Inspection Planning of Fatigue Deteriorating Structures Using Genetic Algorithm

Fujimoto, Yukio; Kim, Sung Chan; Hamada, Koichi

doi:10.2534/jjasnaoe1968.1997.182_729

Cited by 7 publications

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References 5 publications

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“…The goal of RBI is typically to optimize the timing and type of inspections, and likewise the maintenance actions for RBM. RBI and RBM have been extensively applied to deteriorating structures, such as offshore structures [9], steel structures [7,10], floating production, storage, and offloading facilities [11,12], pipelines [13][14][15][16][17], refinery piping [18], bridges [19,20], nuclear power plants [21], and processing plants [22].…”

Section: Introductionmentioning

confidence: 99%

“…Barone and Frangopol [20] used a genetic algorithm to determine the optimal inspection frequency for a deteriorating bridge. Fujimoto et al [10] used a genetic algorithm to determine the optimal inspection times and inspection type of fatiguing structures with single or multiple components. They simplified the framework by ignoring the failure cost and instead using a reliability constraint.…”

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confidence: 99%

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Genetic Algorithm for Inspection and Maintenance Planning of Deteriorating Structural Systems: Application to Pressure Vessels

Haladuick

Dann

2018

Infrastructures

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For engineering systems, decision analysis can be used to determine the optimal decision from a set of options via utility maximization. Applied to inspection and maintenance planning, decision analysis can determine the best inspection and maintenance plan to follow. Decision analysis is relatively straightforward for simple systems. However, for more complex systems with many components or defects, the set of all possible inspection and maintenance plans can be very large. This paper presents the use of a genetic algorithm to perform inspection and maintenance plan optimization for complex systems. The performance of the genetic algorithm is compared to optimization by exhaustive search. A numerical example of life cycle maintenance planning for a corroding pressure vessel is used to illustrate the method. Genetic algorithms are found to be an effective approach to reduce the computational demand of solving complex inspection and maintenance optimizations.

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