Knowledge Based Asset Integrityfor wind farmsAndrew MartinTechnical ManagerLloyd’s Register EMEA23 May 2013
Lloyd’s Register – A Group Overview• Celebrated our 250 year anniversary in 2010• 8,000 employees of 90 nationalities• 237...
Knowledge Based Asset Integrity (KBAITM)Likelihood of Failure(events per year)• Equipment type and items used• Age, usage,...
Why this approach?• Improves reliability• Consequential loss reduction - increasingexported electrical power• Provides jus...
Case study – Port Cranes• Breakdown duration reduced• Quay Side crane (QS) ‐24%;• Rubber Tyred Gantry cranes (RTG) ‐12%• M...
Case study – Oil refinery piping• Pilot study on fixed equipment on eightprocess units led to $1.5m in turnaroundcost savi...
Configuration: Risk Units & Probability Factors areidentified for each asset typeRisk UnitsProbability Factors
Configuration: Consequence factors - Economic, Safety,Environmental & Reputational or client specified
Generate planned maintenance tasksSystem Type A
This year 4 risk units in the asset are medium-high criticalityShows number ofrisk units in eachcriticality band
Next year prediction shows criticality has further changed forone risk unit – undertake pre-emptive work on thisDate forcr...
Summary• Capture relevant data to make informeddecisions and update risk profile both atimplementation stage and through l...
Wind farm pilot study – Knowledge Based Asset Integrity• Actively seeking a partner to run a secondpilot project
Services are provided by members of the Lloyds Register Group.For further information visit www.lr.org/entitiesThank you –...
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Andrew martin - Knowledge Based Asset Integrity (KBAI™)

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Andrew martin - Knowledge Based Asset Integrity (KBAI™)

  1. 1. Knowledge Based Asset Integrityfor wind farmsAndrew MartinTechnical ManagerLloyd’s Register EMEA23 May 2013
  2. 2. Lloyd’s Register – A Group Overview• Celebrated our 250 year anniversary in 2010• 8,000 employees of 90 nationalities• 237 offices globally• Four business divisions:• Marine• Energy• Management Systems• Transportation• 2011/12 turnover £893m• A Registered Charity• Supports the Lloyd’s Register Educational Trust (LRET)Come and see us on Stand J56
  3. 3. Knowledge Based Asset Integrity (KBAITM)Likelihood of Failure(events per year)• Equipment type and items used• Age, usage, environment, etc• Equipment condition (based onvisual inspection, pastmaintenance, failure causes andcondition monitoring, etc)Consequence of Failure(impact per event)• Disruption to business• Environmental + Health and Safety impacts• Reputation – Public/PoliticalConsequence RankingABCDEHIGHMED HIGHMEDIUMLOW12345ProbabilityRankingMaintenance and InspectionTask Plan optimised to theasset and the business(£ impact per event)• Includes industry best practices• May increase or decrease currentmaintenance
  4. 4. Why this approach?• Improves reliability• Consequential loss reduction - increasingexported electrical power• Provides justification for:• Establishing the correct level ofmaintenance and hence maintenanceexpenditure• Actions to reduce breakdowns such asprioritising replacements• Integrity measurements for additionalfailure modes to give furtherconfidence in asset condition
  5. 5. 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 allimproved• Ship turnaround and throughputimproved
  6. 6. Case study – Oil refinery piping• Pilot study on fixed equipment on eightprocess units led to $1.5m in turnaroundcost savings and $7m in risk reduction• Rolled out to 6 further refineries resultingin over $160m in risk reduction and on-going savings in turnaround plans.Achieved within 3 years.• Key lesson learned is the need tocontinually audit and manage the systemto ensure the alignment of peopleprocesses and technologyRBMI - RELIABILITY BASED MECHANICAL INTEGRITYAchieving ValueIdentifying the DELIVERED RISKREDUCTION VALUEFinding this CUI problem wasestimated to save the refiner $2MM.An additional $4MM in lostproduction was avoided when RBMIidentified exchanger problems beforethey could affect the safe operation ofthe refinery. This added up to over$6.373 MM in reduced risk all within 3months of completing the project.The small branch connection on the line was found to be corroded nearlythrough-wall. Continued operation without finding and repairing the damagedconnection would have resulted in a failure with potentially serious effect.
  7. 7. Configuration: Risk Units & Probability Factors areidentified for each asset typeRisk UnitsProbability Factors
  8. 8. Configuration: Consequence factors - Economic, Safety,Environmental & Reputational or client specified
  9. 9. Generate planned maintenance tasksSystem Type A
  10. 10. This year 4 risk units in the asset are medium-high criticalityShows number ofrisk units in eachcriticality band
  11. 11. Next year prediction shows criticality has further changed forone risk unit – undertake pre-emptive work on thisDate forcriticalitycalculationCriticalitychange
  12. 12. Summary• Capture relevant data to make informeddecisions and update risk profile both atimplementation stage and through life• Update maintenance planning and taskpriorities• Provide effective failure mode management inresponse to changing equipment condition• Retain operating knowledge even ifstaff/contractors change• Facilitate knowledge transfer across the assetportfolio, irrespective of location
  13. 13. Wind farm pilot study – Knowledge Based Asset Integrity• Actively seeking a partner to run a secondpilot project
  14. 14. Services are provided by members of the Lloyds Register Group.For further information visit www.lr.org/entitiesThank you – Any questions?Andrew MartinTechnical ManagerLloyd’s Register EMEA71 Fenchurch StreetLondon, EC3M 4BST +44 (0)7713 985983E Andrew.Martin@lr.orgw www.lr.org/energy

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