To analyse the performance measures of complex repairable systems having more than two states, that is, working, reduced and failed, it is essential to model suitably their states so that the system governs a stochastic process. In this paper, the application of time-homogeneous Markov process is used to express reliability and availability of feeding system of sugar industry involving reduced states and it is found to be a powerful method that is totally based on modelling and numerical analysis. The selection of appropriate units/components in designing a system with different characteristics is necessary for the system analyst to maintain the failure-free operation. Keeping this concept in this study, the steady state availability of concern system is analysed and optimized by using a popular search technique, genetic algorithm. The objective of this paper is to consider the system operative process as Markov process and find its reliability function and steady state availability in a very effective manner and also to obtain an optimal system designing constituents which will allow a failure-free operation for long time period as required for maximum system productivity. The system performance measures and optimized design parameters are described and obtained here by considering an illustrative example. 1. Introduction Process industries like chemical industry, sugar mill, thermal power plant, oil refineries, paper plant, fertilizer industry, and so forth have major importance in real life situations as they fulfil our various unavoidable requirements. The demand of product quality and system reliability is on an increase day by day. Further the failure is a random phenomenon, always associated with the operating state of any physical system and its causes are either deterioration in the components of the system and/or man handling errors. Therefore the main concern is to maintain system performance measures such as reliability and availability to achieve high profit goals and productivity in regard to system failures. These measures are considered as most significant factors associated with nonrepairable and repairable systems, respectively [1]. Nowadays industries are becoming quite complex in structure due to the advancement in the technology and therefore it is a difficult job for plant personnel/system analyst to decide proper maintenance policy. By properly designing the system, the factors such as performance, quality, productivity and profit, can easily be enhanced up to the desired goal of demand [2]. While designing, it is convenient to
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