TY - GEN
T1 - ASSESSING THE MANUFACTURABILITY OF STUDENTS’ EARLY-STAGE DESIGNS BASED ON PREVIOUS EXPERIENCE WITH TRADITIONAL MANUFACTURING AND ADDITIVE MANUFACTURING
AU - Pearl, Seth
AU - Meisel, Nicholas
N1 - Funding Information:
This research was conducted through the support of the National Science Foundation under Grant No. 2042917. Any opinions, findings, and conclusions expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF. We would also like to thank Dr. Randall Bock and Dr. Jason Moore for allowing us to conduct the experiment in their respective classes. Lastly, we would like to thank Jayant Mathur for helping with the statistics calculations.
Publisher Copyright:
Copyright © 2022 by ASME.
PY - 2022
Y1 - 2022
N2 - As additive manufacturing (AM) becomes more mainstream in industry, the newer design for additive manufacturing (DfAM) considerations must be distinguished from the older design for traditional manufacturing (DfTM) considerations. Designers who wish to maximize additive manufacturing’s potential must reconsider the traditional manufacturing axioms they may be more familiar with. While research has previously investigated the potential influences that can affect the designs produced in concept generation, little research has been done explicitly targeting the manufacturability of early-stage concepts and how previous experience in manufacturing affects this. The research in this paper addresses this gap in knowledge, specifically targeting differences in concept generation due to designer experience with additive manufacturing and traditional manufacturing. In this study, participants were given priming content on DfTM and DfAM considerations and then asked to complete a design challenge centered on concept generation. The participants’ final designs were evaluated for manufacturability as suited for traditional and additive manufacturing. Results show that students with low manufacturing experience levels create designs that are more naturally suited for traditional manufacturing. Additionally, as designers’ manufacturing experience levels increase, there is an increase in the number of designs suited for additive manufacturing. This correlates with a higher self-reported use of DfAM axioms in the evaluation of these designs. These results suggests that students with high manufacturing experience levels make a subconscious decision for which manufacturing process to design for.
AB - As additive manufacturing (AM) becomes more mainstream in industry, the newer design for additive manufacturing (DfAM) considerations must be distinguished from the older design for traditional manufacturing (DfTM) considerations. Designers who wish to maximize additive manufacturing’s potential must reconsider the traditional manufacturing axioms they may be more familiar with. While research has previously investigated the potential influences that can affect the designs produced in concept generation, little research has been done explicitly targeting the manufacturability of early-stage concepts and how previous experience in manufacturing affects this. The research in this paper addresses this gap in knowledge, specifically targeting differences in concept generation due to designer experience with additive manufacturing and traditional manufacturing. In this study, participants were given priming content on DfTM and DfAM considerations and then asked to complete a design challenge centered on concept generation. The participants’ final designs were evaluated for manufacturability as suited for traditional and additive manufacturing. Results show that students with low manufacturing experience levels create designs that are more naturally suited for traditional manufacturing. Additionally, as designers’ manufacturing experience levels increase, there is an increase in the number of designs suited for additive manufacturing. This correlates with a higher self-reported use of DfAM axioms in the evaluation of these designs. These results suggests that students with high manufacturing experience levels make a subconscious decision for which manufacturing process to design for.
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U2 - 10.1115/DETC2022-91101
DO - 10.1115/DETC2022-91101
M3 - Conference contribution
AN - SCOPUS:85142499504
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 48th Design Automation Conference (DAC)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022
Y2 - 14 August 2022 through 17 August 2022
ER -