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Optimizing Warehouse Capacity in Industrial Manufacturing Through Centralised Storage System Integration

Year: 2025

Type: article

Abstract: To enhance cost-efficiency and streamline logistics operations in industrial manufacturing, centralised warehouse systems have increasingly been adopted as a strategic alternative to decentralised storage structures.In this study, the storage framework of a lubricating oil production facility has been examined to assess the operational implications of decentralised warehousing currently in use.It has been identified that the existing system incurs excessive operational costs, prolongs handling times, and demands a disproportionately high labour force, thereby constraining the overall efficiency of the supply chain.In response to projected increases in production output, the feasibility of constructing a centralised, gravity-fed warehouse equipped with automated and robotic technologies for the handling of palletised goods has been investigated.This proposed facility would be strategically integrated with the product packaging unit to form a unified logistical hub within the manufacturing site.A comprehensive analysis was conducted to determine the optimal location for the central warehouse, with key criteria including material flow, space availability, connectivity to production lines, and scalability.The results indicate that the implementation of a centralised automated storage and retrieval system (AS/RS) would significantly improve warehouse throughput, reduce operational expenditures, and align closely with long-term production expansion plans.Additionally, the integration of advanced storage technologies is expected to enhance inventory visibility, minimise human error, and support real-time production coordination.It is concluded that the establishment of a central warehouse facility, functioning as a core node in the internal logistics network, is essential for achieving sustainable operational efficiency and future-proofing the lubricating oil manufacturing process.

Source: Journal of Intelligent Management Decision

DOI: 10.56578/jimd040204

Authors: Žarko Jovanović, Željko Stević, Stojan Simić

Institution: University of East Sarajevo

Language: English

Topic: Advanced Manufacturing and Logistics Optimization

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production

Open Access status: hybrid

OpenAlex ID: W4410830737