Please use this identifier to cite or link to this item:
https://dspace.iiti.ac.in/handle/123456789/7032
Title: | Joint optimization of reliability design and level of repair analysis considering time dependent failure rate of fleet system |
Authors: | Lad, Bhupesh Kumar |
Keywords: | Failure (mechanical);Failure analysis;Genetic algorithms;Life cycle;Monte Carlo methods;Product design;Reliability analysis;Systems analysis;Turnaround time;Inherent reliabilities;Joint optimization;Level of repair analysis;Maintenance decisions;Maintenance methodology;Maintenance repairs;Reliability design;Time dependent failure;Repair |
Issue Date: | 2020 |
Publisher: | Totem Publishers Ltd |
Citation: | Rawat, M., & Lad, B. K. (2020). Joint optimization of reliability design and level of repair analysis considering time dependent failure rate of fleet system. International Journal of Performability Engineering, 16(6), 821-833. doi:10.23940/ijpe.20.06.p1.821833 |
Abstract: | This paper presents a joint optimization approach of reliability design (RD) and level of repair analysis (LORA) for fleet systems. A fleet is a multi-machine, multi-indenture system. The present paper investigates the interrelated effect of product design in terms of modularity and inherent reliability with maintenance repair strategy. It proposes a joint approach for the configured fleet system design of reliability and repair decisions at the initial design phase considering the time dependent failure rate of components. The consequences of each design options and level of repair decisions are evaluated based on life cycle cost performance. Additionally, the failure of the machine is modeled using time dependent failure rate models at the part level of the indenture. The methodology integrates many interdependent maintenance decisions such as location of maintenance, type of maintenance (repair/replacement/discard), and indenture level at which maintenance should be performed. The time dependent failure rate of components provides flexibility to consider the effect of practical behavior on the overall fleet level maintenance methodology. This makes the fleet methodology more realistic in terms of optimizing the reliability design and maintenance repair decisions (LORA). This joint problem is the complex combinatorial type problem. To obtain appropriate integrated and disintegrated results for fleet system design and level of repair decisions, genetic algorithm (GA)-based Monte Carlo simulation is used. © 2020 Totem Publisher, Inc. All rights reserved. |
URI: | https://doi.org/10.23940/ijpe.20.06.p1.821833 https://dspace.iiti.ac.in/handle/123456789/7032 |
ISSN: | 0973-1318 |
Type of Material: | Journal Article |
Appears in Collections: | Department of Mechanical Engineering |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
Altmetric Badge: