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Utilization of machine tool repeatability in kinematic modelling
KTH, School of Industrial Engineering and Management (ITM), Production Engineering. (Manufacturing and Metrology Systems)ORCID iD: 0000-0003-0045-2085
KTH, School of Industrial Engineering and Management (ITM), Production Engineering. (Manufacturing and Metrology Systems)
2017 (English)In: Conference proceedings euspen’s 17th International Conference & Exhibition, 2017Conference paper, (Refereed)
Abstract [en]

Modelling of non-systematic variations in the positioning performance of machine tools can support the understanding of capability variation in manufacturing processes. Kinematic characterisation is implemented through repeated measurements, which include variations connected to the performance of the machine tool. This paper addresses the integration of the positional repeatability to kinematic modelling through the utilization of direct measurement results. The statistical population of random errors along the single-axis travel first requires the proper management of experimental data. In this paper a methodology is presented for the determination of repeatability under static and unloaded conditions as an inhomogeneous parameter in the workspace. In a case study the component errors of a linear axis were investigated with repeated laser interferometer measurements to quantify the estimated repeatability and express it in the composed repeatability budget. The conclusions of the proposed methodology outline the sensitivity of kinematic models relying on measurement data, as the repeatability of the system can be in the same magnitude as systematic errors.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Machine tool repeatability, Uncertainty estimation, Kinematic modelling
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
SRA - Production
Identifiers
URN: urn:nbn:se:kth:diva-210652OAI: oai:DiVA.org:kth-210652DiVA: diva2:1119132
Conference
euspen’s 17th International Conference & Exhibition, Hannover, Germany, 29th May – 2nd June 2017
Funder
XPRES - Initiative for excellence in production research
Note

QC 20170703

Available from: 2017-07-03 Created: 2017-07-03 Last updated: 2017-07-03Bibliographically approved

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  • apa
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Output format
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