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Master'sRobotics, Automation & Control Applications open

Master’s in Cell and Line Digital Twins Engineering

Online master's programme of 1,900 hours in digital twin engineering for manufacturing cells and lines, structured in 12 modules covering geometric and kinematic modelling, robotic cell simulation, line simulation, control logic, virtual commissioning, operational twins, optimisation, ergonomics, interoperability standards and twin deployment, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Define digital twins of production cells and lines.

02

Model the geometry and kinematics of manufacturing equipment.

03

Simulate robotic cells and programme robots offline.

04

Simulate material flow in production lines.

05

Carry out virtual commissioning with PLCs and robots.

06

Connect the twin to operational plant data.

07

Optimise production using the digital twin.

Profile

Who it's for

  • Manufacturing simulation engineers modelling cells and lines.
  • Digital twin specialists moving from design to operational twins.
  • Offline robot programmers working with RobotStudio or Process Simulate.
  • Manufacturing process engineers planning new lines.
  • Virtual commissioning engineers testing PLC and robot logic before start-up.
  • Continuous improvement engineers using simulation to raise throughput.
  • Engineering or science graduates seeking to enter the automotive sector.
Standards & tools

What you'll work with

  • ISO 23247-2:2021 (digital twin framework for manufacturing — reference architecture)
  • IEC 62714-1:2018 (AutomationML) (engineering data exchange format)
  • IEC 63278-1:2023 (Asset Administration Shell structure)
  • ISO 10218-2:2025 (safety of industrial robot applications and cells)
  • IEC 62541-1:2020 (OPC Unified Architecture — overview and concepts)
  • ISO 11226:2000 (evaluation of static working postures)
  • ISO 22400-2:2014 (KPIs for manufacturing operations management)
  • Siemens Process Simulate
  • ABB RobotStudio
  • Siemens Plant Simulation
  • NVIDIA Omniverse
  • Siemens PLCSIM Advanced
Syllabus

12 modules · 1900 h

  1. 1.1Concepts of cell and line twins
  2. 1.2Model levels of detail
  3. 1.3Design twin versus operational twin
  4. 1.4The ISO 23247 standard
  5. 1.5Elements of a robotic cell
  6. 1.6Elements of a production line
  7. 1.7Use cases by life-cycle phase
  8. 1.8Market tools
  9. 1.9Return on investment
  10. 1.10Case study: scope of a line twin
  1. 2.1CAD import and simplification
  2. 2.2STEP, JT and USD formats
  3. 2.3Kinematic modelling of robots
  4. 2.4Mechanisms, grippers and fixtures
  5. 2.5Conveyors and actuators
  6. 2.6Virtual sensors and signals
  7. 2.7Collision detection
  8. 2.8Managing component libraries
  9. 2.9Performance of complex scenes
  10. 2.10Lab: kinematic model of a cell
  1. 3.1Offline robot programming
  2. 3.2Robot cycle simulation
  3. 3.3RRS virtual controllers
  4. 3.4Reachability and placement
  5. 3.5Path optimisation
  6. 3.6Interference analysis between robots
  7. 3.7Welding and painting simulation
  8. 3.8RobotStudio and Process Simulate tools
  9. 3.9Calibration between model and reality
  10. 3.10Practical exercise: reachability study in RobotStudio
  1. 4.1Material flow modelling
  2. 4.2Cycle times and variability
  3. 4.3Breakdowns and availability
  4. 4.4Buffers and their sizing
  5. 4.5Line balancing
  6. 4.6Product changeovers
  7. 4.7Throughput analysis
  8. 4.8Sensitivity experiments
  9. 4.9Validation with production data
  10. 4.10Workshop: line balancing in Plant Simulation
  1. 5.1Physical behaviour modelling
  2. 5.2Signals and sensors in simulation
  3. 5.3Connection with virtual PLCs
  4. 5.4Robot and drive emulation
  5. 5.5Machine safety models
  6. 5.6Start-up and shutdown sequences
  7. 5.7Fault recovery testing
  8. 5.8Simulation time synchronisation
  9. 5.9Fidelity versus performance
  10. 5.10Practical exercise: cell logic with PLCSIM Advanced
  1. 6.1Planning virtual commissioning
  2. 6.2Software-in-the-loop with PLC
  3. 6.3Hardware-in-the-loop with a real controller
  4. 6.4Robot interface testing
  5. 6.5HMI and alarm testing
  6. 6.6Logging defects found
  7. 6.7Reducing commissioning time
  8. 6.8Handover to the customer
  9. 6.9Project lessons learned
  10. 6.10Lab: virtual commissioning of a palletising cell
  1. 7.1Machine data acquisition
  2. 7.2Synchronising the real state
  3. 7.3OEE indicators in the twin
  4. 7.43D visualisation of status
  5. 7.5Detecting cycle deviations
  6. 7.6Integration with MES
  7. 7.7Product tracking
  8. 7.8Alerts and notifications
  9. 7.9Edge architecture of the twin
  10. 7.10Case study: operational twin of a cell
  1. 8.1Sequence optimisation
  2. 8.2Production scheduling
  3. 8.3Energy optimisation of the line
  4. 8.4Maintenance planning
  5. 8.5Expansion scenarios
  6. 8.6Line reconfiguration
  7. 8.7Genetic and heuristic algorithms
  8. 8.8Reinforcement learning in simulation
  9. 8.9Validating improvements on the plant floor
  10. 8.10Practical exercise: energy optimisation of robots
  1. 9.1Digital human models
  2. 9.2RULA and OWAS ergonomic assessment
  3. 9.3Manual workstations
  4. 9.4Simulated human-robot interaction
  5. 9.5Operator training with virtual reality
  6. 9.6Accessibility validation
  7. 9.7MTM standard times
  8. 9.8Operator-centred design
  9. 9.9Integration into the twin
  10. 9.10Workshop: ergonomic assessment with a digital human
  1. 10.1Asset Administration Shell
  2. 10.2OPC UA for twins
  3. 10.3AutomationML for data exchange
  4. 10.4OpenUSD and Omniverse
  5. 10.5FMI for co-simulation
  6. 10.6Model version management
  7. 10.7Integration with PLM
  8. 10.8Neutral robot formats
  9. 10.9Engineering data governance
  10. 10.10Case study: AutomationML exchange between tools
  1. 11.1Life cycle of the twin
  2. 11.2Updating after plant changes
  3. 11.3Owners and governance
  4. 11.4Compute infrastructure
  5. 11.5Data security of the twin
  6. 11.6Scaling to multiple lines
  7. 11.7Value indicators
  8. 11.8Supplier management
  9. 11.9Future trends in twins
  10. 11.10Practical exercise: twin maintenance plan
  1. 12.1Selection of the cell or line
  2. 12.2Geometric and kinematic modelling
  3. 12.3Logic and behaviour
  4. 12.4Virtual commissioning of the solution
  5. 12.5Production simulation
  6. 12.6Connection to real data
  7. 12.7Proposed optimisation and evaluation
  8. 12.8Conclusions and scaling
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

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 the intake, so it is compatible with full-time work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Siemens Process Simulate, ABB RobotStudio, Siemens Plant Simulation, NVIDIA Omniverse and Siemens PLCSIM Advanced, in free, academic or evaluation versions. Exercises are based on real procedures for virtual commissioning of robotic cells, production line simulation and operational twins fed with machine data. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO 23247-2:2021, IEC 62714-1:2018 (AutomationML), IEC 63278-1:2023, ISO 10218-2:2025, IEC 62541-1:2020, ISO 11226:2000, ISO 22400-2:2014.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 23247, IEC 62714 (AutomationML) and IEC 63278 applied to real cases, not as a theoretical annex.
Industry software:Siemens Process Simulate, ABB RobotStudio, Siemens Plant Simulation, NVIDIA Omniverse and Siemens PLCSIM Advanced, in free, academic or evaluation versions.
Master's Thesis with defence:A digital twin of a manufacturing cell or line, from modelling to optimisation, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Model the cell or line
Select the system and build its geometric and kinematic model.
Add logic and behaviour
Connect the model to virtual PLCs and emulate robots and drives.
Commission virtually
Run virtual commissioning and simulate production throughput.
Connect and optimise
Link the twin to real data and evaluate a proposed optimisation.
Master's Thesis
A digital twin of a manufacturing cell or line, from modelling to optimisation, defended before a panel.
Career opportunities

Where this takes you

Manufacturing simulation engineerDigital twin specialistOffline robot programmerManufacturing process engineerVirtual commissioning engineerContinuous improvement engineer
Admissions & scholarships

Requirements

  • A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • 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.

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FAQ

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 Siemens Process Simulate, ABB RobotStudio, Siemens Plant Simulation, NVIDIA Omniverse and Siemens PLCSIM Advanced, 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.

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