26
Data driven predictive maintenance strategy IEA Wind Task 33 Workshop Dr Robin Elliott, Senior Consultant 23 rd September 2015

Data driven predictive maintenance strategy - … · Data driven predictive maintenance strategy ... o Automotive, heavy industry, marine, aerospace. ... predictive maintenance

Embed Size (px)

Citation preview

Data driven predictive

maintenance strategy

IEA Wind Task 33 Workshop

Dr Robin Elliott, Senior Consultant

23rd September 2015

© Copyright 2015Slide 2CONFIDENTIAL

Romax Technology

• Gearbox and drivetrain specialists

• Established in 1989

• Approx. 220 employees globally, 120

in UK, 12 offices worldwide

• Work in a range of industries

o Wind energy

o Automotive, heavy industry,

marine, aerospace

© Copyright 2015Slide 3CONFIDENTIAL

Romax Technology

InSight health management solutions, predictive

maintenance software and services, independent engineering, due

diligence

Drivetrain and gearbox design, worldwide no. 1

independent wind turbine gearbox designer; 39 certified gearbox

designs to date

Drivetrain simulation, RomaxWIND virtual product

development environment; dynamic analysis and bearing

simulation

Engineering consultancy and fleet services, inspections,

analysis, certification support, failure investigation

© Copyright 2015Slide 4CONFIDENTIAL

InSight – enabling predictive maintenance

© Copyright 2015Slide 5CONFIDENTIAL

Engineering track record

• Romax has assessed the performance

and health of over 10 GW of wind

turbines across 4 continents

• Over 40% of the UK offshore fleet is

currently monitored by Romax

• Acciona, Bonus, Clipper, De Wind,

Gamesa, GE, Mitsubishi, NEG-Micon,

Nordex, Senvion, Siemens, Sinovel,

Suzlon, Vestas, etc.

© Copyright 2015Slide 6CONFIDENTIAL

Contents

• Combining data sources in a single software platform to enable

predictive maintenance

• Maximising up-front data analysis to aid inspections and

maintenance

• Collecting consistent failure data through standardised

inspection routines and reporting

• Other examples of usage of reliability data

© Copyright 2015Slide 7CONFIDENTIAL

Combining data sources in a single software platform to

enable predictive maintenance

© Copyright 2015Slide 8CONFIDENTIAL

Fleet Monitor software

• Hardware-independent wind turbine monitoring solution

© Copyright 2015Slide 9CONFIDENTIAL

CMS (Bently Nevada,

Commtest, SMP, etc.)

Wind farm 1

(e.g. Siemens, Vestas, etc.)

Romax server

‘Hardware independent’ condition monitoring

Romax monitoring

service

Fleet MonitorTM

software

Wind farm 2 (e.g.

GE, Gamesa, Clipper, etc.)

Database or

site server

Database or

site server

CMS (Gram & Juhl

TCM, B&K Vibro, etc.)

© Copyright 2015Slide 10CONFIDENTIAL

Assessing machinery health using vibration, inspection

and oil analysis

Increasing

vibration

trend triggers

inspectionHigh Fe content

in oil analysis

report

Inspection

report logged in

Fleet Monitor

© Copyright 2015Slide 11CONFIDENTIAL

Maximising up-front data analysis to aid inspections and

maintenance

© Copyright 2015Slide 12CONFIDENTIAL

Up-front data analysis

Determine likely targets

before inspections:

• Detailed SCADA and CMS

analysis

• Detailed review of

previous failure types and

timescales

• Issues often fixed with

gearbox modifications –

which are fitted?

© Copyright 2015Slide 13CONFIDENTIAL

‘Punch list’ for inspections and maintenance

© Copyright 2015Slide 14CONFIDENTIAL

Collecting consistent failure data through standardised

inspection routines and reporting

© Copyright 2015Slide 15CONFIDENTIAL

Collecting consistent failure dataStandardised inspection routines and reporting

At what point has a

component ‘failed’?

• Consistent, objective criteria

• Consistently reported

• Romax have developed an

app for phones / tablets

• Directs and simplifies

inspections

© Copyright 2015Slide 16CONFIDENTIAL

Collecting consistent failure dataStandardised inspection routines and reporting

• Detailed failure data helps

direct inspections

o E.g. if planetary bearings are

prone to cracking, inspect more

of each race

o Spend more time where

necessary

• Results immediately sent back

to Romax

o Serial issues can quickly be

identified

© Copyright 2015Slide 17CONFIDENTIAL

Other examples of usage of reliability data

© Copyright 2015Slide 18CONFIDENTIAL

Failure data example – main bearing failure

• CMS has detected a bearing issue – do I need to replace it? And when?

• Micropitting is often the first step in the failure of the bearing

• The debris generated leads to macropitting and a run-away surface fatigue condition

• Deterioration can be slowed, e.g. by grease flushing

© Copyright 2015Slide 19CONFIDENTIAL

Failure data example – main bearing failure

• Typical main bearing failure modes detected by CMS:

Severe outer race macropitting and cracking

Roller macropitting

Severe roller damage Inner race macropitting

© Copyright 2015Slide 20CONFIDENTIAL

Failure data example – main bearing failure

• Typical main bearing fault development over a long time period:

First Romax Alarm

8.5 months

Bearing

Replaced

Main

Beari

ng

Healt

h I

nd

ex

Date

• Recording the damage

level over time enables

statistical estimates of

remaining life

© Copyright 2015Slide 21CONFIDENTIAL

Failure data example – main bearing failure

• Time from fault detection by CMS to main

bearing failure ranges from ~2 months to

~2 years

• P50 time to failure for this particular

bearing type and failure mode is ~1 year

from fault detection

• Correlation of failure data with CMS data

improves maintenance planning – can

reduce the cost of major replacements!

© Copyright 2015Slide 22CONFIDENTIAL

Failure data example - due diligence

• Turbine technology review

o Reduce uncertainty in availability,

power production, failure rates and

O&M cost forecasts

o Turbine historical performance –

benchmarking against global portfolio

o O&M costs and mitigation strategies

o Reliability forecasts, Weibull analysis

o Review of operational agreements,

warranty risks

© Copyright 2015Slide 23CONFIDENTIAL

Failure data example - due diligence

• Site specific/turbine specific

O&M cost forecasts

• Analysis of cost scenarios –

P90, P50, O&M service

providers, equipment

upgrades, etc.

• Financial model review

• Analysis of power production,

availability and downtime

• Independent Engineering

support for contract

negotiations

© Copyright 2015Slide 24CONFIDENTIAL

Asset life extension

• Life extension for 20+ years

• Evaluating asset’s value

approaching the end of useful life

• Operational expenditures vs. power

generation scenarios

• Life extension strategy

• ‘Repower’ decision support

(expected revenue, operational

statistics)

Loads• Designed/predicted loads

• Measured loads

Simulation• Tuned models to predict

asset’s useful life

Cost impact

calculation

• O&M cost

forecast

• Revenue

forecast

© Copyright 2015Slide 25CONFIDENTIAL

Summary

• Romax is an ISP to turbine manufacturers, wind farm owners, operators

and financial sector

• Good reliability data is essential to reduce CoE through:

oMore robust design

oReduced cost of Operations and Maintenance through predictive methodologies

oBetter service contracts

oReduced insurance premiums

oLife extension