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research-article

PULLING AT THE DIGITAL THREAD: EXPLORING THE TOLERANCE STACK UP BETWEEN AUTOMATIC PROCEDURES AND EXPERT STRATEGIES IN SCAN TO PRINT PROCESSES

[+] Author and Article Information
Tobias Mahan

Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
tjm450@psu.edu

Nicholas Meisel

School of Engineering Design and Professional Programs, The Pennsylvania State University, University Park, PA, 16802, USA
nam20@psu.edu

Christopher McComb

School of Engineering Design and Professional Programs, The Pennsylvania State University, University Park, PA, 16802, USA
uum209@psu.edu

Jessica Menold

School of Engineering Design and Professional Programs, Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
Jdm5407@psu.edu

1Corresponding author.

ASME doi:10.1115/1.4041927 History: Received June 22, 2018; Revised October 29, 2018

Abstract

While the combination of 3D scanning and printing processes holds much promise for the field of new product development, problems with repeatability and accuracy have limited the wider spread adoption of some digital prototyping tools, such as 3D scanners. Studies have explored the errors inherent in higher fidelity scan to print (S2P) processes, yet few have explored the errors in S2P processes that leverage affordable rapid non-contact scanners. No studies have explored the strategies experienced designers in digital fabrication employ to mitigate errors. To address these gaps, a controlled study was conducted using data from 27 scans collected with a prototypical off-the-shelf non-contact optical scanner. The geometric and dimensional integrity of the digital models was found to be significantly out of tolerance at various phases of the S2P process, as compared to the original physical model. Larger errors were found more consistently in the data acquisition phase of the S2P process, but results indicate these errors were not sufficiently filtered out during the remainder of the process. A behavioral study was conducted with 13 experienced designers in digital fabrication to determine strategies for manually cleaning Point Clouds. Actions such as increase or decrease brush-size and select or de-select points were recorded. These actions were analyzed using hidden Markov modeling which revealed distinct patterns of behavior. Designer strategies were not beneficial and digital models produced by designers were found to be significantly smaller than original physical models.

Copyright (c) 2018 by ASME
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