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Course in Reliability and Predictive Maintenance in Wind Energy

Online 300 h course in reliability and predictive maintenance in wind energy. 6 modules covering IEC 61400-25 (communications for monitoring and control), IEC 61400-26-1 (wind turbine availability) and Python (scikit-learn). Assigned tutor and enrolment open.

Duration300 h
ModeOnline
Start datesSet by the faculty
AwardSEIUM Institute certificate
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Learning outcomes

What you will be able to do

01

Identify the most critical failure modes of wind turbines.

02

Apply reliability analysis techniques such as Weibull, FMECA and fault trees.

03

Interpret vibration and oil signals and other condition monitoring techniques.

04

Develop predictive models with SCADA data to anticipate failures.

05

Plan maintenance using risk and cost criteria.

06

Measure the availability and performance of maintenance strategies.

07

Design a predictive maintenance programme for a wind farm.

Profile

Who it's for

  • Wind reliability engineer looking to specialise in Reliability and Predictive Maintenance in Wind Energy.
  • Condition monitoring analyst looking to specialise in Reliability and Predictive Maintenance in Wind Energy.
  • Wind turbine maintenance technician looking to specialise in Reliability and Predictive Maintenance in Wind Energy.
  • Renewables data scientist looking to specialise in Reliability and Predictive Maintenance in Wind Energy.
  • Wind O&M manager looking to specialise in Reliability and Predictive Maintenance in Wind Energy.
  • Wind asset manager looking to specialise in Reliability and Predictive Maintenance in Wind Energy.
  • Engineering or science graduates looking to enter the wind energy sector.
Standards & tools

What you'll work with

  • IEC 61400-25 (communications for monitoring and control)
  • IEC 61400-26-1 (wind turbine availability)
  • ISO 10816-21 (vibration assessment of wind turbines)
  • ISO 17359 (condition monitoring and diagnostics)
  • IEC 60812 (failure modes and effects analysis)
  • IEC 61025 (fault tree analysis)
  • EN 13306 (maintenance terminology)
  • ISO 55001 (asset management)
Syllabus

6 modules · 300 h

  1. 1.1Critical wind turbine components
  2. 1.2Gearbox failures
  3. 1.3Main bearing failures
  4. 1.4Generator failures
  5. 1.5Blade damage
  6. 1.6Converter failures
  7. 1.7Failure rates and downtime
  8. 1.8Reliability databases
  9. 1.9Cost of failures
  10. 1.10Practical case: Pareto analysis of wind farm downtime
  1. 2.1Weibull distribution
  2. 2.2MTBF and MTTR
  3. 2.3FMECA analysis of the drivetrain
  4. 2.4Fault tree analysis
  5. 2.5Reliability-centred maintenance
  6. 2.6Risk-based maintenance
  7. 2.7Root cause analysis
  8. 2.8Service life models
  9. 2.9Life extension
  10. 2.10Laboratory: Weibull fitting with failure data
  1. 3.1Vibration analysis
  2. 3.2Spectra and envelopes
  3. 3.3Oil analysis
  4. 3.4Thermography of electrical components
  5. 3.5Ultrasonic inspection
  6. 3.6Acoustic emission techniques
  7. 3.7Blade monitoring
  8. 3.8Drone inspection
  9. 3.9Fibre optic sensors
  10. 3.10Practice: bearing diagnosis by spectrum
  1. 4.1Ten-minute SCADA data
  2. 4.2Normal behaviour models
  3. 4.3Anomaly detection
  4. 4.4Neural networks for temperatures
  5. 4.5Remaining useful life
  6. 4.6Power curve deviations
  7. 4.7Wind turbine digital twins
  8. 4.8CMS and SCADA integration
  9. 4.9False positive management
  10. 4.10Workshop: gearbox normal behaviour model
  1. 5.1Maintenance strategies
  2. 5.2Planning major corrective works
  3. 5.3Cranes and logistics
  4. 5.4Spare parts management
  5. 5.5Service contracts
  6. 5.6Availability KPIs
  7. 5.7CMMS systems
  8. 5.8Work at height
  9. 5.9Cost optimisation
  10. 5.10Practical case: predictive plan for 30 wind turbines
  1. 6.1Study wind farm
  2. 6.2Historical failure analysis
  3. 6.3Selection of critical components
  4. 6.4Monitoring strategy
  5. 6.5Development of the predictive model
  6. 6.6Integration into management
  7. 6.7Cost-benefit analysis of the programme
  8. 6.8Conclusions and recommendations
  9. 6.9Report and presentation
  10. 6.10Final review with the tutor
Methodology, software & labs

How you'll learn

Training is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which allows it to be combined with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (scikit-learn), MATLAB Predictive Maintenance Toolbox, Power Factors Greenbyte, IBM Maximo, in free, academic or evaluation versions. Tests are studied using real vibration analysis procedures for drivetrains, normal behaviour models with SCADA data, and fitting of failure distributions. Assessment is continuous per module plus the final integrating project.

Accreditable laboratories(EN ISO/IEC 17025) with rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-oriented Master's Thesis:safety case, test plan, compliance dossier and operating limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, OT cybersecurity, DIH and compliance as pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Study wind farm

Identify the most critical failure modes of wind turbines.

Historical failure analysis

Apply reliability analysis techniques such as Weibull, FMECA and fault trees.

Selection of critical components

Interpret vibration and oil signals and other condition monitoring techniques.

Monitoring strategy

Develop predictive models with SCADA data to anticipate failures.

Development of the predictive model

Plan maintenance using risk and cost criteria.

Career opportunities

Where this takes you

Wind reliability engineerCondition monitoring analystWind turbine maintenance technicianData scientist in renewablesWind O&M managerWind asset manager
Admissions & scholarships

Requirements

  • No prior degree required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient level of Spanish to follow the reading of technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme is 300 hours in total, spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.

Work is carried out with Python (scikit-learn), MATLAB Predictive Maintenance Toolbox, Power Factors Greenbyte, IBM Maximo. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An own SEIUM diploma upon passing continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.

Yes. Modules passed in a course or postgraduate diploma in the same area are credited towards the advanced programme. Check the credit transfer policy when enrolling.

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