Value-Chain Automation in Beverage Logistics: Throughput, Capacity, and Cost Avoidance via Queueing Models
Keywords:
Beverage logistics, queueing models, value-chain automation, throughput, capacity, cost avoidanceAbstract
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.
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References
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