IMPROVING SYSTEM RELIABILITY UNDER BUDGETARY CONSTRAINT

Abstract

In this thesis a system is designed to improve its reliability under given budgetary constraint. Models are developed for the system to enhance the reliability by adding standby redundancies and incorporative appropriate maintenance. All the feasible states and, failure and repair transitions are identified to develop the system model. Due to the limitation of the Markov model the failure and repair rates are taken as constant. The sets of ordinary differential equations are obtained for the change of probability of being in respective system states with respect to time in each model. The system of rate equations is solved using Runge – Kutta method in MatLab. The system reliability assessment is based on the sum of probabilities of all working states. Dynamic programming is used for optimizing the reliability under cost limitation. These results are helpful to design the highly reliable systems for various industrial applications like thermal power plant, machineries used in medical field, aviation industries etc.