Value-Chain Automation in Beverage Logistics: Throughput, Capacity, and Cost Avoidance via Queueing Models - Olaolu Samuel Adesanya,; Chizoba Michael Okafor,; Omoize Fatimetu Dako,; Akindamola Samuel Akinola, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024)
The beverage industry faces increasing demand for operational efficiency across complex supply chains. This study investigates the role of value-chain automation in enhancing throughput, capacity utilization, and cost avoidance through queueing theory models. Using a combination of discrete-event simulation and analytical modeling, the research evaluates multiple automation strategies, including real-time scheduling, automated inventory replenishment, and robotic handling at bottleneck points. Findings indicate that integrating queueing-based automation can increase throughput by up to 22%, reduce average system wait times by 18%, and mitigate operational costs associated with idle resources and delays. The results further highlight the importance of prioritization strategies and capacity allocation in multi-echelon beverage logistics networks. Implications are drawn for both strategic planning and operational management, providing a data-driven foundation for technology investment decisions in beverage supply chains.
Keywords: Beverage logistics; queueing models; value-chain automation; throughput; capacity; cost avoidance