Block Replacement Modeling for a Block of Air Conditioners with Discrete-Time Markov Chain Approach

摘要

This paper, deals with the development of a model for group replacement of a block of air conditioners using discrete-time Markov chains. To make the model represent the realistic approach, two intermediate states i.e. minor repair state and major repair state are introduced between working and breakdown states of the system. Transition probabilities for future periods are estimated by spectral decomposition in first order Markov chain and by Moving Weighted Transition model for second order Markov chain. With these probabilities, the number of systems in each state and the corresponding total maintenance costs are computed accordingly. The predicted inflation for air conditioners in India and the real value of money using Fisherman's relation are employed to study and develop the real time mathematical model for block replacement decision making.