Course in Digital Twins in Mining Machinery
Online course of 300 h in digital twins for mining machinery. 6 modules covering ISO 23247-1 (digital twin framework for manufacturing), ISO/IEC 30173 (digital twins: concepts and terminology) and Ansys Twin Builder. Assigned tutor and open enrolment.
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
Define what a digital twin is and its maturity levels.
Build physical and behavioural models of a mining machine.
Design the data infrastructure and synchronisation with the real equipment.
Simulate operating scenarios to improve productivity.
Estimate the remaining useful life of critical components.
Establish the governance and cybersecurity of the digital twin.
Propose a project to implement a digital twin in a mine.
Who it's for
- Digital twin engineer who wishes to specialise in Digital Twins in Mining Machinery.
- Mining reliability engineer who wishes to specialise in Digital Twins in Mining Machinery.
- Industrial data scientist who wishes to specialise in Digital Twins in Mining Machinery.
- IIoT solutions architect who wishes to specialise in Digital Twins in Mining Machinery.
- Mining digital transformation manager who wishes to specialise in Digital Twins in Mining Machinery.
- Systems simulation engineer who wishes to specialise in Digital Twins in Mining Machinery.
- Graduates in engineering or science looking to enter the mining sector.
What you'll work with
- ISO 23247-1 (digital twin framework for manufacturing)
- ISO/IEC 30173 (digital twins: concepts and terminology)
- IEC 62541 (OPC UA)
- ISO 15143-3 (telematic data for machinery)
- ISO 13374-1 (data processing for condition monitoring)
- ISO 55001 (asset management)
- IEC 62443 (industrial cybersecurity)
6 modules · 300 h
1.1Definition and digital twin levels1.2Model, simulation and twin: differences1.3Component, machine and operation twins1.4Questions the twin must answer1.5Mining use cases: fleet, plant and mine1.6Data and connectivity requirements1.7Cost of the twin and its return1.8Realistic expectations and common failures1.9Team and required profiles1.10Workshop: defining the scope of a twin
2.1Models based on machine physics2.2Powertrain and consumption models2.3Component wear models2.4Material behaviour models2.5Cycle and productivity models2.6Hybrid models: physics and data2.7Simplification and model order2.8Model validation with real data2.9Model uncertainty and its communication2.10Practice: fuel consumption model of a mining truck
3.1Required signals and sampling frequency3.2Streaming ingestion and storage3.3Synchronisation between twin and real machine3.4Continuous model calibration3.5Acceptable latency by use case3.6Integration with dispatch and plant systems3.7Edge and cloud architecture3.8Security of connections and data3.9Infrastructure costs and optimisation3.10Practice: designing the data architecture
4.1Fleet and haulage circuit simulation4.2Scenarios of route or destination change4.3Simulation of stoppages and availability4.4Optimisation of loader-haul truck matching4.5Consumption and emissions simulation4.6Assessment of electrification and automation4.7Sensitivity analysis of assumptions4.8Comparison of investment alternatives4.9Presenting results to management4.10Practice: simulation of two operating scenarios
5.1Twin applied to asset health5.2Wear and remaining life estimation5.3Effect of operating mode on component life5.4Planning interventions with the twin5.5Advance spare parts ordering5.6Relationship with predictive maintenance5.7Validation with workshop history5.8Measuring attributable savings5.9Integration with maintenance management5.10Practice: estimating the life of a critical component
6.1Phased implementation roadmap6.2Proof of concept and criteria for moving to production6.3Model governance and owners6.4Version management and traceability6.5Training operation teams6.6Risk of relying on a poorly calibrated twin6.7Project and return indicators6.8Supplier dependency and exit plan6.9Common mistakes in digital twin projects6.10Final project: digital twin of a haulage operation
How you'll learn
Fully 100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, making it easy to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The software used is Ansys Twin Builder, MATLAB/Simulink, Azure Digital Twins, Python (pandas, scikit-learn), Siemens Simcenter Amesim, in free, academic or evaluation versions. Practicals cover real model calibration procedures using telemetry data, simulation of mining operating scenarios and component life estimation. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Define what a digital twin is and its maturity levels.
Build physical and behavioural models of a mining machine.
Design the data infrastructure and synchronisation with the real equipment.
Simulate operating scenarios to improve productivity.
Estimate the remaining useful life of critical components.
Where this takes you
Requirements
- No prior degree required.
- Internet connection and a computer capable of running the programme software.
- Sufficient level of Spanish to follow technical standards reading.
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 spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The course uses Ansys Twin Builder, MATLAB/Simulink, Azure Digital Twins, Python (pandas, scikit-learn), Siemens Simcenter Amesim. Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrating 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 are recognised towards the advanced programme. Consult the recognition policy when enrolling.
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