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Measurement uncertainty associated with the performance of machine tool under quasi-static loaded test condition
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)ORCID iD: 0000-0002-6989-2989
KTH, School of Industrial Engineering and Management (ITM), Production Engineering. (Manufacturing and Metrology Systems)ORCID iD: 0000-0001-9185-4607
2017 (English)In: Laser Metrology and Machine Performance XII / [ed] L. Blunt & W. Knapp, Renishaw Innovation Centre, UK, 2017Conference paper, Published paper (Refereed)
Abstract [en]

For proper characterisation of different physical quantities in machine tools, it is necessary to report the uncertainties associated to the measurements. The uncertainty evaluation, according to international standards, expresses information of the quality and the reliability of the measurement result. Applications like calibration and compensation are sensitive for the quality of the input data, thus the reliability of the characterisation results need to be interpreted accurately to avoid significant residual errors or overcompensation. General approaches take several factors into consideration during the estimation of measurement uncertainty such as the environmental variations or the uncertainties of the measurement device or the setup. At the same time, various reproducible and non-reproducible error sources associated to the performance testing of the machine tool are ignored. The reason behind it can be the lack of the applicable standardized measurement instruments.

This paper highlights the significance of the uncertainty sources connected to the performance of the machine tool under quasi-static loaded condition. The variation of the static stiffness of machine tools, the hysteresis and play in the system can be even more significant uncertainty sources than the above mentioned ones. Under the framework of elastically linked systems (ELS), a circular test device, the loaded double ball bar (LDBB), is used in a case study to identify this effect. The LDBB can be used as a double ball bar, with the additional capability of applying a load, thus it enables the measurement of machine tool deviations under quasi-static loaded conditions. A measurement methodology is proposed to properly describe and demonstrate the variation of the contributing uncertainties associated with repeatability performance of the machine tool. With this approach important interdependencies can be expressed as uncertainty sources.

Place, publisher, year, edition, pages
Renishaw Innovation Centre, UK, 2017.
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
SRA - Production
Identifiers
URN: urn:nbn:se:kth:diva-203967OAI: oai:DiVA.org:kth-203967DiVA, id: diva2:1083419
Conference
Lamdamap 12th International Conference & Exhibition,15th-16th March 2017, Renishaw Innovation Centre, UK
Funder
XPRES - Initiative for excellence in production research
Note

QC 20170322

Available from: 2017-03-21 Created: 2017-03-21 Last updated: 2018-10-15Bibliographically approved
In thesis
1. Modelling and Management of Uncertainty in Production Systems: from Measurement to Decision
Open this publication in new window or tab >>Modelling and Management of Uncertainty in Production Systems: from Measurement to Decision
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The advanced handling of uncertainties arising from a wide range of sources is fundamental in quality control and dependability to reach advantageous decisions in different organizational levels of industry. Es-pecially in the competitive edge of production, uncertainty shall not be solely object of estimation but the result of a systematic management process. In this process, the composition and utilization of proper in-formation acquisition systems, capability models and propagation tools play an inevitable role. This thesis presents solutions from production system to operational level, following principles of the introduced con-cept of uncertainty-based thinking in production. The overall aim is to support transparency, predictability and reliability of production sys-tems, by taking advantage of expressed technical uncertainties. On a higher system level, the management of uncertainty in the quality con-trol of industrial processes is discussed. The target is the selection of the optimal level of uncertainty in production processes integrated with measuring systems. On an operational level, a model-based solution is introduced using homogeneous transformation matrices in combination with Monte Carlo method to represent uncertainty related to machin-ing system capability. Measurement information on machining systems can significantly support decision-making to draw conclusions on man-ufactured parts accuracy, by developing understanding of root-causes of quality loss and providing optimization aspects for process planning and maintenance.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 60
Series
TRITA-ITM-AVL ; 2018:37
Keywords
Precision engineering, Uncertainty modelling, Machin-ing system capability
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-235825 (URN)978-91-7729-846-5 (ISBN)
Presentation
2018-11-09, M311, Kungliga Tekniska högskolan, Brinellvagen 68, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
XPRES - Initiative for excellence in production research
Note

QC 20181015

Available from: 2018-10-15 Created: 2018-10-06 Last updated: 2018-10-16Bibliographically approved

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