Sales & Marketing Alignment_ How to Synergize for Success.pptx.pdf
Digital Twin. As enabler of predictive models. Marco Poggi, Bridgestone
1. Data Driven Innovation - Università degli Studi “Roma Tre”
May 18th, 2018
as enabler of predictive models
Digital Twin
Marco Poggi
R&D Digital Solutions, Bridgestone EMEA
2. 2
• Mega-Trends and Mobility Eco-System
• Bridgestone - Overview
• The evolution of the tire
• The Digital Twin
• Predictive models:
• Wear
• Fuel Economy
• Safety
Agenda
3. 3
Mega-Trends transforming the Mobility Eco-System
Mobility Eco-System under transformation:
ACES: Autonomous, Connected, Electric, Shared
Mega-Trends
Exhausting
natural resources
Urbanization
New consumer
behaviors
Aging of
population
New climate
change
5. 5
Bridgestone - Overview
EMEA R&D Rome (1970s)
• 580+ Employee
• 50+% Univ. Degree
• 5+% PhD
• 16 Nations
• Data Scientists
• Computer Engineers
• Cloud Engineers
• App Developers
• Mechatronics
• Electronics
• Automotive Engineers
Bridgestone Corporation 6 business units
1. Japan 2. Americas 3. EMEA 4.Asia Pacific
5. Diversified Products 6.Speciality Tires
150+ countries 143.000+ employees
Digital Garage (2017)
University &
Research
1
Start-ups
Spin off
2
4
Tech prototypes
Young talents
Laboratory experimentations
Tech
providers
5
Disruptive technologies
and products
Accelerator
3
Startups
High tech product/components
TIRES MOBILITY SOLUTIONS
NEWECOSYSTEM
6. 6
The Evolution of Tires
Bias
Radial
Run flat
Lightweight Sensing
Air Free
PAST
• Three major evolutionary phases can be recognized
• The “intelligent tire” phase will be driven by sensing, data and new design concepts
• The digital twin concept will play an important role to make the tire “intelligent”
Rigid
Wheel
Pneumatic Tire
Intelligent Tire
Intelligent
Digital Twin
7. 7
The Digital Twin Concept
Tire Digital Twin
Wear
Fuel Economy
Safety
7
https://www.geoilandgas.com/software-solutions/industrial-internet/digital-twin-machine-learning-differentiator-oil-and-gas-iiot
• Digital Twins are digital representations of physical parts, processes or systems
• Digital and physical data is paired, combined with advanced analytics and learning systems
• Improve accuracy in decision making and deliver savings and optimization
Digital Twin Example: GE Gas Turbine
8. 8
Digital Twin - Wear Technology
Predicted Wear Profile
• Digital Twins for wear are augmented by real data from vehicle and route information
• Connected vehicle and tire information are enablers to deliver on digital twin for Wear
Actual Tire WearReal or Digital Twins
Vehicle
Route
WearPotential
9. 9
Digital Twin – Rolling Loss Technology
Predicted Loss
• Digital Twins for rolling loss increase fuel efficiency over the tire life cycle
• Route and tire configuration can be optimized
Actual Tire LossReal or Digital Twins
Vehicle
Route
RollingLossPotential
10. 10
Digital Twin – Safety performances
Actual Tire Performances
SafetyPotential
• Digital Twins for traction optimize system performance across different driving conditions
• The intelligent tire communicates state information to update the digital twin
11. 11
Mobility is being fundamentally transformed by multiple converging trends
Digital technology is one of the enablers of this transformation
Tires are evolving to become “intelligent”
Intelligence will be also in the digital tire twin
New business models are emerging that will take advantage of these new digital
capabilities
Summary
12. 12
The Hackathon with Roma TRE and other Universities
MOBILITY PEOPLE ENVIROMENT
The 1st hackathon milestone
on Safer Mobility was held
during the opening event.
13. 13
Hackathon with Rome’s University: Winners!
Team C.A.T.
Mobile App to:
- Driver safety notifications
- Help car maintenance (OBD)
Team Looper
Mobile App to:
- Inform on dangerous roads
- User statistics for intelligent notifications
And coming TEST of Time - 9000€ - May 2018
1st 1st
Best APP - 6000€ - Oct. 2017