Net-shape tensile specimens as representatives of material properties of metal additive manufacturing: Evaluation and correction factor

Nicholas Bass, Sagar Jalui, Guha Manogharan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Tensile testing is the most prevalent method for characterizing the mechanical properties of additively manufactured (AM) materials. During qualification of metallic AM properties, near-net AM parts are often machined prior to mechanical testing. The aim of this study is to understand the influence of net-shaped tensile coupons without post-AM machining on the accuracy of bulk material properties. The motivation for this study lies in: (1) reducing the qualification time and costs by (2) formulating and validating a correction factor to estimate bulk AM properties from mechanical testing of as-AM coupons. This research focused on the tensile testing of Laser Powder Bed Fusion (LPBF) produced Inconel 718 to isolate the effects of as-AM surface roughness. Six different surface conditions were produced by varying two different laser processing conditions, with and without contour laser scans. Specimens (n=5 per condition) were tested in both net-shape and post-AM machined conditions. Surface roughness was analyzed using both stylus contact profilometry and micro-computed tomography (micro-CT) non-contact analysis. ANOVA analysis was performed to derive inference on processing conditions and resulting mechanical properties. It was observed that the measurement error in gauge diameter primarily accounts for variability in mechanical properties between machined and netshape coupons, specifically Ultimate Tensile Strength (UTS). This study presents a methodology to determine corrected gauge diameter based on depth of surface roughness. Findings from this study will enable net-shape tensile data to be compared against machined data for accurately predicting the strength of parts with as-AM surfaces. By accounting for surface roughness depth, tensile strength of net-shape AM coupons was within 1% accuracy to that of machined AM coupons.

Original languageEnglish (US)
Title of host publicationManufacturing Processes; Manufacturing Systems
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791885819
DOIs
StatePublished - 2022
EventASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022 - West Lafayette, United States
Duration: Jun 27 2022Jul 1 2022

Publication series

NameProceedings of ASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022
Volume2

Conference

ConferenceASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022
Country/TerritoryUnited States
CityWest Lafayette
Period6/27/227/1/22

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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