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research-article

The Design for Additive Manufacturing Worksheet

[+] Author and Article Information
Joran W. Booth

School of Mechanical Engineering
boothj@purdue.edu

Jeffrey Alperovich

School of Mechanical Engineering
jalper@purdue.edu

Pratik Chawla

School of Mechanical Engineering
chawla0@purdue.edu

Jiayan Ma

School of Mechanical Engineering
ma247@purdue.edu

Tahira Reid

School of Mechanical Engineering
tahira@purdue.edu

Karthik Ramani

School of Electrical & Computer Engineering (by courtesy), Purdue University, West Lafayette, IN 47907, USA; School of Mechanical Engineering
ramani@purdue.edu

1Corresponding author.

ASME doi:10.1115/1.4037251 History: Received January 31, 2017; Revised May 02, 2017

Abstract

Additive manufacturing (AM) technologies have become integral to modern prototyping and manufacturing. Therefore, guidelines for using AM are necessary to help users new to the technology. Many others have proposed useful guidelines, but these are rarely written in a way that is accessible to novice users. Most guidelines 1) assume the user has extensive prior knowledge of the process, 2) apply to only a few AM technologies or a very specific application, or 3) describe benefits of the technology that novices already know. In this paper, we present a 1-page, visual design-for-additive-manufacturing worksheet for novice and intermittent users which addresses common mistakes as identified by various expert machinists and additive manufacturing facilities who have worked extensively with novices. The worksheet helps designers assess the potential quality of a part made using AM and indirectly suggests ways to redesign it. The immediate benefit of the worksheet is to filter out bad designs before they are printed, thus saving time on manufacturing and redesign. We implemented this as a go-no-go test for a high-volume AM facility where users are predominantly novices, and we observed an 81% decrease in the rate of poorly designed parts. We also tested the worksheet in a classroom, but found no difference between the control and the experimental groups. This result highlights the importance of motivation since the cost of using AM in this context was dramatically lower than real-world costs. This second result highlights the limitations of the worksheet.

Copyright (c) 2017 by ASME
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