[en] Machining is one of the most widely employed manufacturing operations, contributing from 3 to 10% of GDP in developed countries. Despite this prevalence, tools and cutting conditions are often chosen on a trial-and-error basis which is costly and time consuming. In recent years, predictive models have emerged as one of the most promising approaches to address this issue. To function correctly however, predictive models require accurate data related to appropriate material properties (e.g., constitutive models, damage law). Thermomechanical tests are usually not representative of the extreme conditions found in machining processes and thus, the material laws obtained through these approaches might not accurately reflect real industrial processes. Inverse identification has the potential to address this problem, characterizing the material under real industrial conditions. However, acquiring information about workpiece temperature, strain or strain rate, remains a challenge. The present study, therefore, presents improved techniques to measure temperature, plastic strain and strain rate to be used as input in an inverse approach. These techniques were applied to the thermomechanical characterization and orthogonal machining of a Ti6Al4V alloy. This alloy is widely used because of its good mechanical properties and its ability to maintain them at elevated temperatures. However, it is also classified as a difficult-to-cut material, mainly due to the low thermal conductivity, its chemical reactivity and its hardness at high temperatures. As a first approach, thermomechanical tests were carried out to acquire a more indepth knowledge of the material behaviour and to set-up a methodology to measure (i) temperature with infrared filming, and (ii) plastic strain with Digital Image Correlation. In addition, a methodology to measure the adiabatic self-heating based on a thermodynamic analysis of a 3D volume was developed. Additionally, chip segmentation frequency was then used as an input in an inverse approach to optimize ductile failure law from orthogonal cutting tests. The prediction error was reduced from more than 100% to less than 10% in chip segmentation frequency predictions, while maintaining the accuracy in the other outcomes. Thermal measurements were carried out together with cutting forces, validating the ductile failure law proving that both workpiece temperature and cutting forces were in counter-phase. A novel grid distortion based methodology able to measure plastic strain in the shear zone under plane strain conditions was also developed and validated. This grid method can have significant application in industry, as it proved to be an appropriate technique to measure subsurface damage, providing accurate results and reducing measurement subjectivity. The method was applied to analyze the effect of inputs such as workpiece initial microstructure, tool radius, and tool coating.

[eu] Mekanizatua oso prozesu garrantzitsua da, horrek herrialde garatuetan barne produktu gordinaren %3-tik %10-era bitarteko tasak erakusten duenez. Hala ere, prozesuko ebaketabaldintza eta mekanizazio-erremintak ez dira sistematikoki aukeratzen, eta honek denboran eta kostuan galerak sortzen du. Karakterizazio termomekanikoen saiakuntzetan mekanizatuan bezalako muturreko baldintzak lortzen ez direnez, lortutako isurpen legeak ez dira mekanizatu prozesuen adierazgarri. Alderantzizko simulazioa irtenbide posible bat izan liteke baina enperatura, deformazioa eta deformazio abiaduraren neurketak burutzea erronka izaten jarraitzen ditu. Tesi honetan tenperatura, deformazio eta deformazio abiaduraren neurketak egiteko metodo berriak aurkezten dira, alderantzizko simulazioetan sarrera parametro gisa erabiltzeko. Azaltzen diren metodoak karakterizazio termomekaniko eta Ti6Al4V aleazioen ebaketa ortogonalean aplikatu ziren. Material hori oso erabilia da dituen ezaugarri mekanikoengatik -erresistentzia espezifiko altua, zurruntasuna, gogortasuna eta neke eta korrosioarekiko duen erresistentziagatik- eta gainera ezaugarri horiek tenperatura altuetan mantentzen dituelako. Hala ere, mekanizatzeko aleazio zaila da, txirbil segmentatua sortzen duelako. Mekanizatzen hasi aurretik, karakterizazio termomekanikoa burutu zen, materialaren portaeraren ezagutza handiagoa izateko eta neurketa metodologiak baieztatzeko. Tenperatura neurtzeko filmazio infragorria erabili zen, eta deformazioa irudi digitalen korrelazioarekin. Gainera, barne-beroketa adiabatikoa (adiabatic self-heating) neurtzeko 3Dn egindako analisi termodinamikoan oinarritutako metodologia bat aurkezten da. Mekanizatuan, ebaketa ortogonalen baldintzetan tenperatura neurketak egin ziren. Horiekin harikortasun irizpidea egiaztatu zen. Alderantzizko simulazioaren bidez txirbilaren segmentazio maiztasuna sarrera moduan erabili zen aipatutako irizpidea ptimizatzeko. Txirbilaren segmentazio maiztasunaren iragarpenean errorea murriztu zen, %100 baino handiagoa izatetik %10 baino txikiagoa izatera igaroz, gainerako irteera aldagaien zehaztasuna mantenduz. Ebaketa eremuan deformazio plastikoak neurtzeko sare mekanizatuen distortsioan oinarritutako metodo berri bat garatu da. Metodo horrek aplikazio garrantzitsua izan dezake industrian, gainazal azpiko kaltea neurtzeko baliagarria zela frogatu baitzen, lortutako balioak zehatzak zirelako subjektibotasuna murriztuz. Metodo hori piezaren hasierako mikroegitura, erremintaren erradio eta estaldura efektuaren analisia egiteko erabili zen.