MHI 1 Development of Quantitative Reliability Centered Maintenance Method April 27-28,1999 by Shinya Kamata (Mitsubishi Heavy Industries, Ltd) Hiroshi.

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Presentation transcript:

MHI 1 Development of Quantitative Reliability Centered Maintenance Method April 27-28,1999 by Shinya Kamata (Mitsubishi Heavy Industries, Ltd) Hiroshi Sakuda (Kansai Electric Power Co., Inc) at 5TH KOREA-JAPAN PSA WORKSHOP, SEOUL

MHI Contents 1. Overview of RCM 2. RCM evaluation procedure 3. Approaches with consideration of aging effects 4. Maintenance selection logic 5. Trial evaluation 6. Conclusion 2

MHI 1. Overview of RCM Increase of plant operation time Increase of PM cost Lack of maintenance staffs Failure experiences Sys. Reliability Analysis PSA information RCM Optimization of PM Expert judgment PM : Preventive Maintenance RCM : Reliability Centered Maintenance Background Reduction of PM cost 3

MHI 1. Overview of RCM Basic concept l Optimize maintenance task selection based on system reliability and plant safety l Reflect the aging effects and failure experiences of components l Reduce maintenance tasks and cost 4

MHI 2. RCM evaluation procedure 5 Selection of System Evaluation of Sys. Reliability PSA Component Importance Selection of PM strategy Maintenance Failure Experiences Re-evaluation of Sys. Reliability Alteration of PM strategy Alteration of PM strategy No New Strategy is Accepted Yes Target Satisfied? Target Satisfied? NoYes Cost Evaluation

MHI 2. RCM evaluation procedure 6

MHI 3. Approaches with consideration of aging effects 7 Survey of aging failure ex.,erosion,corrosion,leak, crack….. Failure DB Occurrence history of component failures Fitting curve by Weibull functionWeibull chart Cumulative failure frequency 1 lnln R(t) F(t) time(lnt)time t m F(t)=1-exp - t 0 F(t) : Failure distribution function m : shape parameter t 0 : scale parameter ・ ・ ・ ・・ ・ ・ ・ ・ ・ ・ ・ ・ Aging model

MHI 3. Approaches with consideration of aging effects 8 Establishment of F(t) in a failure mode t m F(t)=1-exp - t 0 λ 0 →Q 0 λ N →Q N ΔQ=Q N -Q 0 ΔQ:Sys. unavailability change ΔQ ε λ(T)=F(t)/ (1-F(t))dt a=λ(T N )/ λ(T 0 ) λ N =aλ 0 (failure rate for new interval) λ(t) F(t) λ(T)= (1- F(t))dt T0T0 TNTN time Q : Sys. unavailability ε : permitted value of ΔQ λ 0 : Basic failure rate T : Replacement interval Failure rate model T ∫ 0 T ∫ 0

MHI 4. Maintenance selection logic Rank C CD Rank A,B CD ? TD ? Rank D Re-evaluation of Q Survey of interval extension Survey for repeal of PM ΔQ<ε keeping interval ・ New interval ・ Repeal of PM ・ Facilities improvement ・ FFT No Yes No Yes A ~ D component importance rank CD : Condition Directed PM TD : Time Directed PM FFT : Failure Finding Task Logic tree analysis 9

MHI Example of RCM Results for PWR plant l Evaluate the effect of the alteration of the replacement interval on system reliability in Residual Heat Removal system (main 12 components) case1 : RHR pump (2years 5years) MOV (10years 15years),AOV(4years 6years) case2 : RHR pump (2years 5years) MOV (10years 20years),AOV(4years 8years) 5.Trial evaluation 10 Sys. Reliability : Not meaningful change Cost reduction : Effective Results

MHI 5. Trial evaluation 11 Visual information of ΔQ and ΔC Survey for several PM programs Ground for PM mitigation and cost optimization Reduction of PM management ΔQ : Sys. Unavailability change ΔC : Cost change ε : Permitted valve of ΔQ Advantages of RCM-proto type system ΔQ(%) ε ΔC(%)

MHI 5. Trial evaluation Output image for Logic Tree Analysis 12

MHI 5. Trial evaluation Output image for the relation between ΔQ and ΔC 13

MHI 6. Conclusion 1. Development of quantitative RCM method ・ Approaches with consideration of aging effects ・ RCM procedure based on Sys.reliability and plant safety ・ Trial application of the method to PM programs 2. Future subjects ・ Development of component failure DB ・ Combination with deterministic information (ex, service life,and operation environment of the component) 14