000121403 001__ 121403
000121403 005__ 20241125101127.0
000121403 0247_ $$2doi$$a10.1016/j.measurement.2023.112469
000121403 0248_ $$2sideral$$a131915
000121403 037__ $$aART-2023-131915
000121403 041__ $$aeng
000121403 100__ $$0(orcid)0000-0003-3823-7903$$aDíaz-Pérez, L.C.$$uUniversidad de Zaragoza
000121403 245__ $$aUncertainty budget of a large-range nanopositioning platform based on Monte Carlo simulation
000121403 260__ $$c2023
000121403 5060_ $$aAccess copy available to the general public$$fUnrestricted
000121403 5203_ $$aThe objective of precision systems design is to obtain machines with very high and totally predictable work-zone accuracies. In already functional systems, where the errors can be measured, this is achieved by error correction and compensation. The aim of this work is to propose an uncertainty budget methodology to obtain the final measuring uncertainty of precise measuring systems, after error compensation. The case study is a nanopositioning platform, referred as NanoPla, with a confocal sensor integrated as measuring instrument. The NanoPla performs precise positioning in a large range of 50 mm × 50 mm, and its target is surface topography characterization, at a submicrometre scale. After performing the uncertainty budget of the NanoPla, Monte Carlo method is used to obtain the final measuring uncertainty along the whole NanoPla working range, considering all the casuistry. By studying the results, the authors are able to propose solutions to minimize the final measuring uncertainty.
000121403 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T56-20R$$9info:eu-repo/grantAgreement/ES/MICINN/RTI2018-097191-B-I00
000121403 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000121403 590__ $$a5.2$$b2023
000121403 592__ $$a1.181$$b2023
000121403 591__ $$aENGINEERING, MULTIDISCIPLINARY$$b17 / 181 = 0.094$$c2023$$dQ1$$eT1
000121403 591__ $$aINSTRUMENTS & INSTRUMENTATION$$b11 / 76 = 0.145$$c2023$$dQ1$$eT1
000121403 593__ $$aApplied Mathematics$$c2023$$dQ1
000121403 593__ $$aEducation$$c2023$$dQ1
000121403 593__ $$aStatistics and Probability$$c2023$$dQ1
000121403 593__ $$aCondensed Matter Physics$$c2023$$dQ1
000121403 593__ $$aInstrumentation$$c2023$$dQ1
000121403 593__ $$aElectrical and Electronic Engineering$$c2023$$dQ1
000121403 594__ $$a10.2$$b2023
000121403 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000121403 700__ $$0(orcid)0000-0002-3069-2736$$aTorralba, M.
000121403 700__ $$aMuro, L.
000121403 700__ $$0(orcid)0000-0003-4839-0610$$aAlbajez, J.A.$$uUniversidad de Zaragoza
000121403 700__ $$0(orcid)0000-0001-7152-4117$$aYagüe-Fabra, J.A.$$uUniversidad de Zaragoza
000121403 7102_ $$15002$$2515$$aUniversidad de Zaragoza$$bDpto. Ingeniería Diseño Fabri.$$cÁrea Ing. Procesos Fabricación
000121403 773__ $$g28, 112469 (2023), [15 pp.]$$pMeasurement$$tMEASUREMENT$$x0263-2241
000121403 8564_ $$s5749620$$uhttps://zaguan.unizar.es/record/121403/files/texto_completo.pdf$$yVersión publicada
000121403 8564_ $$s2500310$$uhttps://zaguan.unizar.es/record/121403/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000121403 909CO $$ooai:zaguan.unizar.es:121403$$particulos$$pdriver
000121403 951__ $$a2024-11-22-11:57:56
000121403 980__ $$aARTICLE