Diploma in Reliability Metrics and Controlled Trials
Online postgraduate diploma of 800 hours in dependability metrics and controlled testing: 8 modules covering reliability and its measures, statistical life analysis, system reliability, design of controlled tests, accelerated testing, reliability growth, and dependability of AI systems, with an assigned technical tutor.
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
Calculate the main reliability and availability metrics.
Analyse censored life data using statistical methods.
Model system reliability with block diagrams, fault trees and Markov models.
Design controlled and demonstration tests with statistical rigour.
Plan accelerated tests and extrapolate to use conditions.
Manage reliability growth programmes with FRACAS.
Assess the dependability of systems that integrate AI components.
Who it's for
- Reliability engineers.
- Test engineers who plan and analyse life and demonstration tests.
- Quality engineers.
- Field data analysts.
- Predictive maintenance leads.
- RAMS engineers.
- Engineering or science graduates aiming to enter the electronics sector.
What you'll work with
- IEC 61703:2016 (mathematical expressions for reliability, availability and maintainability)
- IEC 61649:2008 (Weibull analysis)
- IEC 61124 (reliability testing, compliance tests for constant failure rate)
- IEC 61164:2004 (reliability growth, statistical test and estimation methods)
- IEC 60812:2018 (failure mode and effects analysis, FMEA)
- IEC 61025:2006 (fault tree analysis)
- IEC 61709:2017 (electronic components failure rates)
- MIL-STD-810H (environmental engineering and laboratory tests)
- ReliaSoft Weibull++
- Minitab
- R (survival package)
- Python reliability
8 modules
1.1Reliability function and failure rate1.2MTTF, MTBF and MTTR1.3Inherent and operational availability1.4The bathtub curve1.5Exponential, Weibull and lognormal distributions1.6Random and systematic failures1.7IEC 60050-192 definitions1.8IEC 61703 metrics1.9Software and AI reliability1.10Workshop: availability calculation for repairable equipment
2.1Complete, censored and truncated data2.2The Kaplan-Meier estimator2.3Weibull probability plots2.4Maximum likelihood parameter estimation2.5Confidence intervals and bounds2.6Weibull analysis according to IEC 616492.7Comparing populations2.8Warranty analysis2.9Competing risks models2.10Lab: Weibull analysis with censored data
3.1Reliability block diagrams3.2Fault trees according to IEC 610253.3FMEA according to IEC 608123.4Markov models for repairable systems3.5Redundancy and common cause failures3.6Prediction with IEC 61709 and MIL-HDBK-217F3.7Allocation of reliability targets3.8Monte Carlo availability simulation3.9Component importance3.10Practical exercise: fault tree of a pumping system
4.1Statistical test planning4.2Factorial design and response surface4.3Randomisation, blocking and replication4.4Sample size and power4.5Reliability demonstration tests4.6Compliance tests according to IEC 611244.7Zero-failure (success-run) plans4.8Analysis of variance4.9Analysing results in Minitab4.10Practical exercise: MTBF demonstration plan
5.1Arrhenius and Eyring acceleration models5.2Inverse power law and Coffin-Manson5.3ALT tests with multiple stress levels5.4HALT and HASS5.5Accelerated degradation testing5.6Environmental testing according to IEC 600685.7MIL-STD-810H profiles5.8Extrapolation to use conditions5.9Risks of non-representative failure modes5.10Lab: Arrhenius model on ageing data
6.1Duane and Crow-AMSAA models6.2Growth testing according to IEC 611646.3Managing corrective actions with FRACAS6.4Tracking product maturity6.5Reliability projection6.6Field data and feedback6.7In-service reliability indicators6.8Condition-based maintenance6.9Root cause analysis6.10Case study: growth programme for an electronic unit
7.1Performance metrics with confidence intervals7.2A/B and controlled tests of models7.3Failure rates of AI components7.4Degradation due to data drift7.5Robustness and stress testing7.6Availability of inference services7.7Service level objectives (SLO)7.8Statistical comparison between versions7.9Reliability reports for customers7.10Case study: controlled evaluation of a detection model
8.1Selection of the product or system8.2Definition of requirements and metrics8.3System reliability modelling8.4Design of the test plan8.5Statistical analysis of results8.6Reliability projection in use8.7Improvement plan and corrective actions8.8Conclusions and residual risks8.9Report and presentation8.10Final 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 it fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ReliaSoft Weibull++, Minitab, R (survival package) and Python reliability, in free, academic or evaluation versions. Testing is studied on real procedures: accelerated life tests in a climatic chamber, reliability demonstration tests with limited samples and controlled evaluation of AI model versions. Assessment is continuous by module, plus the final capstone project.
Standards covered: IEC 61703:2016, IEC 61649:2008, IEC 61124, IEC 61164:2004, IEC 60812:2018, IEC 61025:2006, IEC 61709:2017, MIL-STD-810H.
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 ReliaSoft Weibull++, Minitab, R (survival package) and Python reliability, 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 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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