Digital Twin
A way to Drive Smarter IoT Business Decisions
Webinar Agenda
▪ Digital twin definition
▪ The driving technology behind Digital twin
▪ Companies behind realizing this concept
▪ Open source contribution to the digital twin pattern
Definition
Historical background
▪ NASA initial pioneered the idea of digital twin
▪ The concept formulated in University of Michigan 2003 By Dr.
Michael Grieves Specialist in Life cycle management & JohnVickers
of Nasa
▪ The adoption of this model in industries till 2014
▪ Introducing cognitive & AI starting form 2015 by IBM, Microsoft and
industry leaders
▪ 2017 and going on introduce immersive digital twin experience with
Augmented reality
Information Mirroring Model
▪ Physical products (Real space)
▪ Virtual products(Virtual Space)
▪ The connection
– Data
– Information
The current situation
▪ The product modeled in 3D and numerically simulated
▪ Generate the bill of material and deliver this model to manufacturer
▪ The manufacturer convert this 3D models in many cases to 2D blue
prints
▪ The digital and simulated product no longer used
▪ The actual link between simulated digital model and physical
fabricated device was not there
The Aim of Digital twin
▪ Close the loop between
physical and digital world
▪ Build a unified repository that
link two product together
▪ Build a closed loop feedback
between simulated model and
physical product after
manufacturing
Digital Twin Model Use cases
▪ Conceptualization
▪ Comparison
▪ Collaboration
Conceptualization
▪ Current situation
– Human take visual information
– Reduce it to symbols of numbers and letters
– Re-conceptualize it visually
▪ Draw back of this
– Loose great deal of information
– Inefficient time
▪ Using digital twin directly provide the conceptualize visual look for
the current situation
Comparison
▪ Current situation
– Virtual product information
– Physical product information
– Find out the correspondence and work out the difference
▪ Using digital twin will directly provide the difference in term of colors
for example green no difference between virtual prediction and
physical, red there is difference that need corrective action
Collaboration
▪ Current situation
– A fault detected in machine or in product line
– Machine physically inspected
– Identify the error and perform calibration
▪ Draw backs
– The accident already occurred
– Might require access to technical expert in different Geo
– Limited to the machines assessed in physical location for example consumer car
should be inspected in maintenance center
▪ Digital twin: Physical device report its state real-time, experts has
digital representation to it, expert could perform the tuning and
calibration remotely
Motivation behind Digital twin
▪ Better connectivity (Devices, bandwidth, cloud, ….)
▪ Artificial intelligence & Cognitive in business domain
▪ Big data and analytics
▪ And Finally Internet of things
The Role of IoT in Digital Twin
▪ Internet of things is one piece puzzle in the piece of digital twin
concepts envisioned by NASA to be adopted in industrial Enterprise
and consumer product, by making the two way commination
between the physical product and its digital realization by events and
commands
▪ Events
– A physical device data sent to Digital platform
▪ Commands
– The outcome of analytics, human interaction on virtual world, translated into
command to the Physical device
Digital twin Journey by Microsoft
https://www.youtube.com/watch?v=5lgOcWPQP1A
Digital twin sample architecture diagram
by IBM
https://www.ibm.com/blogs/bluemix/2017/06/smartfactorykl-industrie-40-
reference-architecture-example/
Immersive experience IBM & DAQRI
https://www.youtube.com/watch?v=RjuoYJ5ZXcY
Eclipse Ditto
Ditto provides
Things representation in Ditto
▪ ACL
▪ Attributes
▪ Features
References
▪ Dr. Michael Grieves
– https://www.youtube.com/watch?v=Rs5qczNT6zo
– http://innovate.fit.edu/plm/documents/doc_mgr/912/1411.0_Digital_Twin_Whit
e_Paper_Dr_Grieves.pdf
▪ IBM resources
– https://www.youtube.com/watch?v=0-GCYIAKbiI
– https://www.youtube.com/watch?v=RaOejcczPas&t=2s
– https://www.ibm.com/blogs/bluemix/2017/06/smartfactorykl-industrie-40-
reference-architecture-example/
▪ Microsoft resources
– https://www.youtube.com/watch?v=5lgOcWPQP1A

Digital twin - Internet of Things

  • 1.
    Digital Twin A wayto Drive Smarter IoT Business Decisions
  • 2.
    Webinar Agenda ▪ Digitaltwin definition ▪ The driving technology behind Digital twin ▪ Companies behind realizing this concept ▪ Open source contribution to the digital twin pattern
  • 3.
  • 4.
    Historical background ▪ NASAinitial pioneered the idea of digital twin ▪ The concept formulated in University of Michigan 2003 By Dr. Michael Grieves Specialist in Life cycle management & JohnVickers of Nasa ▪ The adoption of this model in industries till 2014 ▪ Introducing cognitive & AI starting form 2015 by IBM, Microsoft and industry leaders ▪ 2017 and going on introduce immersive digital twin experience with Augmented reality
  • 5.
    Information Mirroring Model ▪Physical products (Real space) ▪ Virtual products(Virtual Space) ▪ The connection – Data – Information
  • 6.
    The current situation ▪The product modeled in 3D and numerically simulated ▪ Generate the bill of material and deliver this model to manufacturer ▪ The manufacturer convert this 3D models in many cases to 2D blue prints ▪ The digital and simulated product no longer used ▪ The actual link between simulated digital model and physical fabricated device was not there
  • 7.
    The Aim ofDigital twin ▪ Close the loop between physical and digital world ▪ Build a unified repository that link two product together ▪ Build a closed loop feedback between simulated model and physical product after manufacturing
  • 8.
    Digital Twin ModelUse cases ▪ Conceptualization ▪ Comparison ▪ Collaboration
  • 9.
    Conceptualization ▪ Current situation –Human take visual information – Reduce it to symbols of numbers and letters – Re-conceptualize it visually ▪ Draw back of this – Loose great deal of information – Inefficient time ▪ Using digital twin directly provide the conceptualize visual look for the current situation
  • 10.
    Comparison ▪ Current situation –Virtual product information – Physical product information – Find out the correspondence and work out the difference ▪ Using digital twin will directly provide the difference in term of colors for example green no difference between virtual prediction and physical, red there is difference that need corrective action
  • 11.
    Collaboration ▪ Current situation –A fault detected in machine or in product line – Machine physically inspected – Identify the error and perform calibration ▪ Draw backs – The accident already occurred – Might require access to technical expert in different Geo – Limited to the machines assessed in physical location for example consumer car should be inspected in maintenance center ▪ Digital twin: Physical device report its state real-time, experts has digital representation to it, expert could perform the tuning and calibration remotely
  • 12.
    Motivation behind Digitaltwin ▪ Better connectivity (Devices, bandwidth, cloud, ….) ▪ Artificial intelligence & Cognitive in business domain ▪ Big data and analytics ▪ And Finally Internet of things
  • 13.
    The Role ofIoT in Digital Twin ▪ Internet of things is one piece puzzle in the piece of digital twin concepts envisioned by NASA to be adopted in industrial Enterprise and consumer product, by making the two way commination between the physical product and its digital realization by events and commands ▪ Events – A physical device data sent to Digital platform ▪ Commands – The outcome of analytics, human interaction on virtual world, translated into command to the Physical device
  • 14.
    Digital twin Journeyby Microsoft https://www.youtube.com/watch?v=5lgOcWPQP1A
  • 15.
    Digital twin samplearchitecture diagram by IBM https://www.ibm.com/blogs/bluemix/2017/06/smartfactorykl-industrie-40- reference-architecture-example/
  • 16.
    Immersive experience IBM& DAQRI https://www.youtube.com/watch?v=RjuoYJ5ZXcY
  • 17.
  • 18.
  • 19.
    Things representation inDitto ▪ ACL ▪ Attributes ▪ Features
  • 20.
    References ▪ Dr. MichaelGrieves – https://www.youtube.com/watch?v=Rs5qczNT6zo – http://innovate.fit.edu/plm/documents/doc_mgr/912/1411.0_Digital_Twin_Whit e_Paper_Dr_Grieves.pdf ▪ IBM resources – https://www.youtube.com/watch?v=0-GCYIAKbiI – https://www.youtube.com/watch?v=RaOejcczPas&t=2s – https://www.ibm.com/blogs/bluemix/2017/06/smartfactorykl-industrie-40- reference-architecture-example/ ▪ Microsoft resources – https://www.youtube.com/watch?v=5lgOcWPQP1A