Before01
Company profile
- Hand-written rounds
- Fragmented records
- Limited MES visibility
DX Solution
Digital Twin
A digital twin that connects the physical and the virtual
SYSTEM ARCHITECTURE
System architecture
Visualisation, data/model, transport and physical — four layers connected as one data flow.
TWIN
Digital twin visualisation
Visualization Layer
3D Visualization
Unity- Entity Mapping
Blender
WebGL- Rendering Pipeline(HDRP)
- Data Connector(C# Scripts)
- Texture AtlasML-Agents
Digital Twin
Real-Time Data
3D Physics Simulation
Cross-Platform
Quality Prediction
Smart Alarm
Industry Safety
DATA
Data / model layer
Data & Model Layer
Data collection
- OPC-UA collectionNODE → SubmodelElement semantic tags applied automatically
- IoT collectionLive state values bound in
Data storage
- AASX packageJSON serialisation
- Version and historySubmodel version tags / LifeCycle state tracking
Data integration
- AAS RegistrySupports enterprise-wide resource integration
- API GatewayREST API interface
Analytics / AI models
- Digital twin model engineUnity / syncs physical state with the virtual model
- AI / ML submodelsPrediction and anomaly models registered
LINK
Transport layer
Transport Layer
OPC-UA based integration interface
- Data collection
- Protocol standardisation
- Data validation
- Server-client structure
- Encryption / authentication
PHYS
Physical layer
Physical Layer
Equipment controllers
PLCProduction equipment
CNCMachine tools
Robots
Cobot
Industrial robot
AGV / AMR
Identification
Barcode
RFID
Machine vision
IoT sensors
Power meter
Temperature/humidity sensor
Vibration sensor
ARCHITECTURE PROCESS
Implementation process
Four stages, from data collection and infrastructure through model development and integration testing to rollout.
Data collection and infrastructure
- Installing on-site sensors and IoT
- Building the data pipeline
- Starting baseline data collection
Digital twin model development
- 3D physics modelling
- Real-time data integration
- Implementing the simulation engine
- Developing AI/ML prediction models
System integration and validation
- Integrating legacy systems
- Running integration tests
- User acceptance testing (UAT)
Rollout and enhancement
- Deploying to the production environment
- Training administrators
- Enhancement based on feedback
EFFECT
Benefits
What a digital twin leaves behind — in output, defect rate, working environment and cost.
BUSINESS OUTCOME
Floor data,turned into measurable results
- UNIT
Higher output
Running 24/365 without interruption and handling tasks far faster than a person does, cutting processing time.
Uptime · output · tact time
- PASS
Fewer defects
Sensor data raises an alert the moment something drifts, and past data plus the virtual environment explain the cause so the same mistake does not repeat.
Defect rate · anomaly detection · recurrence
- SAFE
A better working environment
Hazards in the areas people work in are simulated to raise safety, and emergency scenarios are rehearsed to sharpen the safety manual.
Hazard zones · emergency response · incidents
- COST
Lower costs
AI reads each machine's energy consumption pattern to strip out waste, and optimal work paths and process order cut labour and logistics cost.
Energy use · labour cost · logistics cost
CASE STUDY
Case study
A factory rebuilt virtually, with power data linked in and carried through to predictive maintenance.
Customer industry
Printed circuit board (PCB) manufacturing
After02
What was built
- Plant rebuilt in 3D
- Meter data per machine
- Predictive maintenance
Results
A digital twin that replaced manual rounds with live visibility
Run the change in the virtual plant before you make it.
Layout changes and added lines, simulated before the money is spent.
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