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dc.contributor.authorUrbicain Pelayo, Gorka ORCID
dc.contributor.authorOlvera Trejo, Daniel
dc.contributor.authorLuo, M.
dc.contributor.authorTang, K.
dc.contributor.authorLópez de Lacalle Marcaide, Luis Norberto
dc.contributor.authorElías Zuñiga, Alex
dc.date.accessioned2021-12-16T08:55:48Z
dc.date.available2021-12-16T08:55:48Z
dc.date.issued2021
dc.identifier.citationMeasurement 186 : (2021) // Article ID 110120es_ES
dc.identifier.issn0263-2241
dc.identifier.issn1873-412X
dc.identifier.urihttp://hdl.handle.net/10810/54516
dc.description.abstract[EN]There is a need in manufacturing as in machining of being more productive. However, at the same time, workshops are also urged for lesser energy waste in cutting operations. Specially, rough milling of impellers and bladed integrated disks of aircraft engines need an efficient use of energy due to the long cycle times. Indeed, to avoid dramatic tool failures and idle times, cutting conditions and operations tend to be very conservative. This is a multivariable problem, where process engineers need to handle several aspects such as milling operation type, toolpath strategies, cutting conditions, or clamping systems. There is no criterion embracing productivity and power consumption. In this sense, this work proposes a methodology that meets productivity and sustainability by using a specific cutting energy or sustainable productivity gain (SPG) factor. Three rough milling operations-slot, plunge nad trochoidal milling-were modelled and verified. A bottom-up approach based on data from developed mechanistic force models evaluated and compared different alternatives for making a slot, which is a common operation in that king of workpieces. Experimental data confirmed that serrated end milling with the highest SPG value of 1 is the best milling operation in terms of power consumption and mass removal rate (MRR). In the case of plunge milling technique achieve an SPG < 0.51 while trochoidal milling produces a very low SPG value.es_ES
dc.description.sponsorshipThe authors acknowledge the support from the Spanish Government (JANO, CIEN Project, 2019.0760) and Basque Government (ELKARTEK19/46, KK-2019/00004). This research was funded by Tecnologico de Monterrey through the Research Group of Nanotechnology for Devices Design, and by the Consejo Nacional de Ciencia y Tecnologia de Mexico (Conacyt), Project Number 296176, and National Lab in Additive Manufacturing, 3D Digitizing and Computed Tomography (MADiT) LN299129. The authors also acknowledge the support from Garikoitz Goikoetxea and fruitful discussions with Mr. Jon Mendez (Guhring (c)) and Endika Monge (Hoffmann Group (c)).es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectproductivityes_ES
dc.subjectsustainabilityes_ES
dc.subjectrough millinges_ES
dc.subjectpower consumptiones_ES
dc.subjectforce modelses_ES
dc.titleA model-based sustainable productivity concept for the best decision-making in rough milling operationses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder2021 The Author(s). This is an open access article under the CC BY licensees_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S026322412101040X?via%3Dihubes_ES
dc.identifier.doi10.1016/j.measurement.2021.110120
dc.departamentoesIngeniería mecánicaes_ES
dc.departamentoeuIngeniaritza mekanikoaes_ES


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2021 The Author(s). This is an open access article under the CC BY license
Except where otherwise noted, this item's license is described as 2021 The Author(s). This is an open access article under the CC BY license