Postgraduate Diploma in Predictive Maintenance and Health Index
Online 800-hour Postgraduate Diploma in Predictive Maintenance and Health Index. 8 modules with IEC 60599 (dissolved gas interpretation), IEEE C57.104 (dissolved gases in transformers) and Python (scikit-learn). Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Compare corrective, preventive and predictive maintenance strategies.
Diagnose transformers through gas analysis and electrical testing.
Assess the condition of switchgear and cables using diagnostic techniques.
Build an asset health index from condition data.
Design online monitoring systems for critical assets.
Apply predictive analytics models to estimate failures.
Turn predictive results into investment and maintenance decisions.
Who it's for
- Predictive maintenance engineer who wants to specialise in Predictive Maintenance and Health Index.
- Electrical asset management engineer who wants to specialise in Predictive Maintenance and Health Index.
- Transformer diagnostics specialist who wants to specialise in Predictive Maintenance and Health Index.
- Asset data scientist who wants to specialise in Predictive Maintenance and Health Index.
- Reliability manager who wants to specialise in Predictive Maintenance and Health Index.
- Condition monitoring technician who wants to specialise in Predictive Maintenance and Health Index.
- Engineering or science graduates seeking to enter electrical distribution.
What you'll work with
- IEC 60599 (dissolved gas interpretation)
- IEEE C57.104 (dissolved gases in transformers)
- ISO 55000 (asset management)
- IEC 60270 (partial discharge measurement)
- IEC 60422 (mineral oil supervision)
- ISO 17359 (condition monitoring of machines)
- ISO 13374 (processing of monitoring data)
8 modules · 800 h
1.1Corrective, preventive and predictive maintenance1.2Reliability-centred maintenance (RCM)1.3Failure mode analysis: FMEA and FMECA1.4IEC 60300-3-11 standard on RCM1.5MTBF, MTTR and availability indicators1.6P-F curve and inspection intervals1.7Condition-based maintenance1.8Maintenance costs1.9CMMS systems and work orders1.10Workshop: FMECA analysis of a power transformer
2.1Dissolved gas analysis according to IEC 605992.2Duval and Rogers methods and key gases2.3Oil analysis: moisture and dielectric strength2.4Furans and degree of polymerisation2.5Frequency response analysis (SFRA)2.6Tan delta and capacitance measurement2.7Partial discharges in transformers2.8Infrared thermography2.9Tap changer diagnostics2.10Practice: DGA interpretation with the Duval triangle
3.1Circuit breaker diagnostics: timing and resistance3.2SF6 monitoring and leakage3.3Partial discharges in GIS cells3.4VLF and tan delta cable testing3.5Partial discharges in cables according to IEC 602703.6Connection thermography3.7Surge arrester diagnostics3.8Substation battery monitoring3.9Ultrasound in switchgear3.10Case study: diagnosis of an MV cell with partial discharges
4.1Concept and objectives of the Health Index4.2Selection of condition indicators4.3Weighting and normalisation4.4CNAIM and CIGRE methodologies4.5Transformer health index4.6Cable and line health index4.7Effective age and remaining life4.8Validation with experts and failures4.9Dynamic index updating4.10Laboratory: Health Index calculation for a transformer fleet
5.1Sensors for network assets5.2Online DGA monitors5.3Optical fibre for winding temperature5.4Bushing monitoring5.5UHF partial discharge sensors5.6Communications and the IEC 61850 protocol5.7Edge computing in substations5.8Alarm management5.9Cost-benefit of monitoring5.10Practice: designing a transformer monitoring system
6.1Preparation of condition time series6.2Anomaly detection6.3Degradation regression models6.4Remaining useful life (RUL) estimation6.5Supervised machine learning6.6Survival models6.7Model explainability6.8Validation and performance metrics6.9Production deployment and MLOps6.10Laboratory: RUL model with Python and scikit-learn
7.1Prioritisation of interventions7.2Risk-based maintenance planning7.3CMMS integration7.4Spare parts management and logistics7.5Optimisation of field resources7.6Programme effectiveness indicators7.7Success stories in utilities7.8Change management in maintenance7.9Return on investment7.10Case study: maintenance plan based on the Health Index
8.1Asset selection and scope8.2Initial FMECA analysis8.3Definition of condition variables8.4Building the Health Index8.5Predictive degradation model8.6Prioritised maintenance plan8.7Economic evaluation of the programme8.8Implementation plan8.9Report and presentation8.10Final review with the tutor
How you'll learn
Training 100 % online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (scikit-learn), MATLAB, Power BI, IBM Maximo, OSIsoft PI System, in free, academic or evaluation versions. Tests are studied using real procedures for dissolved gas analysis in oil, partial discharge measurement and thermography of switchgear. Assessment is continuous, module by module, plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Compare corrective, preventive and predictive maintenance strategies.
Diagnose transformers through gas analysis and electrical testing.
Assess the condition of switchgear and cables using diagnostic techniques.
Build an asset health index from condition data.
Design online monitoring systems for critical assets.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory reading.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
You will work with Python (scikit-learn), MATLAB, Power BI, IBM Maximo, OSIsoft PI System. Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.
An own diploma from SEIUM upon passing the 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 recognised in the higher programme. Check the recognition policy when you enrol.
Related programmes
Postgraduate Diploma in Operation and Stability of Isolated Systems
Online 800-hour Postgraduate Diploma in Operation and Stability of Isolated Systems. 8 modules covering Real Decreto 738/2015 (generation in non-peninsular territories), Reglamento (UE) 2016/631 (RfG grid…
Postgraduate Diploma in DER Orchestration and Network Flexibility
Online 800-hour Postgraduate Diploma in DER Orchestration and Network Flexibility. 8 modules with IEEE 2030.5 (application protocol for smart energy), IEC 61850-7-420 (information models for DER)…
Postgraduate Diploma in Relay Coordination and Characteristic Curves
Online Postgraduate Diploma of 800 h in Relay Coordination and Characteristic Curves. 8 modules covering IEC 60255-151 (overcurrent protection), IEEE C37.112 (inverse-time curves) and ETAP. Assigned…
More in Energy and Networks
All Energy and Networks programmes → · How to apply · Fees & financing · Scholarships