Integration of Optimization Methods into Simulation Technology for Manufacturing via Warehouse Optimization

Abstract

The manufacturing industry is transitioning towards digital, intelligent, and sustainable practices. However, small and medium-sized enterprises (SMEs) often lack the resources and expertise to leverage digital tools in their research and development (R&D) activities. This paper demonstrates warehouse optimization using a Genetic algorithm to optimize pallet transfers within a flexible manufacturing system (FMS) cell. The simulation model, created with Visual Components software and an external Python application, includes a warehouse with nine Euro pallets and a stacker crane. The optimization reduced the total duration of pallet transfers by approximately 20 seconds (8.1%). Integrating simulation and optimization tools offers significant benefits, including enhanced production efficiency, reduced operational costs, and improved decision-making capabilities. This demonstration highlights the practical applications and advantages of these digital tools for SMEs, showcasing their potential to streamline processes and foster sustainable manufacturing practices. The results have sparked longer-term collaborations with local industry, emphasizing the practical applications and advantages of these digital tools in enhancing manufacturing efficiency.