Predictive Maintenance Course for Rolling Stock
Online course of 300 hours in predictive maintenance of rolling stock: 6 modules covering rolling stock maintenance, condition monitoring, reliability and degradation models, machine learning for prediction and organisational implementation, with an assigned technical tutor.
Predictive Maintenance Course for Rolling Stock — studying from Malta
Malta's civil engineering sector is active, driven by ongoing construction, infrastructure upgrades, coastal works and urban regeneration projects across the islands. Demand for civil engineers is closely linked to public works, land development and the modernisation of transport networks. Smart city initiatives, including digital mapping, traffic management and sustainable urban planning, are increasingly relevant. Engineers typically find employment with contractors, consultancies, government departments and utility providers managing infrastructure in a densely populated environment.
Fees for Malta: €743 (Euro), with instalments and employer sponsorship available.
Relevant bodies in Malta
Typical roles
Questions from Malta
Which Maltese bodies regulate civil engineering and related professional practice?
The Chamber of Engineers (KSU) regulates the use of the title 'engineer' in Malta under the Engineering Profession Act. Planning and development matters fall under the Planning Authority, and public works and transport infrastructure involve government agencies including Transport Malta. A SEIUM qualification does not itself grant a regulated title; recognition is decided by employers or the relevant body.
What employers in Malta would value civil, rail or smart city engineering skills?
Malta's construction, infrastructure, consultancy and public sector firms are the main employers, along with transport and utilities bodies. Smart city and digital infrastructure work is growing in some areas. Employers typically look for chartered-level experience and licensing, so a private qualification should be seen as supporting your professional development rather than a substitute for those requirements.
How can I study this while working on site, and what support is there?
The programme is delivered entirely online in English, so you can study from anywhere in Malta without a student visa. Each student has an assigned technical tutor, and the course ends with a final project. Time commitment depends on the programme length, from 300 to 1,900 hours. Ask about instalment payments and employer sponsorship to help manage costs.
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
Understand the maintenance strategies applicable to rolling stock.
Apply condition monitoring techniques to critical components.
Model the reliability and degradation of railway components.
Develop machine learning models to predict failures.
Integrate predictive maintenance into depot management and the CMMS.
Assess the economic impact of predictive maintenance.
Design a predictive maintenance system for a real fleet.
Who it's for
- Rolling stock maintenance engineers
- RAMS reliability engineers
- Maintenance data scientists
- Railway depot managers
- Fleet engineering managers
- Condition monitoring technicians
- Engineering or science graduates looking to join railway operators
What you'll work with
- EN 50126 (railway applications – specification and demonstration of RAMS)
- Implementing Regulation (EU) 2019/779 (entities in charge of maintenance)
- ISO 17359 (condition monitoring and diagnostics of machines)
- EN 13306 (maintenance terminology)
- EN 15341 (maintenance key performance indicators)
- ISO 13374 (data processing for condition monitoring)
- EN 60812 (failure mode and effects analysis (FMEA))
- ISO 55001 (asset management)
- MATLAB Predictive Maintenance Toolbox
- Python with scikit-learn and TensorFlow
- IBM Maximo
- SAP PM
- ReliaSoft Weibull++
6 modules
1.1Corrective, preventive and predictive strategies1.2Maintenance plans by mileage and time1.3Critical components: bogies, wheels, brakes and traction1.4Maintenance depots and levels of intervention1.5Entity in Charge of Maintenance (ECM)1.6RAMS indicators and fleet availability1.7Condition-based maintenance (CBM)1.8Life cycle cost (LCC)1.9Spare parts and warehouse management1.10Case study: failure analysis of a commuter fleet
2.1Vibration analysis of bearings2.2Thermography of traction equipment2.3Oil and wear analysis2.4Wheel profile and diameter measurement2.5Trackside detectors: wayside monitoring2.6On-board diagnostics and TCN buses2.7Monitoring of doors and HVAC2.8Ultrasonic testing of axles and wheels2.9Sampling frequencies and data acquisition2.10Lab: spectral analysis of a bearing
3.1Weibull and exponential distributions3.2Failure mode analysis (FMECA)3.3Fault trees and reliability block diagrams3.4Degradation models and remaining useful life3.5Stochastic processes and Markov chains3.6Survival analysis3.7Censored data and how to handle it3.8Reliability-centred maintenance (RCM)3.9Optimising inspection intervals3.10Practical exercise: calculating the remaining life of a wheel profile
4.1Preparing sensor and failure data4.2Feature engineering on signals4.3Classification of failure states4.4Regression for estimating useful life4.5Recurrent neural networks and LSTM4.6Unsupervised anomaly detection4.7Validation and metrics for predictive models4.8Deploying models in production4.9Explainability and interpretation of results4.10Workshop: predictive model for door failures
5.1Integration with the CMMS5.2Automatic generation of work orders5.3Depot planning based on predictions5.4Change management in maintenance teams5.5Availability-based maintenance contracts5.6Cybersecurity of on-board data5.7ECM Regulation and traceability5.8Economic assessment and savings5.9Implementation cases at European operators5.10Case study: business case for predictive maintenance
6.1Selecting the subsystem and the fleet6.2Analysis of critical failure modes6.3Defining the instrumentation6.4Data collection and preparation6.5Developing the predictive model6.6Decision rules and CMMS integration6.7Assessment of savings and availability6.8Deployment plan6.9Report and presentation6.10Final project: final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB Predictive Maintenance Toolbox, Python with scikit-learn and TensorFlow, IBM Maximo, SAP PM, ReliaSoft Weibull++, in free, academic or evaluation versions. Real procedures are studied for vibration analysis of bogies and bearings, modelling the remaining useful life of components and economic assessment of maintenance strategies. Assessment is continuous by module, plus the final integrating project.
Standards covered: EN 50126; Implementing Regulation (EU) 2019/779; ISO 17359; EN 13306; EN 15341; ISO 13374; EN 60812; ISO 55001.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- No prior qualification is required.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
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 totals 300 hours over 3 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with MATLAB Predictive Maintenance Toolbox, Python with scikit-learn and TensorFlow, IBM Maximo, SAP PM and ReliaSoft Weibull++, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute certificate, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
No prior qualification is required; you need an internet connection, a computer capable of running the programme software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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