Postgraduate Diploma in Detection/Diagnosis and FDIR
Online Postgraduate Diploma of 800 hours in Detection/Diagnosis and FDIR. 8 modules covering IEC 61508, ISO 26262 and MATLAB/Simulink. Dedicated tutor and enrolment open.
Postgraduate Diploma in Detection/Diagnosis and FDIR — studying from Ireland
Ireland's manufacturing and technology sectors create strong demand for robotics, automation and control engineering, particularly in pharmaceuticals, medical devices, food processing and electronics. Research centres and universities contribute work in autonomous systems, sensing and control theory, with links to industry through national research programmes. Engineers in this area design, integrate and commission robotic cells, programmable logic controllers and industrial automation systems. Safety requirements for machinery and robotic systems are overseen by national safety authorities and European machinery standards.
Fees for Ireland: €1,490 (Euro), with instalments and employer sponsorship available.
Relevant bodies in Ireland
Typical roles
Questions from Ireland
Which Irish bodies relate to robotics and control engineering, and is this qualification recognised?
Robotics and control engineers in Ireland commonly pursue membership through Engineers Ireland, and the Science Foundation Ireland-funded research ecosystem supports the field. SEIUM's qualifications are private and not accredited by any national body, so recognition is decided by employers or the relevant body rather than conferred by the programme.
How do Irish employers in automation and robotics view private online training?
Employers in Ireland's technology and manufacturing automation sectors often value demonstrable project work and practical skills. A private online qualification can support your application, including through the final project, but its weight is at each employer's discretion. No particular role or career outcome is guaranteed.
Is the programme workable alongside a job, and what language is it taught in?
The programme is taught entirely in English and delivered 100% online, so you can study from anywhere in Ireland or abroad. Durations are 300, 800 or 1,900 hours depending on the course. Fees can be paid in instalments, employer sponsorship is possible, and an assigned technical tutor supports you throughout.
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
Classify fault types and analyse redundant architectures.
Design model-based residual generators.
Apply data-driven techniques for fault detection.
Isolate and estimate faults using signatures and observer banks.
Implement fault-tolerant control and reconfiguration strategies.
Estimate remaining useful life using PHM techniques.
Verify FDIR systems through fault injection and HIL testing.
Who it's for
- Diagnostics and monitoring engineer looking to specialise in Detection/Diagnosis and FDIR.
- Functional safety engineer looking to specialise in Detection/Diagnosis and FDIR.
- Reliability engineer looking to specialise in Detection/Diagnosis and FDIR.
- Predictive maintenance specialist looking to specialise in Detection/Diagnosis and FDIR.
- Space systems engineer looking to specialise in Detection/Diagnosis and FDIR.
- Researcher in fault-tolerant control looking to specialise in Detection/Diagnosis and FDIR.
- Graduates in engineering or sciences seeking to enter the aerospace sector.
What you'll work with
- IEC 61508
- ISO 26262
- ISO 13374-1
- IEC 60812
- IEC 61025
- ECSS-E-ST-70-11C
- ISO 13849-1
8 modules · 800 h
1.1Terminology: fault, error and failure1.2Classification of sensor and actuator faults1.3Abrupt, incipient and intermittent faults1.4Redundant hardware architectures1.5Availability and reliability1.6Fault trees and block diagrams1.7FDIR concept in critical systems1.8Levels of autonomy in the face of faults1.9Safety and availability requirements1.10Practical: fault tree of an actuation system
2.1Residual generation2.2Luenberger observers for diagnosis2.3Parity equations2.4Kalman filter and innovation test2.5Parameter estimation for diagnosis2.6Robustness and decoupling from disturbances2.7Adaptive decision thresholds2.8Sensitivity to small faults2.9Diagnosis with hybrid system models2.10Laboratory: residuals with an observer in Simulink
3.1Principal component analysis and T²3.2Q statistic and SPE3.3Detection with autoencoders3.4Time series models3.5Spectral analysis of vibrations3.6Supervised fault classifiers3.7Labelling fault data3.8Detection metrics and false alarms3.9Feature selection for diagnosis3.10Workshop: fault detection with PCA on process data
4.1Fault signature matrices4.2Design of structured residuals4.3Observer banks4.4Knowledge-based diagnosis4.5Bayesian diagnostic networks4.6Case-based reasoning4.7Multiple fault diagnosis4.8Estimation of fault magnitude4.9Data-based isolation classifiers4.10Practical: isolation with an observer bank
5.1Passive fault-tolerant control5.2Active fault-tolerant control5.3Reconfiguration of control laws5.4Control allocation with redundant actuators5.5Virtual sensors and estimation5.6Degraded operating modes5.7Management of mode transitions5.8Recovery in space systems5.9Reconfiguration of redundant sensors5.10Laboratory: control reallocation after an actuator failure
6.1Prognostics and Health Management (PHM)6.2Remaining useful life estimation6.3Degradation models6.4Particle filters for prognosis6.5Condition-based maintenance6.6Integration of diagnosis and maintenance6.7Health indicators6.8OSA-CBM maintenance architectures6.9Uncertainty in life prediction6.10Case study: remaining life of a bearing
7.1Fault injection in simulation7.2Hardware-in-the-Loop testing with injected faults7.3FMECA of the system7.4Functional safety requirements7.5Diagnostic coverage7.6Validation with field data7.7Certification in critical sectors7.8Documentation of the FDIR architecture7.9Metrics for false alarms and late detection7.10Case study: fault injection campaign
8.1System analysis and failure modes8.2Detection design8.3Isolation design8.4Recovery strategy8.5Implementation in simulation8.6Fault injection campaign8.7Coverage assessment8.8Analysis of results8.9Report and presentation8.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and a dedicated technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB/Simulink, MATLAB Predictive Maintenance Toolbox, Python with scikit-learn, dSPACE, Isograph Reliability Workbench, in free, academic or evaluation versions. Tests are studied using real procedures for fault detection in chemical process sensors, fault-tolerant control in unmanned aircraft, and bearing remaining useful life prognostics. Assessment is continuous across each module, plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Classify fault types and analyse redundant architectures.
Design model-based residual generators.
Apply data-driven techniques for fault detection.
Isolate and estimate faults using signatures and observer banks.
Implement fault-tolerant control and reconfiguration strategies.
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 command of Spanish to follow technical standards documentation.
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, 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 MATLAB/Simulink, MATLAB Predictive Maintenance Toolbox, Python with scikit-learn, dSPACE, Isograph Reliability Workbench. Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.
A SEIUM Institute diploma upon passing the continuous assessment and the integrative 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 can be credited towards the advanced programme. Please check the credit transfer policy when you enrol.
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