A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation

Olusayo Obajemu, Mahdi Mahfouf, Thomas E. McLeay, Xiang Jiang, Paul J. Scott, Visakan Kadirkamanathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Surface texture parameters are important indicators for understanding and controlling manufacturing processes. Deriving these parameters is however beset by ambiguities and uncertainties. The inclusion of confidence bands should provide valuable information on the reliability of the derived surface parameters. Existing methodologies of uncertainty modelling assume nonrandom interpolation functions, which do not adequately allow for the inclusion of interpolation uncertainties. This paper presents a new approach based on Gaussian processes, including a mechanism for the derivation and inclusion of such interpolation-based uncertainties when calculating surface texture parameters. The interpolation-based uncertainties are assumed to be independent of measurement uncertainties and as such, they can be independently modelled and propagated onto the derived parameters. When tested using real machining surface data, validation results show that the newly proposed technique has the advantage over the ISO-based approach of systematically characterising interpolation-based uncertainties in the form of confidence bands in the estimated profile parameters.

LanguageEnglish
Title of host publicationEuropean Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019
EditorsC. Nisbet, Richard K. Leach, D. Billington, D. Phillips
Publishereuspen
Pages520-523
Number of pages4
ISBN (Electronic)9780995775145
Publication statusPublished - 2019
Event19th International Conference of the European Society for Precision Engineering and Nanotechnology - Euskalduna, Bilbao, Spain
Duration: 3 Jun 20197 Jun 2019
Conference number: 19
https://www.euspen.eu/events/19th-ice-bilbao/

Conference

Conference19th International Conference of the European Society for Precision Engineering and Nanotechnology
Abbreviated titleEUSPEN 2019
CountrySpain
CityBilbao
Period3/06/197/06/19
Internet address

Fingerprint

Parameter estimation
metrology
interpolation
Interpolation
propagation
profiles
inclusions
confidence
textures
Textures
machining
ambiguity
Uncertainty
derivation
manufacturing
Machining
methodology

Cite this

Obajemu, O., Mahfouf, M., McLeay, T. E., Jiang, X., Scott, P. J., & Kadirkamanathan, V. (2019). A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation. In C. Nisbet, R. K. Leach, D. Billington, & D. Phillips (Eds.), European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019 (pp. 520-523). euspen.
Obajemu, Olusayo ; Mahfouf, Mahdi ; McLeay, Thomas E. ; Jiang, Xiang ; Scott, Paul J. ; Kadirkamanathan, Visakan. / A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation. European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019. editor / C. Nisbet ; Richard K. Leach ; D. Billington ; D. Phillips. euspen, 2019. pp. 520-523
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abstract = "Surface texture parameters are important indicators for understanding and controlling manufacturing processes. Deriving these parameters is however beset by ambiguities and uncertainties. The inclusion of confidence bands should provide valuable information on the reliability of the derived surface parameters. Existing methodologies of uncertainty modelling assume nonrandom interpolation functions, which do not adequately allow for the inclusion of interpolation uncertainties. This paper presents a new approach based on Gaussian processes, including a mechanism for the derivation and inclusion of such interpolation-based uncertainties when calculating surface texture parameters. The interpolation-based uncertainties are assumed to be independent of measurement uncertainties and as such, they can be independently modelled and propagated onto the derived parameters. When tested using real machining surface data, validation results show that the newly proposed technique has the advantage over the ISO-based approach of systematically characterising interpolation-based uncertainties in the form of confidence bands in the estimated profile parameters.",
keywords = "Kriging, Profile parameters, Surface metrology, Uncertainty",
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Obajemu, O, Mahfouf, M, McLeay, TE, Jiang, X, Scott, PJ & Kadirkamanathan, V 2019, A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation. in C Nisbet, RK Leach, D Billington & D Phillips (eds), European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019. euspen, pp. 520-523, 19th International Conference of the European Society for Precision Engineering and Nanotechnology, Bilbao, Spain, 3/06/19.

A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation. / Obajemu, Olusayo; Mahfouf, Mahdi; McLeay, Thomas E.; Jiang, Xiang; Scott, Paul J.; Kadirkamanathan, Visakan.

European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019. ed. / C. Nisbet; Richard K. Leach; D. Billington; D. Phillips. euspen, 2019. p. 520-523.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation

AU - Obajemu, Olusayo

AU - Mahfouf, Mahdi

AU - McLeay, Thomas E.

AU - Jiang, Xiang

AU - Scott, Paul J.

AU - Kadirkamanathan, Visakan

PY - 2019

Y1 - 2019

N2 - Surface texture parameters are important indicators for understanding and controlling manufacturing processes. Deriving these parameters is however beset by ambiguities and uncertainties. The inclusion of confidence bands should provide valuable information on the reliability of the derived surface parameters. Existing methodologies of uncertainty modelling assume nonrandom interpolation functions, which do not adequately allow for the inclusion of interpolation uncertainties. This paper presents a new approach based on Gaussian processes, including a mechanism for the derivation and inclusion of such interpolation-based uncertainties when calculating surface texture parameters. The interpolation-based uncertainties are assumed to be independent of measurement uncertainties and as such, they can be independently modelled and propagated onto the derived parameters. When tested using real machining surface data, validation results show that the newly proposed technique has the advantage over the ISO-based approach of systematically characterising interpolation-based uncertainties in the form of confidence bands in the estimated profile parameters.

AB - Surface texture parameters are important indicators for understanding and controlling manufacturing processes. Deriving these parameters is however beset by ambiguities and uncertainties. The inclusion of confidence bands should provide valuable information on the reliability of the derived surface parameters. Existing methodologies of uncertainty modelling assume nonrandom interpolation functions, which do not adequately allow for the inclusion of interpolation uncertainties. This paper presents a new approach based on Gaussian processes, including a mechanism for the derivation and inclusion of such interpolation-based uncertainties when calculating surface texture parameters. The interpolation-based uncertainties are assumed to be independent of measurement uncertainties and as such, they can be independently modelled and propagated onto the derived parameters. When tested using real machining surface data, validation results show that the newly proposed technique has the advantage over the ISO-based approach of systematically characterising interpolation-based uncertainties in the form of confidence bands in the estimated profile parameters.

KW - Kriging

KW - Profile parameters

KW - Surface metrology

KW - Uncertainty

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M3 - Conference contribution

SP - 520

EP - 523

BT - European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019

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Obajemu O, Mahfouf M, McLeay TE, Jiang X, Scott PJ, Kadirkamanathan V. A new Gaussian process-based approach for uncertainty propagation in surface metrology profile parameters estimation. In Nisbet C, Leach RK, Billington D, Phillips D, editors, European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 19th International Conference and Exhibition, EUSPEN 2019. euspen. 2019. p. 520-523