Diploma in PHM Applied to Land Systems
Online postgraduate diploma of 800 hours in PHM applied to land systems: 8 modules covering PHM fundamentals under IEEE 1856-2017 and ISO 13374, on-board sensing and acquisition, health indicators, diagnostics, prognostics and remaining useful life, logistics integration and system verification, with an assigned technical tutor.
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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 fundamentals and architecture of PHM in land systems.
Design on-board sensing and data acquisition strategies.
Extract health indicators from vehicle data.
Develop diagnostic and prognostic models.
Estimate remaining useful life with uncertainty quantification.
Integrate PHM into logistics support and fleet management.
Assess the performance and value of a PHM system.
Who it's for
- PHM engineers.
- Maintenance data scientists.
- Vetronics engineers.
- Reliability engineers.
- Integrated logistics support managers.
- On-board diagnostics engineers.
- Engineering or science graduates seeking to enter the land defence sector.
What you'll work with
- IEEE 1856-2017 (prognostics and health management of electronic systems)
- ISO 13374 (condition monitoring data processing)
- ISO 13381-1 (prognostics)
- SAE JA6268 (design and life-cycle management for integrated vehicle health management readiness)
- SAE J1939 (heavy-duty vehicle networks)
- MIL-STD-1553B (multiplexed data bus)
- ISO 55000 (asset management)
- MATLAB Predictive Maintenance Toolbox
- Python (PyTorch)
- Vector CANalyzer
- LabVIEW
8 modules
1.1The concept of prognostics and health management1.2Architecture according to ISO 133741.3IEEE 1856 and its framework1.4Diagnostics versus prognostics1.5Benefits for availability1.6PHM in vehicle programmes1.7Design for health readiness1.8Challenges in land vehicles1.9PHM maturity1.10Case study: analysis of a PHM programme
2.1On-board sensors2.2CAN bus and SAE J19392.3MIL-STD-1553B in vehicles2.4Data loggers2.5Sampling rate and storage2.6Edge processing2.7Data quality2.8Sensor power management2.9Environmental ruggedness2.10Lab: CAN bus data acquisition
3.1Time-domain features3.2Spectral features3.3Time-frequency analysis3.4Feature selection3.5Normalisation by operating conditions3.6Engine indicators3.7Transmission indicators3.8Battery indicators3.9Hydraulic system indicators3.10Practical exercise: extracting health indicators
4.1Anomaly detection4.2Fault classification4.3Physics-based models4.4Data-driven models4.5Hybrid models4.6Diagnostic trees4.7Diagnostics of electrical systems4.8Validation of diagnostics4.9Explainability4.10Lab: fault classification with machine learning
5.1Degradation models5.2Particle filters for prognostics5.3Recurrent neural networks5.4Similarity models5.5Uncertainty quantification5.6Prognostic metrics5.7Battery prognostics5.8Prognostics of mechanical components5.9Updating with new data5.10Practical exercise: estimating battery useful life
6.1PHM and integrated logistics support6.2Condition-based maintenance6.3Spare parts management6.4Mission planning6.5Integration with logistics information systems6.6Fleet management6.7Availability-based contracts6.8Data interoperability6.9Cybersecurity6.10Case study: integrating PHM into maintenance planning
7.1Algorithm verification7.2Seeded fault testing7.3Fleet validation7.4Cost-benefit analysis7.5Success indicators7.6Certification of PHM software7.7Change management7.8Lessons learned7.9Future trends7.10Workshop: value analysis of a PHM system
8.1Subsystem selection8.2Failure mode analysis8.3Sensing strategy8.4Health indicators8.5Diagnostic model8.6Prognostic model8.7Logistics integration8.8System evaluation8.9Report and presentation8.10Final project: final review with your tutor
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: you progress at your own pace within each intake, so the programme can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB Predictive Maintenance Toolbox, Python (PyTorch), Vector CANalyzer and LabVIEW, in free, academic or evaluation versions. Practical work is based on real procedures: extraction of health indicators from CAN bus data, estimation of battery remaining useful life and design of an on-board PHM architecture. Assessment is continuous by module, plus the final project.
Standards covered: IEEE 1856-2017, ISO 13374, ISO 13381-1, SAE JA6268, SAE J1939, MIL-STD-1553B, ISO 55000.
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
- Prior technical training or professional experience in the sector. No university degree 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 800 hours over 6–8 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 (PyTorch), Vector CANalyzer and LabVIEW, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, 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.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the 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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