education master class - mathworks · 8 what tomorrow’s engineers and scientists need to know •...
TRANSCRIPT
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2© 2015 The MathWorks, Inc.
Education Master ClassPreparing Future Engineers and
Scientists for the Challenges of
Digital Transformation
Martina Sciola
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Digital Transformation Era
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Machine Learning for Real-time Optimization of Energy Usage
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CETO, a Wave Farm built with Model-Based Design
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Augmented Reality Visualization of blood flow with SLAM
technology
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Why Digital Transformation?
• Increasingly individualized products
• Autonomous machines that do not require costly
programming to meet new requirements
• Intelligent products that collect data to optimize
processes and develop new products
• Opportunities for innovative business models
and services
“Sample-size 1”
“Smart products”
“Servitization”
[From en.wikipedia.org]
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What Tomorrow’s Engineers and Scientists Need to Know
• Control, Signal Processing, Optimization, Computer Vision
• Abstraction, Modelling, and Simulation
AND
• Multidomain System Development
AND
• Distributed and Connected Systems
• Using Cloud Platforms and Big Data Processing
• AI and Data Science
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Project-Based Learning with MATLAB and Simulink
Treat engineering students like engineers
Hands-on experience of working on hardware and software
Solve authentic problems in myriad contexts
Increase student interest and improve learning
https://www.mathworks.com/hardware-support/home.html
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Today’s Topics: Three Exercises to Develop That Know-How
Triplex Pump Digital Twin
Arduino Mobile Rover
Quadcopter Simulation
• Develops Computational
Thinking for complex
systems
• Enables comparisons of
theory and simulation
• Principles of control and
path planning
• Model-Based Design
for autonomous vehicle
• Integrates control,
communication, path
planning, and
localization
• Multidisciplinary
system
• Complex industrial
application
• Combines engineering
and data science
• Cloud computing
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Today’s Topics: Three Exercises to Develop That Know-How
Triplex Pump Digital Twin
Arduino Mobile Rover
Quadcopter Simulation
• Develops Computational
Thinking for complex
systems
• Enables comparisons of
theory and simulation
• Principles of control and
path planning
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Quadcopter SimulationDevelop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Quadcopter: Modelling – part 1 Develop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Quadcopter: Modelling – part 2 Develop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Quadcopter: Modelling – part 3 Develop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Quadcopter: Modelling – part 3 Develop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Quadcopter: Control Design Develop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Quadcopter: Code Generation for Deployment Develop Understanding of
Technical concepts
Control System Design
Code generation for
deployment
Plant Modelling
Commercial
CAE
Simscape
Multibody
Comparison
Math
Derivation
MATLAB
Simulink
Symbolic
Math
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Today’s Topics: Three Exercises to Develop That Know-How
Triplex Pump Digital Twin
Arduino Mobile Rover
Quadcopter Simulation
• Model-Based Design
for autonomous vehicle
• Integrates control,
communication, path
planning, and
localization
• Multidisciplinary system
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Arduino Mobile Rover in Action
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Mobile Rover Basics
Arduino+
Motor Control
DC Motors+
Encoders
Battery
Ultrasonic
Sensor
Servo Motor
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1. Modelling and simulation
2. Deploy to hardware
3. Integrate with localization using Wi-Fi
Workflow
Mathematical
Models
C/C++
code
(0,0)
(25,25)
91⁰(12,37)
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Rover velocities Input Rover trajectoryOutput
Modelling and Simulation
Rover kinematics
ICC
ꞷ
v
ꞷlꞷr
L
Forward velocity (v)
Rate of rotation (ꞷ)
Right wheel speed (ꞷr)
Left wheel speed (ꞷr)
[ꞷr, ꞷl]=f(v, ꞷ, L, r)
Trajectory on x axes (x(t))
Trajectory on y axes (y(t))
Angle of rotation (θ(t))
[x(t), y(t), θ(t)]=f(v, ꞷ)
θ
x
y
Wheels velocities
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Modelling and Simulation
Rover kinematics
10
5
v (cm/s)
t (s)
t (s)
ꞷ (deg/s)
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5 10 Forward kinematics
𝜔𝑙
𝜔𝑟=1
𝑟∗
1 − ൗ𝐿 2
1 ൗ𝐿 2
∗𝑣𝜔
Inverse kinematics
𝑥 𝑡 = න0
𝑡
𝑣 ∗ cos 𝜃 𝑑𝑡
𝑦 𝑡 = න0
𝑡
𝑣 ∗ 𝑠𝑖𝑛 𝜃 𝑑𝑡
𝜃 𝑡 = න0
𝑡
𝜔 𝑑𝑡
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Modelling and Simulation
Path Planning and Motion Control
Calculate angle
Turn
Calculate distance
Move Forward
Pick-up / Drop
Next waypoint Legend
Path planning
Motion control
Rover location
Object location
Final destination
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1. Modelling and simulation
2. Deploy to hardware
3. Integrate with localization using Wi-Fi
Workflow
Mathematical
Models
C/C++
code
(0,0)
(25,25)
91⁰(12,37)
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Deploy to Hardware
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Deploy to Hardware
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1. Modelling and simulation
2. Deploy to hardware
3. Integrate with localization using Wi-Fi
Workflow
Mathematical
Models
C/C++
code
(0,0)
(25,25)
91⁰(12,37)
![Page 29: Education Master Class - MathWorks · 8 What Tomorrow’s Engineers and Scientists Need to Know • Control, Signal Processing, Optimization, Computer Vision • Abstraction, Modelling,](https://reader033.vdocuments.site/reader033/viewer/2022052019/6032805564e8a37d0a28a32d/html5/thumbnails/29.jpg)
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(0,0)
(25,25)
91⁰(12,37)
Get Location Data over Wi-Fi
Webcam on top of a table;
Tethered to PC
Taking
picture of
arena
Image
Processing
Location
results sent via
Wi-Fi
• RGB threshold applied
• Noise removed
• Centroid identified
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Arduino
Raspberry PiLEGO Mindstorms EV3
TI C2000
ST Micro
Parrot
Minidrones
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Today’s Topics: Three Exercises to Develop That Know-How
Triplex Pump Digital Twin
Arduino Mobile Rover
Quadcopter Simulation
• Complex industrial
application
• Combines engineering
and data science
• Cloud computing
![Page 32: Education Master Class - MathWorks · 8 What Tomorrow’s Engineers and Scientists Need to Know • Control, Signal Processing, Optimization, Computer Vision • Abstraction, Modelling,](https://reader033.vdocuments.site/reader033/viewer/2022052019/6032805564e8a37d0a28a32d/html5/thumbnails/32.jpg)
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Triplex Pump
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Predictive Maintenance Using Digital Twins
How can I teach students these concepts if I don’t have a real pump?
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Sensor Data
Predictive
Maintenance
algorithm
Digital Twin
Machine
Learning model
in MATLAB.
Prevent system downtime
by sending
to aBlocked inlet
Seal Weak
Worn Bearing?
created using a
and
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Component
Failure
Triplex Pump
▪ Crankshaft drives three plungers
– Each 120 degrees out of phase
– One chamber always discharging
– Smoother flow than single
or duplex piston pumps
Crankshaft
Outlet
Algorithm
Pressure
Sensor
Failure
Diagnosis
Inlet
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Predictive Maintenance Workflow
▪ Sensor data isn‘t always available
– Failure conditions difficult to reproduce
– Time consuming or costly to generate
Solution: Build digital twin and generate
sensor data using simulation
▪ Developing algorithm is complex
– Requires complex concepts and analysis
Solution: Use MATLAB to simplify process of
developing and deploying algorithm
Deploy
Algorithm
Develop
Predictive Model
Preprocess
Training Data
Obtain and
Explore Data
Build Digital
Twin
SimulationControl
Unit
Sensor Data
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Bring these exercises to your classroom!
Triplex Pump Digital Twin
Arduino Mobile Rover
Quadcopter Simulation
• Develops Computational
Thinking for complex
systems
• Enables comparisons of
theory and simulation
• Principles of control and
path planning
• Model-Based Design
for autonomous vehicle
• Integrates control,
communication, path
planning, and
localization
• Multidisciplinary
system
• Complex industrial
application
• Combines engineering
and data science
• Cloud computing
![Page 39: Education Master Class - MathWorks · 8 What Tomorrow’s Engineers and Scientists Need to Know • Control, Signal Processing, Optimization, Computer Vision • Abstraction, Modelling,](https://reader033.vdocuments.site/reader033/viewer/2022052019/6032805564e8a37d0a28a32d/html5/thumbnails/39.jpg)
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Key takeaways
▪ Digital Transformation is revolutionizing the industry
▪ New graduates will be expected to address challenges like these
▪ Experience with tools and workflows used in industry make students more
hireable
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Vision
2040: Austria is world leader in STEM education
Mission
Strengthen STEM education and secure local industry in Austria
Strategy
Connect stakeholders in academia, industry and government.
Initiate, and support high-impact STEM projects.
Projects
Multicopter for teaching and research
EDU
COMGOV
[From Google Maps]
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ComGov
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Turn CHALLENGES into OPPORTUNITIES
Recruiting
Hiring
Market
penetration
in AERO
Brand
awareness
Courses
Research
in AERO
3 Hires
in 1 semester
1 Million
views in
24 hrs
Retain
Students
Prepare
Students for INDUSTRY
Positive
Learning
Experience
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CALL TO ACTION!
Build relationships
Partner
Design joint projects
Actively collaborate
EDU
COMGOV P
P
P
P
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Thank you!