Executive Summary : | Service interruptions in machining environments are a common issue, and queueing models for repairable multi-component systems with service interruptions have significant applications in various sectors. These systems may experience various types of interruptions, such as unexpected server failure, machine failure, common cause failure, server vacation, and preemptive priority. The research proposal aims to enhance the performability, reliability, and availability of unreliable systems operating in machining environments. The study will analyze repairable multi-component systems with service interruptions using various metrics such as mean queue size, throughput, waiting time, failure frequency, machine availability, and delay time. Both Markovian and non-Markovian queueing modeling of multi-component systems have broad applications in various systems, including computer and communications, industrial and manufacturing, power plants, and traffic control. The project will use stochastic theory for analyzing Markov and non-Markovian machine repair models, and various analytical techniques will be used for performance analysis. Cost-benefit analysis and identifying optimal system design parameters are crucial, and numerical optimization and nature-inspired metaheuristics algorithms will be applied.
The study will be validated both theoretically and in terms of managerial insights, providing valuable insights to industrial engineers, system analysts, developers, and practitioners for optimal and efficient system design. The results will be applicable to reduce blocking and delay encountered in the machining environment. |