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Fnt presentation for ittf 2020

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Condition Based
Maintenance and
Predictive Maintenance
Opportunities and challenges for the shipping industry
Konstantinos...

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The common problem with Planned Maintenance
System (PMS)
➢ Most time-based maintenance periods are
arbitrary, based on ini...

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DNV-GL
publication
2014
 DNV-GL, in their research
and publication “Beyond
Condition Monitoring”,
(Knutsen et al, 2014)
i...

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Fnt presentation for ittf 2020

  1. 1. Condition Based Maintenance and Predictive Maintenance Opportunities and challenges for the shipping industry Konstantinos Kamaras Technical Manager FNT at SEA SERVICES ltd. ITTF April 2020
  2. 2. The common problem with Planned Maintenance System (PMS) ➢ Most time-based maintenance periods are arbitrary, based on initial OEM recommendations which in most cases go unquestioned and remain set throughout the vessel’s life. It is difficult for OEM to undertake a full analytical maintenance justification for every piece of equipment. ➢ Most marine vessel failures occur due to unnecessary and excessive maintenance, incorrect installation, poor design and incorrect operation.
  3. 3. DNV-GL publication 2014  DNV-GL, in their research and publication “Beyond Condition Monitoring”, (Knutsen et al, 2014) identified and correlated aviation’s 30-year study of six failure patterns with Maritime’s failure patterns.  DNV-GL study showed that regular overhaul and maintenance was detrimental to machinery condition and functionality
  4. 4. 68% of failures are not age related but maintenance or design related
  5. 5. CBM strategy and cost/risk reduction
  6. 6. CM CBM PdM  Condition Monitoring (CM): the use of advanced technologies in order to determine equipment condition, and potentially predict failure.  Condition Based maintenance (CBM) : the use of CM technology in order to perform maintenance at the exact moment it is needed, prior to failure.  Predictive maintenance (PdM) : a type of CBM that monitors the condition of machinery, and the CM data is used to predict when the asset will require maintenance and prevent equipment failure.
  7. 7. Vibration Analysis as CM signature technology
  8. 8. Images from Mobius Institute
  9. 9.  Motors  Pumps  Fans & blowers VA applications onboard  Alternators  Turbochargers  Compressors  Purifiers Images from HAT 3D machinery library FNT prototype 3-axis Vibration analyzer with embedded advance diagnostic algorithm.
  10. 10. Common faults detected by Vibration Analysis  Unbalance  Misalignment  Bent shaft  Rotating Looseness  Structural Looseness  Soft foot  Eccentricity  Gear wear  Bearing wear  Motor stator and rotor electrical problem  Cavitation  Turbulence  Oil Whirl & Oil Whip
  11. 11. Different approaches available in market  3rd party undertakes the entire task; onboard survey for machinery measurements, analysis of data and machinery condition report  Ship owns measuring equipment. Crew collects data and 3rd party provides the analysis and machinery condition report  Ship owns measuring equipment. Crew collects data and SaaS cloud services is used for automatic evaluation. 3rd party analysis is available on demand if required  On-Line CM for critical machinery
  12. 12. Limitations of each approach  3rd party for onboard survey and analysis/machinery condition report  Ship collects data by her own means and 3rd party provides the analysis and machinery condition report  SaaS (Software as a Service) approach for data upload and automatic evaluation and 3rd party analysis on demand if required  On-Line CM for critical machinery  Overhead cost due to s.e. traveling. Difficulties for survey due to ship volatile schedule  Purchase cost. Crew training/discipline to collect data  Purchase cost, crew training/discipline. Automatic reports in most cases are based on generic band limits. Extra charges may be required for detailed analysis by 3rd party.  High installation cost, no flexibility
  13. 13. To improve reliability we need to measure it. Although for most land industry sectors the ROI on Condition Monitoring has been calculated, you cannot find such a number in maritime industry, because: o Less years of implementation o Calculations are highly affected by freight rates An answer to that can be given if we examine the following: o How much existing maintenance cost? is it really required? o Affect: availability of spares, crew working load, machinery availability, maintenance induced failures o How much reliability improvement of machinery can be succeeded. o Affect: machinery downtime, repair cost, company image to shareholders and market “What gets measured gets managed” William Thomson, Lord Kelvin
  14. 14. Case Study: 2016-2019 Review of Condition Monitoring (VA) results Tankers LNGs LPGs Dry Bulk Containerships Types of machinery  Motors  Centrifugal pumps  Screw – Gear & Hydraulic Pumps  Deepwell Pumps  Reciprocating Pumps  Turbine driven Pumps  Direct Fans  Fans with intermediate shaft  Fans with belt  Lobe Fans  Purifiers with belt  Purifiers with gear  Compressors (reciprocating and rotary)  Alternators  Aux Engines Turbochargers Total number of surveyed machinery 46,696 Total number of companies 10 Type of ships
  15. 15. Only 5.5% of machinery in average requires invasive maintenance For 95% of machinery lubrication, bolt tightness and visual inspection is adequate 84.34% 10.03% 4.39% 1.24% Average of Maintenance Recommendations No maintenance is required 39383 machinery Non-invasive maintenance is required 4684 machinery Invasive maintenance is required to be scheduled 2048 machinery Invasive maintenance is required asap 581 machinery
  16. 16. 5.83% 6.78% 6.93% 6.44% 3.71% 3.61% 2.76% 2.16% 0.59% 0.76% 0.29% 0.24% 70% 75% 80% 85% 90% 95% 100% 2016 2017 2018 2019 15 Containership Fleet average age 5 years old at 2019 sat fair marg unac c An average of 2,500 machinery surveyed per year Progress of Machinery Condition Rating through 4 years
  17. 17. In other words…  Fleet initiate machinery Condition Monitoring semiannually with vibration analysis almost after delivery  2% further improvement of reliability  At 2019: - 2.5% (60 machinery) of machinery required invasive maintenance and - 97.5% (2440 machinery) of machinery required just lubrication, bolts tightening and visual inspections.  At 2019 ships entered 5Y dry- docking with minimum requirements for machinery openings and repairs
  18. 18. 10.45% 4.26% 3.88% 4.02% 4.90% 1.66% 0.97% 0.97% 70% 75% 80% 85% 90% 95% 100% 2016 2017 2018 2019 50 Tankers Fleet average age 8.9 years old at 2019 sat fair marg unacc An average of 6,500 machinery surveyed per year
  19. 19. In other words…  Fleet initiate machinery Condition Monitoring at 2016 before ships 5Y dry-dockings  Since 2017 Fleet machinery are surveyed semiannually with vibration analysis 10.3%improvement of reliability  At 2019: - 5% (265 machinery) of machinery (5 mach. per ship) required invasive maintenance and - 95% (6235 machinery) of machinery required just lubrication, bolts tightening and visual inspections.
  20. 20. In Summary IN A 4-YEAR SPAN, ONLY 5% OF MACHINERY SEEMS TO REQUIRE MONEY AND TIME TO BE FIXED. ANYTHING MORE IS MONEY WASTED. NEW BUILDING VESSELS: CONDITION MONITORING PLAN KEEPS VESSELS’ MACHINERY AS RELIABLE AS NEW (AND EVEN BETTER) FOR THE FIRST 5 YEARS OLDER VESSELS: HUGE RELIABILITY IMPROVEMENT CAN BE SUCCEEDED BY SEMIANNUAL CONDITION MONITORING PLAN Such information can add value and support CBM or PdM plan through the years of implementation
  21. 21. CM data analytics tools Machinery Condition Report in a pdf document is not enough. Ships reports information should be further processed with data analytics tools capable to present : - entire Fleet machinery condition analytics - drill down to Group and ship machinery level - Selected KPIs. Such information can add value and support CBM or PdM plan through the years of implementation Images from SYNOPSIS FNT Fleet Management CM tool
  22. 22. Examples of CM data analytics information MACHINERY CONDITION AMONG SHIPS OF ENTIRE FLEET OR WITHIN A GROUP OF SHIPS MOST COMMON DEFECTIVE MACHINERY AND FAILURE RATE MOST COMMON FAULT TYPES PER MACHINERY MACHINERY CONDITION TREND THROUGH CM IMPLEMENTATION MANUFACTURERS FAILURE RATE PER MACHINERY AND TYPES OF FAULTS
  23. 23. Examples of CM data analytics information Images from SYNOPSIS FNT Fleet Management CM tool
  24. 24. Thank You! Konstantinos Kamaras Technical Manager FNT at SEA SERVICES ltd www.fnt.com.cy Email: info@fnt.com.cy

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