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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
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.
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
68% of
failures are
not age
related but
maintenance
or design
related
CBM
strategy
and
cost/risk
reduction
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.
Vibration Analysis as CM signature technology
Images from Mobius Institute
 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.
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
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
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
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
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
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
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
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
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
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.
Fnt presentation for ittf 2020
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
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
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
Examples of CM data analytics information
Images from SYNOPSIS FNT Fleet Management CM tool
Thank You!
Konstantinos Kamaras
Technical Manager
FNT at SEA SERVICES ltd
www.fnt.com.cy
Email: info@fnt.com.cy

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Fnt presentation for ittf 2020

  • 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. 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. 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. 68% of failures are not age related but maintenance or design related
  • 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. Vibration Analysis as CM signature technology
  • 8. Images from Mobius Institute
  • 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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.
  • 21. 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
  • 22. 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
  • 23. 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
  • 24. Examples of CM data analytics information Images from SYNOPSIS FNT Fleet Management CM tool
  • 25. Thank You! Konstantinos Kamaras Technical Manager FNT at SEA SERVICES ltd www.fnt.com.cy Email: info@fnt.com.cy