RAM ANALYSIS OF AN INDUSTRIAL SYSTEM USING GENETIC ALGORITHM

Abstract

Industrial components are mostly complex and considered as repairable. Availability analysis has been an important issue in the design field of any industrial system. As the system now a days are becoming more complex and complicated, so their failure and repair data. Thermal Power Plant has many complex industrial systems, such as aerator, id fans, boiler, super heater, reheater, turbine, etc. Some components of the thermal plant are the subject of study here. The reliability, availability, Mean time between failures (MTBF), Expected number of failures (ENOF's), failure rate and repair time for any industrial system are to be calculated using modified methods such as GA. Mostly industrial systems are stochastic in nature, thus use of genetic algorithm. GABLT (Genetic algorithm based lambda-tau technique) is a hybridized technique in which two important tools namely, Lambda-tau methodology and GA are hybridized to analyse the complex reparable industrial system. The main aim of this analysis is to obtain the preference order in which components of a pulverizer unit are to be repaired. To carry out this analysis, the RAM parameters are further utilized to find RAM-index which is the main criteria to decide the preferential order in which the attention should be given to the components for better performance of the system.