133428 20260217205450.0 doi 10.3390/s24072380 sideral 138155 ART-2024-138155 eng Egaña, Fernando A Novel Methodology for Measuring Ambient Thermal Effects on Machine Tools 2024 Access copy available to the general public Unrestricted Large machine tools are critically affected by ambient temperature fluctuations, impacting their performance and the quality of machined products. Addressing the challenge of accurately measuring thermal effects on machine structures, this study introduces the Machine Tool Integrated Inverse Multilateration method. This method offers a precise approach for assessing geometric error parameters throughout a machine’s working volume, featuring a low level of uncertainty and high speed suitable for effective temperature change monitoring. A significant innovation is found in the capability to automatically realise the volumetric error characterisation of medium- to large-sized machine tools at intervals of 40–60 min with a measurement uncertainty of 10 µm. This enables the detailed study of thermal errors which are generated due to variations in ambient temperature over extended periods. To validate the method, an extensive experimental campaign was conducted on a ZAYER Arion G™ large machine tool using a LEICA AT960™ laser tracker with four wide-angle retro-reflectors under natural workshop conditions. This research identified two key thermal scenarios, quasi-stationary and changing environments, providing valuable insights into how temperature variations influence machine behaviour. This novel method facilitates the optimization of machine tool operations and the improvement of product quality in industrial environments, marking a significant advancement in manufacturing metrology. info:eu-repo/grantAgreement/EC/H2020/958357/EU/Interlinked Process, Product and Data Quality framework for Zero-Defects Manufacturing/InterQ This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 958357-InterQ info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 3.5 2024 CHEMISTRY, ANALYTICAL 38 / 111 = 0.342 2024 Q2 T2 INSTRUMENTS & INSTRUMENTATION 24 / 79 = 0.304 2024 Q2 T1 ENGINEERING, ELECTRICAL & ELECTRONIC 134 / 368 = 0.364 2024 Q2 T2 0.764 2024 Instrumentation 2024 Q1 Analytical Chemistry 2024 Q1 Medicine (miscellaneous) 2024 Q2 Information Systems 2024 Q2 Biochemistry 2024 Q2 Atomic and Molecular Physics, and Optics 2024 Q2 Electrical and Electronic Engineering 2024 Q2 8.2 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Mutilba, Unai Yagüe-Fabra, José A. Universidad de Zaragoza (orcid)0000-0001-7152-4117 Gomez-Acedo, Eneko 5002 515 Universidad de Zaragoza Dpto. Ingeniería Diseño Fabri. Área Ing. Procesos Fabricación 24, 7 (2024), 2380 [24 pp.] Sensors Sensors 1424-8220 4299584 http://zaguan.unizar.es/record/133428/files/texto_completo.pdf Versión publicada 2724085 http://zaguan.unizar.es/record/133428/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:133428 articulos driver 2026-02-17-20:18:46 ARTICLE