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REAL-TIME PREDICTION OF SHIMS DIMENSIONS IN POWER TRANSFER UNITS USING MACHINE LEARNING
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2019.
Keywords [en]
MATLAB, Machine Learning, Smart Manufacturing, Classification, Regression, Power Transfer Units, Industry 4.0, Assembly Line, Support Vector Machines, Artificial Neural Network, Partial Least Squares Regression, Decision Tree, Bagging, Bagged Decision Trees, Support Vector Regression Machines, SVR, SVM, ANN, PTU, DT, Bagged DTs
National Category
Robotics
Identifiers
URN: urn:nbn:se:mdh:diva-45615OAI: oai:DiVA.org:mdh-45615DiVA, id: diva2:1362747
External cooperation
GKN Automotive Köping AB
Presentation
(English)
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Examiners
Available from: 2019-11-13 Created: 2019-10-21 Last updated: 2019-11-13Bibliographically approved

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3031323334353633 of 37
CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf