Use virtual models to de-risk projects, prove concepts and optimise performance before you touch the real plant. Our Digital Twin & Simulation services let you test control strategies, validate designs and train operators in a safe, repeatable environment – reducing commissioning time, cost and disruption.
Overview
Digital twins and high-fidelity simulations create a virtual replica of your production line, machine, warehouse or process.
We use them to help you:
- Prove ideas and control concepts quickly and safely
- Find bottlenecks and failure modes before they impact operations
- Shorten on-site commissioning and minimise downtime
- Support continuous improvement with data-driven insight
Whether you’re upgrading legacy equipment or designing a new facility, simulation gives you evidence to make better decisions.
What we do
Content & Scoping
- Define objectives – throughput, availability, layout changes, automation upgrades
- Decide model scope and required fidelity (machine, line, plant, warehouse)
Dynamic simulation models
- Discrete-event and continuous process models
- Layout, material flow and buffering studies
- Queue, resource and workforce modelling
Control System Emulation
- Virtual PLC, robot and safety logic testing
- Emulation of conveyors, drives, sensors, AMRs/AGVs and interlocks
- Virtual FAT to debug logic before site work
Digital twins of existing systems
- Build as-is twins from layouts, P&IDs, tags and live data
- Connect to real-time data for what-if and performance analysis
- Replay incidents to understand root causes and improvements
Operator training & rehearsal
- Scenario-based training on the digital twin
- Start-up, shutdown and fault handling drills without production risk
Typical applications
Customers most often use Digital Twin & Simulation for:
New production lines and cells
Validate layouts, cycle times and buffer sizes
Prove automation concepts before committing capital
Robotics, logistics & warehousing
Validate robot reach, cycle times and paths
Test AMR/AGV flows, traffic rules and charging strategies
Optimise picking, packing and despatch operations
Process industries & utilities
Evaluate control strategies, setpoints and alarm handling
Assess impact of new equipment or operating regimes
Upgrades and brownfield projects
Test phased migration strategies and cutover plans
Simulate running old and new systems in parallel
Mission critical & safety-related systems
Rehearse emergency and degraded-mode operation
Demonstrate availability and redundancy strategies
Our process
We follow a structured, engineering-led approach:
Model design & data gathering
Capture layouts, equipment data, control logic and process rules
Agree assumptions, simplifications and scenarios to be modelled
Model build & validation
Build the simulation or digital twin and review interim versions
Validate behaviour and performance against real-world data where available
Scenario analysis & optimisation
Run defined scenarios – normal, peak, failure and future-state
Perform sensitivity and bottleneck analysis; compare options quantitatively
Handover, training & ongoing support
Present findings and recommendations in clear engineering terms
Option for ongoing access to the model for further studies and training
Support to integrate results into design, control logic and project plans
Define objectives & success criteria
Workshops with operations, engineering and management
Clear questions the model must answer and decisions it will inform
Model build & validation
Build the simulation or digital twin and review interim versions
Validate behaviour and performance against real-world data where available
Scenario analysis & optimisation
Run defined scenarios – normal, peak, failure and future-state
Perform sensitivity and bottleneck analysis; compare options quantitatively
Handover, training & ongoing support
Present findings and recommendations in clear engineering terms
Option for ongoing access to the model for further studies and training
Support to integrate results into design, control logic and project plans