Implementation of Class-Based Storage for Warehouse Layout Optimization in Temperature-Controlled Raw Material Storage (Case Study: PT. XYZ)

Inefficiencies in temperature-controlled raw material warehouses, especially in the Fast-Moving Consumer Goods (FMCG) industry, can hinder production continuity and escalate operational costs. PT. XYZ, a leading cosmetic manufacturer, currently uses a Dedicated Storage system that fails to consider material movement frequency, resulting in limited storage slots, high material handling costs, and ineffective retrieval processes. To overcome these challenges, this study applied the Class-Based Storage (CBS) method by classifying materials into A (fast-moving), B (medium-moving), and C (slow-moving) categories based on their movement frequency. The contribution of this research lies in integrating CBS with the nearest location principle and simulation modeling to provide a structured solution for warehouse layout optimization. A quantitative approach was used by collecting outbound raw material data from January to December 2024, analyzing material movement frequency, and calculating material handling costs. The redesign of the warehouse layout considered the frequency-based classification and used AnyLogic software to simulate the proposed configuration. The analysis also involved calculating rectilinear distances and estimating handling costs based on operator and equipment expenses. The results showed that the proposed CBS-based layout reduced the total travel distance by 27.55% and decreased daily material handling costs by 28.67%. Additionally, high-frequency materials were positioned closer to the input/output points, improving accessibility and retrieval speed. The simulation confirmed increased warehouse efficiency, better space utilization, and reduced operator workload. In conclusion, the implementation of the CBS method in warehouse layout design significantly improved operational performance and reduced logistics costs. This study serves as a reference for companies managing temperature-sensitive inventory and provides a foundation for future research incorporating real-time inventory tracking and dynamic slotting systems.