Workforce and Logistics Centered Lineside Stock Optimization: A Case Study in automotive Industry.

Abstract

In general assembly in the automotive industry, material handling is crucial in terms of system efficiency and overall costs. Line balancing and optimized cycle times are heavily dependent on the line-side stock layout and assignment. This paper presents a hybrid approach for line-side stock area layout optimization under consideration of worker cost and logistics accessibility. While certain layouts are evaluated by a single-agent production simulation of different product variations, a genetic algorithm is proposed to optimize the layout with respect to multiple criteria. The resulting approach considers line-side stock dimensions as well as accessibility restrictions to enable automated line-balancing.