ASSESSING THE MANUFACTURABILITY OF STUDENTS’ EARLY-STAGE DESIGNS BASED ON PREVIOUS EXPERIENCE WITH TRADITIONAL MANUFACTURING AND ADDITIVE MANUFACTURING

Seth Pearl, Nicholas Meisel

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

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication48th Design Automation Conference (DAC)
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791886229
DOIs
StatePublished - 2022
EventASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022 - St. Louis, United States
Duration: Aug 14 2022Aug 17 2022

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume3-A

Conference

ConferenceASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022
Country/TerritoryUnited States
CitySt. Louis
Period8/14/228/17/22

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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