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Predicting Product Cosmetic Quality in the Automobile Industry

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University of Strathclyde. Presentation for Kathryn Milnes. Slide 2. Funded by. Supported by ... University of Strathclyde. Neal Juster, Snudge and Martin ... – PowerPoint PPT presentation

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Title: Predicting Product Cosmetic Quality in the Automobile Industry


1
Predicting Product Cosmetic Quality in the
Automobile Industry
  • Stephen Taylor Martin Fitchie
  • CAD Centre
  • University of Strathclyde

2
Funded by
Supported by
3
Content
  • Business Case
  • Overview of the VITAL System
  • Case Study
  • Technical Challenges
  • TAVI within VITAL
  • Future Work Developments

4
Product Development VITAL
5
Overall Goal
  • To enable multi-disciplinary design teams
  • To visualise the external aspects of an
    automobile
  • Within a realistic model of the physical
    environment
  • At conceptual design stage

6
Case Study Rover 75
7
Cosmetic Quality
  • No agreed definition
  • Look of the product
  • Gaps and flushness
  • Can dramatically affect customer perception

8
Example
Good
Bad
9
VITAL Demonstration
10
Real and Virtual Comparison
Virtual
Real
11
Technical Challenges
  • Visualisation of tolerances (Strathclyde)
  • Interface commercial tolerance packages with high
    quality visualisation
  • TAVI (Tolerance Analysis Visualisation Interface)
  • Deformable assemblies (Leeds)

12
System Architecture
User Interaction Interface
Behaviour Model
Deformation Model
Assembly Model
Environment Model
TAVI
VITAL Tools
Feedback to the user
PQP Collision Detection MathEngine Dynamics
ClearCoat? Rendering
Third Party Tools
OpenGL Optimizer
VSA
Visualisation
13
Current tolerance tools
  • Difficult to visualise impact of output

14
(No Transcript)
15
VSA
VSA I-DEAS analysis on Filler Flap, FFMs Select
measurement points.
VSA Monte Carlo on assemblies
Output to VSL files
Data file read into TAVI
TAVI communicates with VITAL
16
VITAL Tolerance Analysis
17
Future Work and Developments
  • Apply data from real VSA results
  • Introduce system for simultaneous examination of
    multiple inspection points and TAVI windows
  • Feedback from engineers Jaguar Magna
  • Use on real-time case studies Jaguar

18
Team
  • University of Strathclyde
  • Neal Juster, Snudge and Martin Fitchie
  • University of Leeds
  • Peter Dew, John Maxfield, Jeff Zhao
  • SGI
  • Steve Watson
  • MAGNA
  • Mark Skelly
  • Funded by EPSRC

19
(No Transcript)
20
Assembly Model
21
Assembly Model
  • Enables assignment of mating conditions
  • Against
  • Concentric
  • Cylindrical fit
  • Spherical fit

22
Environment Model
  • Aims to maximise reality
  • Materials, textures, shadows, reflections
  • Extremely important for quality audits
  • Define light sources
  • Produce sealed cuboid from digital photographs of
    environment
  • Sgis ClearCoat360

23
Behaviour Model
  • Attempt to simulate physics
  • Gravity
  • Friction
  • Kinematics

24
Deformable Model
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