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dc.contributor.authorPombo Rodilla, Iñigo
dc.contributor.authorGodino Fernández, Leire
dc.contributor.authorSánchez Galíndez, José Antonio ORCID
dc.contributor.authorLizarralde, Rafael
dc.date.accessioned2020-10-07T10:17:08Z
dc.date.available2020-10-07T10:17:08Z
dc.date.issued2020-09-22
dc.identifier.citationFuture Internet 1 (9) : (2020) // Article ID 159es_ES
dc.identifier.issn1999-5903
dc.identifier.urihttp://hdl.handle.net/10810/46602
dc.description.abstractGrinding is a critical technology in the manufacturing of high added-value precision parts, accounting for approximately 20–25% of all machining costs in the industrialized world. It is a commonly used process in the finishing of parts in numerous key industrial sectors such as transport (including the aeronautical, automotive and railway industries), and energy or biomedical industries. As in the case of many other manufacturing technologies, grinding relies heavily on the experience and knowledge of the operatives. For this reason, considerable efforts have been devoted to generating a systematic and sustainable approach that reduces and eventually eliminates costly trial-and-error strategies. The main contribution of this work is that, for the first time, a complete digital twin (DT) for the grinding industry is presented. The required flow of information between numerical simulations, advanced mechanical testing and industrial practice has been defined, thus producing a virtual mirror of the real process. The structure of the DT comprises four layers, which integrate: (1) scientific knowledge of the process (advanced process modeling and numerical simulation); (2) characterization of materials through specialized mechanical testing; (3) advanced sensing techniques, to provide feedback for process models; and (4) knowledge integration in a configurable open-source industrial tool. To this end, intensive collaboration between all the involved agents (from university to industry) is essential. One of the most remarkable results is the development of new and more realistic models for predicting wheel wear, which currently can only be known in industry through costly trial-and-error strategies. Also, current work is focused on the development of an intelligent grinding wheel, which will provide on-line information about process variables such as temperature and forces. This is a critical issue in the advance towards a zero-defect grinding process.es_ES
dc.description.sponsorshipThe authors gratefully acknowledge the funding support received from the Spanish Ministry of Economy and Competitiveness and the FEDER operation program for funding the project “Scientific models and machine-tool advanced sensing techniques for efficient machining of precision components of Low-Pressure Turbines” (DPI2017-82239-P).es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/DPI2017-82239-Pes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectcyber-physical systemses_ES
dc.subjectdigital twines_ES
dc.subjectadvanced manufacturinges_ES
dc.subjectgrinding processes_ES
dc.subjectgrinding wheeles_ES
dc.titleExpectations and limitations of Cyber-Physical Systems (CPS) for Advanced Manufacturing: A View from the Grinding Industryes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2020-09-25T13:28:53Z
dc.rights.holder2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/1999-5903/12/9/159es_ES
dc.identifier.doi10.3390/fi12090159
dc.departamentoesIngeniería mecánica
dc.departamentoeuIngeniaritza mekanikoa


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2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).