PERFORMANCE OPTIMIZATION OF RUBBER TUBE EXTRACTION SYSTEM USING NATURE BASED ALGORITHMS
Keywords:
Markov Modelling, Availability, Genetic Algorithm, Whale Optimization Algorithm, Particle Swarm OptimizationAbstract
Reliability and maintenance engineering is a powerful tool which enables the industries to find ways of costs savings and operational improvement opportunities. In this paper, the rubber tube extraction system is considered to evaluate the availability of the system under different maintenance conditions. The methodology employed for analysis purpose is based upon Markov Modeling in which failure and repair rates of the units comprising the system are taken as constant. Differential equations are derived and solved by Laplace transform to attain state probabilities. Solving reliability problems using meta-heuristic algorithms have attracted increasing thought in recent years. Various recent nature based algorithms are considered to solve availability optimization problem. The computational results were carried out on different algorithms and their experimental results are exhibited and compared with best obtained solutions. The analysis enables to find the local maxima of the objective function, which will help plant personnel to increase the daily production with optimum parameters.
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