TY - GEN
T1 - Net-shape tensile specimens as representatives of material properties of metal additive manufacturing
T2 - ASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022
AU - Bass, Nicholas
AU - Jalui, Sagar
AU - Manogharan, Guha
N1 - Publisher Copyright:
© Proceedings of ASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85140984210&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85140984210&partnerID=8YFLogxK
U2 - 10.1115/MSEC2022-85310
DO - 10.1115/MSEC2022-85310
M3 - Conference contribution
AN - SCOPUS:85140984210
T3 - Proceedings of ASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022
BT - Manufacturing Processes; Manufacturing Systems
PB - American Society of Mechanical Engineers
Y2 - 27 June 2022 through 1 July 2022
ER -