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MID3
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 experimental facility synchronized
with the actual factory, performing constant status monitoring
and performance forecasting
The data-driven simulation of the I4.0Lab deployed on the
MIDIH infrastructure
TTS Simulation Engine equipped with MIDIH Unit Databus
Connector
MID3 Implementation
Overall architecture
OPC to REST
Service Provider
MIDIH-RA extension
The MIDIH framework has been extended with a new
Arrowhead Service Provider:
OPC-UA to REST translation service
gives the clients visibility over to the whole set of OPC-UA
variables available on the PLCs
access using simple HTTP GET requests returning required
values encoded in JSON format.
OPC-UA OPC-UA OPC-UA
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
AH Connector
Monitoring
engine
Temporary
parameters
store
Configuration and
simulation management
GUI
MID3 Management Module
Data
acquisition
Simulation
Control
I4.0 Lab Simulation Model
Modular 3D Simulation
model
Parametrized behavioural
logics
Support to all existing and
newly defined MES
workplans
MID3 Results assessment
KPI
KPI-1
Stations covering
Percentage of simulated processing stations of the “I4.0 Lab”
POLIMI didactic plant respect to the total number of physical
stations.
100%
KPI-2
Production lead time deviation
Deviation of the lead time calculated by the simulation model and
the real one on all the product variants
<10%
KPI-3
Models reuse
Reuse into the simulation of the 3D models already existing of the
plant.
100%
KPI-4
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 from
the companies side
openness and extensibility of the
frameworks creates value for the whole
ecosystem
MID3 Outlook
Near future improvements
Improve the Digital Twin modularity level
Move to “Digital Twin as a service”
THANK
YOU!

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MIDIH TTS-MID3 experiment

  • 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 experimental facility synchronized with the actual factory, performing constant status monitoring and performance forecasting The data-driven simulation of the I4.0Lab deployed on the MIDIH infrastructure TTS Simulation Engine equipped with MIDIH Unit Databus Connector
  • 7. OPC to REST Service Provider MIDIH-RA extension The MIDIH framework has been extended with a new Arrowhead Service Provider: OPC-UA to REST translation service gives the clients visibility over to the whole set of OPC-UA variables available on the PLCs access using simple HTTP GET requests returning required values encoded in JSON format. OPC-UA OPC-UA OPC-UA
  • 8. 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 AH Connector Monitoring engine Temporary parameters store Configuration and simulation management GUI
  • 10. I4.0 Lab Simulation Model Modular 3D Simulation model Parametrized behavioural logics Support to all existing and newly defined MES workplans
  • 12. KPI KPI-1 Stations covering Percentage of simulated processing stations of the “I4.0 Lab” POLIMI didactic plant respect to the total number of physical stations. 100% KPI-2 Production lead time deviation Deviation of the lead time calculated by the simulation model and the real one on all the product variants <10% KPI-3 Models reuse Reuse into the simulation of the 3D models already existing of the plant. 100% KPI-4 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 from the companies side openness and extensibility of the frameworks creates value for the whole ecosystem
  • 15. Near future improvements Improve the Digital Twin modularity level Move to “Digital Twin as a service”