000266611 001__ 266611
000266611 005__ 20190625174541.0
000266611 022__ $$a0268-3768
000266611 022__ $$a1433-3015
000266611 02470 $$a000463240400011$$2isi
000266611 0247_ $$a10.1007/s00170-018-3033-3$$2doi
000266611 037__ $$aARTICLE
000266611 245__ $$a3D laser shock peening as a way to improve geometrical accuracy in selective laser melting
000266611 260__ $$c2019$$aLondon$$bSPRINGER LONDON LTD
000266611 269__ $$a2019-04-01
000266611 336__ $$aJournal Articles
000266611 520__ $$aOne of the major drawbacks of selective laser melting (SLM) is the accumulation of tensile residual stresses (TRS) in the surface and subsurface zones of produced parts which can lead to cracking, delamination, geometrical distortions, and a decrease in fatigue life. 3D laser shock peening (3D LSP) is a novel hybrid method which introduces a repetitive LSP treatment during the manufacturing phase of the SLM process. In this paper, the ability of 3D LSP to convert TRS into beneficial compressive residual stresses and their subsequent effect on the geometrical accuracy of produced parts were investigated. Samples made of Ti6Al4V were manufactured with the 3D LSP process and treated with different processing parameters. Cuboidal samples were used for residual stress measurements, and the evolution of residual stresses was evaluated. Geometrical distortions were measured on bridge-like samples, and the influence on the final sample geometry was quantified. A significant improvement in geometrical accuracy resulting from reduced distortions was observed in all selected 3D LSP processing conditions.
000266611 650__ $$aAutomation & Control Systems
000266611 650__ $$aEngineering, Manufacturing
000266611 650__ $$aAutomation & Control Systems
000266611 650__ $$aEngineering
000266611 6531_ $$a3d laser shock peening
000266611 6531_ $$aselective laser melting
000266611 6531_ $$alaser shock peening
000266611 6531_ $$adistortion
000266611 6531_ $$ageometrical accuracy
000266611 6531_ $$ati6al4v
000266611 6531_ $$aresidual-stress
000266611 6531_ $$amechanical-properties
000266611 6531_ $$afatigue life
000266611 6531_ $$adistortion
000266611 6531_ $$aprediction
000266611 6531_ $$aalloy
000266611 6531_ $$aparts
000266611 700__ $$aKalentics, Nikola$$0248802$$g252434
000266611 700__ $$aBurn, Andreas
000266611 700__ $$aCloots, Michael
000266611 700__ $$aLoge, Roland E.$$0248074$$g243441
000266611 773__ $$k5-8$$j101$$q1247-1254$$tInternational Journal Of Advanced Manufacturing Technology
000266611 8560_ $$fcyril.cayron@epfl.ch
000266611 909C0 $$zMarselli, Béatrice$$0252516$$yApproved$$pLMTM$$xU12903$$mcyril.cayron@epfl.ch
000266611 909CO $$particle$$ooai:infoscience.epfl.ch:266611$$pSTI
000266611 961__ $$apierre.devaud@epfl.ch
000266611 973__ $$aEPFL$$sPUBLISHED$$rREVIEWED
000266611 980__ $$aARTICLE
000266611 980__ $$aWoS
000266611 981__ $$aoverwrite