Dynamic Queueing Model for Smart Manufacturing: A Priority-Based Performance Study - Saini, Balveer; Singh, Dharamender; Sharma, Kailash Chand (Communications in Mathematics and Applications, 2025)
In this paper, we present a Dynamic Priority Queueing Model (DPQM), which effectively solves the problems of traditional queueing models in complex priority scheduling situations in manufacturing systems. The DPQ paradigm uses priority functions, time-based queueing, and advanced scheduling algorithms to schedule tasks elegantly. The priority function swiftly prioritizes tasks based on urgency, relevance, and resource demands, adapting to changing circumstances. The~suggested \(M(t)/G(t)/c\) queueing model extends the \(M/G/c\) model for real-world applications with time-dependent task arrivals and service activities. The model validation and implementation process enable efficient calculations of priority values, lead time, tardiness, usage, and efficiency. The average lead time is 179 minutes, tardiness is 106 minutes, and resource utilization is 100%. The scheduling efficiency improves by 17.6% by effectively sequencing activities to match system priorities. The validation shows that the model prioritizes work and properly maps changing parameters compared to traditional queueing systems. The results indicate that improving adaptive scheduling, real-time feedback systems, and using multiple servers can maximize resource utilization to generate high throughput and eliminate work delays. This approach serves as a robust and adaptable strategy for dynamic scheduling, thoughtfully considering priorities within complex manufacturing environments.