
Intelligent Maintenance Prioritization and Optimization Strategies for Thermal Power Plant Boilers
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c1007.1083s19
Subject(s) - reliability engineering , analytic hierarchy process , preventive maintenance , particle swarm optimization , boiler (water heating) , scheduling (production processes) , thermal power station , shutdown , computer science , engineering , optimal maintenance , operations research , operations management , waste management , machine learning , nuclear engineering
Steam boiler also known as steam generator is an integral component in thermal power plants requiring effective maintenance scheduling to extend the overall life cycle of the boiler. However, steam boilers are commonly plagued with issues such as boiler shutdown and tube leakage. Industry experts adopted preventative maintenance to overcome the repetition of outage in steam boilers. This method is flawed in the aspect of redundant maintenance activities. The repetition in maintenance activities will lead to reduced work productivity and increased maintenance operational costs. In this study, a maintenance optimization system specialized in ranking, prioritization and optimization based on Analytical Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) are chosen. The AHP is used to rearrange the maintenance activities according to its priority while the PSO is an intelligent swarm used to optimize the operational duration and maintenance cost based on the result formed from AHP after implemented using MATLAB software. This work proposes maintenance scheduling based on minimization of the objectives focusing on the forming new list of the maintenance activities with the optimal operational duration and maintenance cost.