kth.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
Machine tool calibration: Measurement, modeling, and compensation of machine tool errors
Tohoku Univ, Sendai, Japan..ORCID iD: 0000-0001-9336-2729
Hiroshima Univ, Higashihiroshima, Japan..
Natl Inst Stand & Technol NIST, Gaithersburg, MD USA..
Kyoto Univ, Kyoto, Japan..
Show others and affiliations
2023 (English)In: International journal of machine tools & manufacture, ISSN 0890-6955, E-ISSN 1879-2170, Vol. 187, p. 104017-, article id 104017Article, review/survey (Refereed) Published
Abstract [en]

Advanced technologies for the calibration of machine tools are presented. Kinematic errors independently of their causes are classified into errors within one-axis as intra-axis errors, errors between axes as inter-axis errors, and as volumetric errors. As the major technological elements of machine tool calibration, the measurement methods, modeling theories, and compensation strategies of the machine tool errors are addressed. The criteria for selecting a combination of the technological elements for machine tool calibration from the point of view of accuracy, complexity, and cost are provided. Recent applications of artificial intelligence and machine learning in machine tool calibration are introduced. Remarks are also made on future trends in machine tool calibration.

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 187, p. 104017-, article id 104017
Keywords [en]
Machine tool, Calibration, Measurement, Uncertainty, Self -calibration, Machine learning
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-327389DOI: 10.1016/j.ijmachtools.2023.104017ISI: 000984847900001Scopus ID: 2-s2.0-85153572410OAI: oai:DiVA.org:kth-327389DiVA, id: diva2:1759685
Note

QC 20230526

Available from: 2023-05-26 Created: 2023-05-26 Last updated: 2023-05-26Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Szipka, KárolyArchenti, Andreas

Search in DiVA

By author/editor
Gao, WeiSzipka, KárolyArchenti, Andreas
By organisation
School of Industrial Engineering and Management (ITM)
In the same journal
International journal of machine tools & manufacture
Production Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 133 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