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Predictive models on the influence of laser texturing parameters on the Inconel 718 surface by using Nd: YVO4 laser

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Summary:This work presents a detailed study on Inconel 718 alloy surface texturing by a Nd: YVO4 fibre laser aiming to create localized textured areas for further introduction of reinforcement materials for improvin relevant properties such as thermal conductivity (copper alloys), lightweight (aluminium alloys) or avoid chemical oxidizing reactions (stainless steel alloys).Various laser parameters - there are laser power (P), scan speed (S) and number of passes (N) - and different line spacing (D) were combined. The characterization of the textured surfaces was carried out by scanning electron microscopy (SEM) and analyzed using image analysis software (Image J) to measure the depth and width of the grooves. The textured Inconel 718 specimens were etched to analyze the effect of the laser interaction with the grain morphology. The influence of laser parameters on the grain morphology was assessed by using statistical analysis. In order to find the significant main factors and their interactions an analysis of variance (ANOVA) was used.Results show high-quality textured surfaces are obtained by using low power values and medium scan speed values and remelting areas are produced when considering a low number of passes. Moreover, the grain size is larger when considering high power values when compared with non-textured areas. The mathematical models demonstrated that laser power, scan speed and number of passes affect the depth and width of the grooves. According to its significance, the power (P) is the variable that most affects width of the grooves and the number of passes (N) is the significant variable that most influences the depth variable.
Main Authors:Marques, Ana Cristina Ribeiro
Other Authors:Cunha, Ângela Sofia Varela; Faria, Susana; Silva, Filipe Samuel; Carvalho, Óscar Samuel Novais
Subject:Inconel 718 Laser surface modification Texturing Nd: YVO4 laser Statistical analysis Nd: YVO laser 4
Year:2022
Country:Portugal
Document type:article
Access type:restricted access
Associated institution:Universidade do Minho
Language:English
Origin:RepositóriUM - Universidade do Minho

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