Performance Analysis and Optimization for the Yarn Pre-Spinning Unit of a Textile Industry

The paper focuses on the performance analysis and optimization for the yarn pre-spinning unit of a textile industry using Genetic Algorithm (GA) technique. Yarn pre-spinning unit has seven subsystems arranged in hybrid configuration. For the performance evaluation of the system, a performance evaluating model has been developed with the help of mathematical formulation based on Markov- Birth-Death process using a transition diagram. Then, the overall performance of the concerned system has been first analyzed and then optimized using GA. The optimum values of failure/repair rates for maximum system availability have also been determined. By varying the parameters of GA, the optimum system availability achieved is about 8% more with the best possible combinations of the failure and repair rates of all the subsystems as compared to the best possible availability level obtained with the help of Markov Birth-Death process. Therefore, the findings of the paper would be highly useful to the textile plant management for the timely execution of proper maintenance strategies and thus to enhance the overall performance of the system concerned