughput times are investigated in detail by means of cluster analysis. Our results provide new insights into the influence of different key parameters on the complex material flow dynamics in manufacturing networks, and their reflection in different optimization goals.