Master’s in Predictive Maintenance
Online master's programme of 1,900 hours in predictive maintenance — vibration and acoustic analysis, models and deployment in the plant. 12 modules covering maintenance strategies, vibration analysis, complementary predictive techniques, sensing and data acquisition, signal processing, machine learning for diagnosis, remaining useful life prognosis, platforms, sector applications, implementation and reliability, with ISO 17359, ISO 20816-3 and ISO 13374 and an assigned technical tutor.
Master’s in Predictive Maintenance — studying from Singapore
Singapore is one of Asia's leading electronics manufacturing centres, with semiconductor fabrication, back-end assembly and test, and precision electronics concentrated in areas such as Tampines and Jurong. The sector also includes embedded systems for industrial and automotive use and a strong telecommunications base led by the Infocomm Media Development Authority. Major employers include global semiconductor firms and electronics manufacturers. Engineers work on hardware design, firmware, communications systems and test engineering.
Fees for Singapore: S$8,450 (Singapore dollar), with instalments and employer sponsorship available.
Relevant bodies in Singapore
Typical roles
Questions from Singapore
How are electronics and telecom engineers recognised in Singapore, and does SEIUM count?
Telecom and electronics engineering is regulated by the Infocomm Media Development Authority (IMDA), and engineers may register with the Professional Engineers Board (PEB). SEIUM's qualifications are private, not state degrees, and not accredited by any national body. Whether they are recognised is decided by employers or the relevant body, so confirm this before enrolling.
Which Singapore employers hire embedded systems and telecom engineers?
Singapore has demand from telecom operators, semiconductor and electronics manufacturers, defence and aerospace firms, and industrial automation companies. Employers generally assess hands-on skills in firmware, hardware design and testing. Your final project can evidence embedded or telecom competence, but its value is for each employer to judge.
Can I follow this from Singapore while working, and does it need a visa?
Yes, the programmes are 100% online and taught in English, so no student visa is needed to study from home in Singapore. Expect a heavy workload: 1,900 hours for a master's, 800 for a postgraduate diploma and 300 for a specialist course. Fees can be paid in instalments, and employer sponsorship is possible.
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
Select maintenance strategies according to asset criticality.
Diagnose faults through vibration analysis.
Apply complementary predictive techniques.
Design sensing and data acquisition systems.
Develop diagnostic models with machine learning.
Estimate the remaining useful life of equipment.
Implement cost-effective predictive maintenance programmes.
Who it's for
- Predictive maintenance engineers looking to deepen their expertise.
- Vibration analysts who want to broaden their diagnostic toolkit.
- Reliability engineers.
- Industrial data scientists moving into condition monitoring.
- Maintenance managers.
- Asset management engineers.
- Engineering or science graduates seeking to enter the process industry.
What you'll work with
- ISO 17359 (condition monitoring and diagnostics of machines — general guidelines)
- ISO 20816-3 (measurement and evaluation of machine vibration — industrial machines)
- ISO 13374 (condition monitoring data processing, communication and presentation)
- ISO 55001 (asset management systems — requirements)
- ISO 18436-2 (qualification and assessment of vibration analysis personnel)
- UNE-EN 13306 (maintenance terminology)
- ISO 13381-1 (machine prognostics — general guidelines)
- SAE JA1011 (evaluation criteria for RCM processes)
- Python with scikit-learn
- MATLAB Predictive Maintenance Toolbox
- SKF Enlight
- IBM Maximo
- Grafana
12 modules
1.1Corrective and preventive maintenance1.2Condition-based maintenance1.3Predictive and prescriptive maintenance1.4Reliability-centred maintenance (RCM)1.5P-F curve and inspection intervals1.6Asset criticality1.7Maintenance indicators1.8Asset management to ISO 550001.9Life-cycle costs1.10Case study: criticality matrix for a plant
2.1Mechanical vibration in rotating machinery2.2Accelerometers and proximity sensors2.3FFT spectral analysis2.4Unbalance and misalignment2.5Bearing faults2.6Gear faults2.7Looseness and resonances2.8Envelope analysis2.9Severity according to ISO 208162.10Lab: bearing diagnosis with FFT
3.1Infrared thermography of equipment3.2Oil analysis3.3Airborne ultrasound detection3.4Motor current analysis3.5Acoustic emission technique3.6Partial discharge measurement3.7Dissolved gas analysis3.8Visual inspection with drones3.9Combining techniques3.10Practical exercise: thermography of an electrical switchboard
4.1Wireless vibration sensors4.2Online acquisition systems4.3Sampling frequency and aliasing4.4Edge computing for condition monitoring4.5Integration through industrial protocols4.6Integration with SCADA4.7Data quality4.8Sensor installation4.9Cost of sensing4.10Lab: vibration acquisition system
5.1Digital signal filtering5.2Windows and spectral resolution5.3Joint time-frequency analysis5.4Wavelet transform in diagnosis5.5Cepstral analysis of gears5.6Demodulation of impact signals5.7Feature extraction5.8Order analysis5.9Noise treatment5.10Practical exercise: condition indicators in Python
6.1Preparing condition data6.2Fault classification6.3Anomaly detection6.4Convolutional neural networks6.5Unsupervised learning6.6Class imbalance6.7Model validation6.8Explainability of diagnoses6.9Transfer between machines6.10Lab: bearing fault classifier
7.1Health indicators7.2Degradation models7.3Remaining useful life (RUL) estimation7.4Physics-based models7.5Data-driven models7.6LSTM networks for prognosis7.7Prognostic uncertainty7.8Evaluation metrics7.9Decision-making with prognostics7.10Practical exercise: RUL with the C-MAPSS dataset
8.1Computerised maintenance management systems (CMMS)8.2Integration between CMMS and predictive systems8.3Cloud condition-monitoring platforms8.4Dashboards8.5Work order management8.6Digital twins of machines8.7Mobile applications for technicians8.8System interoperability8.9Platform selection8.10Lab: integrating alarms into a CMMS
9.1Process industry9.2Predictive maintenance in wind turbines9.3Rolling stock and railway track9.4Engines and systems in aviation9.5Power generation plants9.6Water infrastructure9.7Building services installations9.8Vehicle fleets9.9Particularities of each sector9.10Case study: predictive maintenance in wind turbines
10.1Implementation plan10.2Pilot programme design10.3Return on investment10.4Training technicians10.5Analyst certification to ISO 1843610.6Change management10.7Success indicators10.8Outsourcing the service10.9Continuous improvement of the programme10.10Workshop: business case for a predictive programme
11.1Root cause analysis11.2FMEA and FMECA11.3Weibull analysis11.4Fault trees11.5Lessons-learned register11.6Equipment redesign11.7Spare parts optimisation11.8Risk-based maintenance11.9Reliability indicators11.10Practical exercise: root cause analysis of a pump failure
12.1Asset selection12.2Criticality analysis12.3Sensing design12.4Data acquisition12.5Development of diagnostic models12.6Remaining useful life prognosis12.7Integration into maintenance management12.8Economic evaluation of the programme12.9Master's Thesis report12.10Master's Thesis: defence before a panel
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 you can combine the programme with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python with scikit-learn, MATLAB Predictive Maintenance Toolbox, SKF Enlight, IBM Maximo and Grafana, in free, academic or evaluation versions. Practical work is based on real procedures for vibration analysis of rotating machinery, thermography of installations and validation of remaining useful life models. Assessment is continuous for each module, plus the final Master's Thesis.
Standards covered: ISO 17359, ISO 20816-3, ISO 13374, ISO 55001, ISO 18436-2, UNE-EN 13306, ISO 13381-1 and SAE JA1011.
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
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- 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 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Python with scikit-learn, MATLAB Predictive Maintenance Toolbox, SKF Enlight, IBM Maximo and Grafana, 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 Master's Thesis. 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 in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), 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.
Related programmes
Master’s in Marine/Nautical Electronics: IP67/69K
Online master's programme of 1,900 hours in marine/nautical electronics (IP67/69K, corrosion, NMEA 2000 and on-board power). 12 modules covering the marine environment, IP protection ratings, sealed…
Master’s in Functional Safety in Electronics Engineering
Online master's programme of 1,900 hours in functional safety in electronics engineering, structured in 12 modules covering hazard and risk analysis, safety system architectures, hardware failure…
Master’s in Reliability, Derating and Design for Manufacture Engineering
Online master's programme of 1,900 hours in reliability, derating and design for manufacturing engineering. 12 modules covering reliability statistics and prediction, component derating to ECSS-Q-ST-30-11C, FMEA…
More in Electronics, Embedded Systems & Telecom
All Electronics, Embedded Systems & Telecom programmes → · How to apply · Fees & financing · Scholarships