dimensional variation in automotive body assembly student: timothy ian matuszyk academic supervisory...
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![Page 1: Dimensional Variation in Automotive Body Assembly Student: Timothy Ian Matuszyk Academic supervisory panel: Prof. Michael Cardew-Hall Dr. Bernard F. Rolfe](https://reader036.vdocuments.net/reader036/viewer/2022062516/56649d605503460f94a40e68/html5/thumbnails/1.jpg)
Dimensional Variation in Automotive Body Assembly
Student:Timothy Ian Matuszyk
Academic supervisory panel:
Prof. Michael Cardew-HallDr. Bernard F. RolfeDr. Paul Compston
Funding:
Australian Research Council Linkage Grant (#LP0560908)
Industry Partner: Ford of Australia
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Territory front-cross #10922
Front Cross member
Front Cross member & Fender
Front Cross / Fender / Hood
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Improving manufacturing processes
“In the future sustainable competitive advantage will depend more on new process technologies
and less on new product technologies”
(Thurow 1992)
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Continuous quality improvement benefits
Higher quality assemblies, Less warranty concerns, Reduced launch time
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Rigid vs Non-rigid assembly
Takezawa (1980) first showed that the additive theorem of variance does not hold for non-rigid assemblies, and that variation was in fact absorbable.
Rigid assembly Non-rigid assembly
21 hhH
h22
2
2
1 hhH
h1
H
4.111 22 H
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1
2L 4L 5L
17L
38L 19L
8L7L
37L 36L
32L
33L
29L
30L
31L
27L28L
23R
22R
42L
21R
26L
14L
10L
11L41L
16L
43L40L
39L
Note: Points and locators mirrored on opposite side
Clamp/rest -
Rest -
1
2L 4L 5L
17L
38L 19L
8L7L
37L 36L
32L
33L
29L
30L
31L
27L28L
23R
22R
42L
21R
26L
14L
10L
11L41L
16L
43L40L
39L
Note: Points and locators mirrored on opposite side
Clamp/rest -
Rest -
Assembly x 9
Component D x 9 Component C x 9
Component A1/A2 x 9
Component B1/B2 x 9
• Observe and compare variation levels in components & assembly (9 samples)
• 38 points & 22 holes measured in final assembly
Initialstudy
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Industry study findings Looked at production assembly issues & identified areas of investigation,
which included: Cases of variation levels decreasing over the assembly process Consistent positional shifts of holes from components to assembly
Lower Variation
Higher Variation
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FE Assembly models
A way of simulating process variation stack-up. Linear models are fast but lack
accuracy. Non-linear models are more
accurate but are slow and suffer from convergence issues.
Thermo-mechanical approaches add even more complexity.
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New data analysis possibilities
Optical co-ordinate measuring machines have allowed for quick and detailed inspection.
Shape characterization
Regression modelling of responses
Machine learning to deal with large data sets.
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Aims
This project aims to identify:How component variation propagates through
an assembly processWhich process changes can reduce overall
variability in assemblies
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Experimental vs FEM
•Actual process provides the best data
•Rapid prototyping
•Easy dimensional inspection
ADVANTAGES
•Time consuming
•Resources
•Model assumptions = less accuracy
DISADVANTAGES
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How does part variation translate to assembly variation?
Assembly shape?Bow
Bow and
Spring-back
Twist
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Do different processes affect final assembly variability?
Comparison of final assembly shapes for 3 different clamp sequences given the same input part variability (bow in the hat).
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Data reduction and patterns
Component
shapes
Assembly
shapes
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Key steps
1. Understanding/modelling variation transmission.
2. Structured experimentation to identify the variation of alternative processes.
3. Classifying component shapes into groups that share the same optimal process.
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An adaptable assembly process
Imagine a process that can measure input components
and select the optimal assembly approach for
minimized variability in the final assembly.
In-line OCMM