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MID3
Manufacturing Industry Data-Driven Digital Twin
Speaker: Diego Rovere
MID3 Objectives
MID3 Focus
Digital Twin of the I4.0Lab (Polytechnic of Milan) for:
1. factory constant status monitoring
2. behavioural models adaptation
3. what-if analysis
MIDIH-RA as real-to-digital synchronization framework
Expected results
Full simulation model of the I4.0Lab synchronized with the
actual factory, performing constant status monitoring and
performance forecasting and deployed on the MIDIH
infrastructure
TTS Simulation Engine equipped with MIDIH Unit Databus
Connector
MID3 Implementation
Overall architecture
MID3 Management Module
FIWARE Connector
Simulation
Engine
Monitoring
engine
Temporary
parameters
store
Configuration and
simulation management
GUI
OPC-UA
Shop Floor
OPC-UA
Agent
Orion Context Broker
MID3 Management Module
MID3 Management Module supports
• continuous data acquisition from the
field
• synchronization of simulation model
parameters
• plant simulation configuration and
control
• MES interfacing
MID3 Management Module
FIWARE Connector
Monitoring
engine
Temporary
parameter
s store
Configuration and
simulation management
GUI
MID3 Management Module GUI
Data
acquisition
Simulation
Control
I4.0 Lab Simulation Model
Support to all existing
and newly defined MES workplans
Modular 3D Simulation model
Parametrized behavioural logics
An alternative deployment
MID3 Management Module
FIWARE Connector
Simulation
Engine
Monitoring
engine
Temporary
parameter
s store
Configuration and
simulation management
GUI
OPC-UA
Shop Floor
MID3 Results assessment
KPI
Stations covering Percentage of simulated processing stations of the
“I4.0 Lab” POLIMI didactic plant respect to the total
number of physical stations.
100%
Production lead time
deviation
Deviation of the lead time calculated by the
simulation model and the real one on all the product
variants
<10%
Models reuse Reuse into the simulation of the 3D models already
existing of the plant.
100%
Integrated stations Percentage of stations monitored through the MIDIH
infrastructure of the I4.0 Lab based on Arrowhead and
mirroring their parameters on the digital twin
100%
Lesson learnt
real applications of advanced I4.0 technologies
create immediately benefits in terms of
perception and understanding
openness and extensibility
of the frameworks like FIWARE create
value for the whole ecosystem
MID3 Outlook
Near future improvements
Improve the Digital Twin modularity level
Move to “Digital Twin as a service” through
FIWARE infrastructure
THANK
YOU!

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FIWARE Global Summit - MID3 Manufacturing Industry Data-Driven Digital Twin

  • 1. MID3 Manufacturing Industry Data-Driven Digital Twin Speaker: Diego Rovere
  • 3. MID3 Focus Digital Twin of the I4.0Lab (Polytechnic of Milan) for: 1. factory constant status monitoring 2. behavioural models adaptation 3. what-if analysis MIDIH-RA as real-to-digital synchronization framework
  • 4. Expected results Full simulation model of the I4.0Lab synchronized with the actual factory, performing constant status monitoring and performance forecasting and deployed on the MIDIH infrastructure TTS Simulation Engine equipped with MIDIH Unit Databus Connector
  • 6. Overall architecture MID3 Management Module FIWARE Connector Simulation Engine Monitoring engine Temporary parameters store Configuration and simulation management GUI OPC-UA Shop Floor OPC-UA Agent Orion Context Broker
  • 7. MID3 Management Module MID3 Management Module supports • continuous data acquisition from the field • synchronization of simulation model parameters • plant simulation configuration and control • MES interfacing MID3 Management Module FIWARE Connector Monitoring engine Temporary parameter s store Configuration and simulation management GUI
  • 8. MID3 Management Module GUI Data acquisition Simulation Control
  • 9. I4.0 Lab Simulation Model Support to all existing and newly defined MES workplans Modular 3D Simulation model Parametrized behavioural logics
  • 10. An alternative deployment MID3 Management Module FIWARE Connector Simulation Engine Monitoring engine Temporary parameter s store Configuration and simulation management GUI OPC-UA Shop Floor
  • 12. KPI Stations covering Percentage of simulated processing stations of the “I4.0 Lab” POLIMI didactic plant respect to the total number of physical stations. 100% Production lead time deviation Deviation of the lead time calculated by the simulation model and the real one on all the product variants <10% Models reuse Reuse into the simulation of the 3D models already existing of the plant. 100% Integrated stations Percentage of stations monitored through the MIDIH infrastructure of the I4.0 Lab based on Arrowhead and mirroring their parameters on the digital twin 100%
  • 13. Lesson learnt real applications of advanced I4.0 technologies create immediately benefits in terms of perception and understanding openness and extensibility of the frameworks like FIWARE create value for the whole ecosystem
  • 15. Near future improvements Improve the Digital Twin modularity level Move to “Digital Twin as a service” through FIWARE infrastructure