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Knowledge based asset integrity for wind farms

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Information about Knowledge based asset integrity for wind farms
Business & Mgmt

Published on March 6, 2014

Author: LREnergy

Source: slideshare.net

Description

Asset integrity services such as KBAI™ (Knowledge Based Asset Integrity) provide risk profiling for key components based on assessment of data from a variety of sources. This allows owners and operators to better predict where problems will occur. Similar approaches are already regularly used by owners and operators in other industries such as oil and gas. Such systems provide a maintenance and/or inspection task plan that is optimised specifically for the asset and the business. - See more at: http://blog.lr.org/2013/05/kbai-the-definitive-addition-to-your-om-strategy/#sthash.TWKPtbTK.dpuf
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Lloyd’s Register Energy Knowledge Based Asset Integrity (KBAI) for wind farms Andrew Martin Technical Manager Lloyd’s Register Energy Working together for a safer world

Lloyd’s Register Energy Knowledge Based Asset Integrity (KBAI) (events per year) •Equipment type and items used •Age, usage, environment, etc •Equipment condition (based on visual inspection, past maintenance, failure causes and condition monitoring, etc) 1 Probability Ranking Likelihood of failure HIGH 2 MED HIGH (£ impact per event) MEDIUM 3 4 Maintenance and inspection task plan optimised to the asset and the business •Includes industry best practices •May increase or decrease current maintenance LOW 5 E D C B A Consequence ranking Consequence of failure (impact per event) Lloyd’s Register Energy •Disruption to business •Environmental + health and safety impacts •Reputation – public/political

Lloyd’s Register Energy Why this approach? • Improves reliability • Consequential loss reduction - increasing exported electrical power • Provides justification for: • • Actions to reduce breakdowns such as prioritising replacements • Lloyd’s Register Energy Establishing the correct level of maintenance and hence maintenance expenditure Integrity measurements for additional failure modes to give further confidence in asset condition

Lloyd’s Register Energy Case study – port cranes • Breakdown duration reduced • Quay Side crane (QS) ‐24%; • Rubber Tyred Gantry cranes (RTG) ‐ 12% • Maintenance cost savings: QS 17%; RTG 32% • Significant commercial operational benefits: • Crane efficiency enhanced • Containers handled and related safety all improved • Ship turnaround and throughput improved Lloyd’s Register Energy

Lloyd’s Register Energy Case study – oil refinery piping • Pilot study on fixed equipment on eight process units led to $1.5m in turnaround cost savings and $7m in risk reduction • Rolled out to 6 further refineries resulting in over $160m in risk reduction and on-going savings in turnaround plans. Achieved within 3 years. • Key lesson learned is the need to continually audit and manage the system to ensure the alignment of people processes and technology Identifying the DELIVERED RISK REDUCTIO N VALUE Finding t his CUI problem w as est imat ed t o save t he ref iner $2M M . An addit ional $4M M in lost product ion w as avoided w hen RBM I ident if ied exchanger problems bef ore t hey could af f ect t he saf e operat ion of t he ref inery. This added up t o over $6.373 M M in reduced risk all w it hin 3 mont hs of complet ing t he project . RBM I - RELIABILITY BASED M ECHANICAL INTEGRITY Achieving Value The small branch connection on the line was found to be corroded nearly through-wall. Continued operation without finding and repairing the damaged connection would have resulted in a failure with potentially serious effect. Lloyd’s Register Energy

Lloyd’s Register Energy What-if Analysis Cumulative Risk Curves Safety Losses 1,800,000 1,600,000 90% Risk Reduction Achieved by Cumulative Risk ($ Cumulative Risk ($ / yr) / yr) 1,400,000 Addressing 10% of Equipment As-Found Risk 1,200,000 Risk Distribution 1,000,000 20 246 2 235 3 238 4 232 800,000 1 5 971 600,000 10 72 71 76 88 5 81 77 71 35 5 74 74 71 36 0 18 12 17 65 E 317 D 269 C 260 B 112 Risk Distribution 0 1 1 3 8 A 13 2 1 238 2 248 3 251 4 232 5 971 400,000 1 61 91 76 88 1 81 70 82 35 0 79 74 71 36 0 17 13 17 65 0 0 0 5 8 E 317 D 269 C 260 B 112 A 13 As-Left Risk 200,000 0 1 60 119 178 Lloyd’s Register Energy 237 296 355 414 473 532 591 650 709 768 827 Equipment Component Count 886 945 1004 1063 1122 1181 1240 1299 1358

Configuration: Risk units & probability factors are identified Lloyd’s Register Energy for each asset type Risk Units Probability Factors Lloyd’s Register Energy

Lloyd’s Register Energy Generate planned maintenance tasks System Type A Lloyd’s Register Energy

The prediction for next year shows criticality has changed for five Lloyd’s Register Energy risk units – undertake pre-emptive work on these Date for criticality calculation Criticality change Lloyd’s Register Energy

Lloyd’s Register Energy Summary • Capture relevant data to make informed decisions and update risk profile both at implementation stage and through life • Update maintenance planning and task priorities • Provide effective failure mode management in response to changing equipment condition • Record operating knowledge even if staff/contractors change • Facilitate knowledge transfer across the asset portfolio Lloyd’s Register Energy

Lloyd’s Register Energy AndrewMartin Technical Manager, RBMI Aberdeen Lloyd’s Register Energy E: andrew.martin@lr.org Lloyd’s Register Energy 71 Fenchurch Street, London EC3M 4BS @LREnergy Follow LR Energy on LinkedIn Working together for a safer world Lloyd’s Register and variants of it are trading names of Lloyd’s Register Group Limited, its subsidiaries and affiliates. Copyright © Lloyd’s Register Energy. 2014. A member of the Lloyd’s Register group.

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