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Special Issue paper

The Design for Additive Manufacturing Worksheet

[+] Author and Article Information
Joran W. Booth

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: boothj@purdue.edu

Jeffrey Alperovich, Pratik Chawla, Jiayan Ma, Tahira N. Reid

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907

Karthik Ramani

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907;
School of Electrical and Computer Engineering,
Purdue University,
West Lafayette, IN 47907

1Corresponding author.

Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 31, 2017; final manuscript received May 2, 2017; published online August 30, 2017. Assoc. Editor: Carolyn Seepersad.

J. Mech. Des 139(10), 100904 (Aug 30, 2017) (9 pages) Paper No: MD-17-1084; doi: 10.1115/1.4037251 History: Received January 31, 2017; Revised May 02, 2017

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 one-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 most AM processes 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.

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Figures

Grahic Jump Location
Fig. 1

The DfAM worksheet is designed for novices and intermittent users of additive manufacturing technologies

Grahic Jump Location
Fig. 2

Examples of prints created after students used the DfAM worksheet. A lower score rates better on the worksheet. The bottom right image is of a cartoon robot head. Score = 24, score = 22, score = 19, score = 16, score = 15, and score = 11.

Grahic Jump Location
Fig. 3

Examples of parts from the second study. (a) and (b) One of only three examples of any changes made. The other two examples show no change from pre to post. All the three changes we observed were unrelated to improving the manufacturability: (a) initial part, (c) initial part, (e) initial part, (b) final part, (d) final part, and (f) final part.

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