his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
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
Improved Automatic Quality Inspections through the Integration of State-of-the-Art Machine Vision and Collaborative Robots
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-3973-3394
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-3705-5553
2019 (English)In: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 107-112Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we discuss the concepts of a flexible and high-performing solution for automatic quality control that integrates state-of-the-art machine learning algorithms with collaborative robots. The overall aim of the paper is to take the first steps towards improved automatic quality inspections in the manufacturing industry, leading to reduced quality defects and reduced costs in the manufacturing process. For developing and evaluating a first version of a solution that integrates state-of-the-art machine vision and collaborative robots we use a real-world case study focusing on improved quality inspection. Results from the case study shows that it is possible to realize automatic quality inspections through the use of a collaborative robot as intended, but also that there are some challenges that need to be further addressed in order to achieve a top-performing system.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019. Vol. 9, p. 107-112
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords [en]
Industrial Quality Control, Machine Vision, Collaborative Robot
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-18222DOI: 10.3233/ATDE190020ISBN: 978-1-64368-008-8 (print)ISBN: 978-1-64368-009-5 (electronic)OAI: oai:DiVA.org:his-18222DiVA, id: diva2:1396148
Conference
17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, 10–12 September 2019, Queen’s University, Belfast, UK
Available from: 2020-02-25 Created: 2020-02-25 Last updated: 2020-02-26Bibliographically approved

Open Access in DiVA

fulltext(204 kB)3 downloads
File information
File name FULLTEXT01.pdfFile size 204 kBChecksum SHA-512
35ff952d1a7c253a91e8bcddec30696c67bef767dcb1ff057a3c60dcf96a2a7498f48312d927a99e6e4840c8abacd085fc9f4941641c3dea1fcec6a451444949
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Syberfeldt, AnnaEkblom, Tom

Search in DiVA

By author/editor
Syberfeldt, AnnaEkblom, Tom
By organisation
School of Engineering ScienceVirtual Engineering Research Environment
Production Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar
Total: 3 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 25 hits
CiteExportLink to record
Permanent link

Direct link
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