Akademik Veri Yönetim Sistemi
SIMULATION MODELLING PRACTICE AND THEORY, cilt.147, 2026 (SCI-Expanded, Scopus)
As online buyers desire a wider variety of products in smaller quantities with faster delivery times, warehouse technology is evolving to meet their needs. The Robotic Compact Storage and Retrieval System (RCS/RS) provides a solution by offering improved flexibility, continuous operation, and efficient use of available space. This study focuses on a single-robot RCS/RS configuration, in which one robot moves horizontally across a grid-based storage area and accesses vertical stacks while performing storage and retrieval tasks. To access a specific bin, the robot first removes any blocking bins above it and temporarily repositions them to neighboring stacks before delivering the requested bin to the port. To support improved system design, this study implements a large-scale, full-factorial experimental framework to evaluate key factors, including total bin capacity, stack height, arrival rate, and robot velocity. A refined simulation model, incorporating detailed retrieval and storage operations, is developed using ARENA 16.0 under an academic license. ANOVA-based analysis using IBM SPSS Statistics 28.0 is applied to the simulation results to evaluate the effects of system factors and their interactions on performance. Results indicate that robot velocity is the dominant factor, followed by total bin capacity and arrival rate, while stack height has a comparatively minor effect. The analysis also shows that several factor interactions play a significant role, highlighting the importance of considering combined effects when designing RCS/RS systems.