Simulation-based joint optimization of fleet system modularity and level of repair decisions considering different failure rates of components

Abstract

PurposeModularization and level of repair analysis for fleet system influences every phase of the system life cycle. Modular based fleet system design raises new issues since the maintenance/repair services introduces further requirements than traditional product engineering. The decision of modular system and level of repair plays an important role to reduce the Life Cycle Costs (LCC) of fleet maintenance system. The concept of modularity has been extended to services in maintenance for the varieties of fleet systems such as wind turbines, gas turbines, advance machine tools and aircrafts etc. System modularity allows the designers to use of different design alternatives and ease of fault diagnosis, repair and services. The purpose of this paper to develop a joint optimization approach for optimal selection of modular design and level of repair decisions. Usually these two decisions are taken separately.Design/methodology/approachIn the proposed joint approach, level of repair analysis is used to obtain the optimal modular design decisions with reduced life cycle cost. In the existing research, the effect of system modularity on the level of repair decisions is investigated. The simulation-based approach is used to solve this joint problem. Which is rarely seen in the existing literature. A genetic algorithm-based simulation is used to investigate the joint problem. The proposed approach also evaluates all the possible configurations of modular design to justify the integrated effect of modularity and maintenance decisions, that is Level of Repair (LOR).FindingsThis paper highlights interactive effect of system modularity and level of repair decisions for the system operated in multi-echelon maintenance network. A comparative study is provided on effect of system modularity and level of repair decisions considering the time dependent failure rate and constant failure rate of the system components. A simulation based joint approach is used to solve this problem. The results obtained from the investigation are shown that modularity plays an important role to allocate modularity and level of repair decisions for the fleet system. The novelty of this research work is to identify the role of modularization to optimizing the level of repair decisions. The models, that is time-dependent failure rate and constant failure rate presented in this study provides more practical approach to deal the modularity and level of repair analysis.Research limitations/implicationsThe proposed joint approach illustrates using a numerical case of a mechanical system operated at fleet level. More modular structure in terms of number of modules in the machine may be presented for an industrial case. Additionally, the joint approach can also be extended for the any other consumer product and system. But, the prime motive of the paper is to highlights the importance of the modular design while selecting the level of repair decisions.Originality/valueThis is the first work which consider the joint optimization of modular design and level of repair analysis to the best of authors knowledge. Present paper is a more practical approach for identifying the modular design and level of repair decisions for the system operated at fleet level.