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Research Papers: Design for Manufacture and the Life Cycle

Design for Manufacturability-Based Feedback to Mitigate Design Fixation

[+] Author and Article Information
Esraa S. Abdelall

Department of Industrial and Manufacturing
System Engineering,
Iowa State University,
3004 Black Engineering 2529 Union Drive,
Ames, IA 50011
e-mail: abdelallesra@gmail.com

Matthew C. Frank

Department of Industrial and Manufacturing
System Engineering,
Iowa State University,
3004 Black Engineering 2529 Union Drive,
Ames, IA 50011
e-mail: mfrank@iastate.edu

Richard T. Stone

Department of Industrial and Manufacturing
System Engineering,
Iowa State University,
3004 Black Engineering 2529 Union Drive,
Ames, IA 50011
e-mail: rstone@iastate.edu

Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received December 7, 2017; final manuscript received May 20, 2018; published online June 22, 2018. Assoc. Editor: Paul Witherell.

J. Mech. Des 140(9), 091701 (Jun 22, 2018) (9 pages) Paper No: MD-17-1813; doi: 10.1115/1.4040424 History: Received December 07, 2017; Revised May 20, 2018

This study assessed the effectiveness of three-dimensional (3D) visual feedback from design for manufacturability (DFM) software on mitigating design fixation on nonproducible manufacturability features. A fixation group and a defixation group were asked to design a basic product for additive manufacturing (AM) and then to modify the next iteration for conventional machining. The fixation group relied on their self-assessment while modifying, while the defixation group utilized dfm software feedback. Results showed that 3D feedback reduced design fixation on nonproducible features and improved the machinability of modified designs. Findings suggest the use of dfm software for treating the design fixation related to AM and for facilitating migration of designs from additive to conventional manufacturing. This work could be applied to manufacturing industries, particularly where AM is used for prototyping, or when demand for part changes and an AM part needs to migrate to conventional methods.

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Figures

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Fig. 2

Example of ANA output (a) visibility, (b) reachability, (c) accessibility, and (d) setup complexity

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Fig. 1

(a) Opener for Arthritis showing designer fixation on nonproducible features, part designed for AM and (b) same part modified for conventional processes, mainly casting and machining

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Fig. 3

Example of jars opener (Photo courtesy of The Container Store, used with permission)

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Fig. 4

Sample of dfm software 3D visual feedback

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Fig. 5

Mean number of nonproducible features in designs created by both groups during first and second design iteration. Error bar represents ±1 standard error.

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Fig. 6

Fixation percentage on nonproducible features for both groups. Error bar represents ±1 standard error.

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Fig. 7

Average ANA machinability score of designs created by both groups during first and second design iteration. Error bar represents ±1 standard error.

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Fig. 8

Sample of designs created by the defixation group; (a) first design iteration and (b) second design iteration. *V—Visibility score, R—Reachability score, a—Accessibility score, and S—Setup complexity score.

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Fig. 9

Average redesign difficulty score for both groups. Error bar represents ±1 standard error.

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Fig. 10

Average frustration score for both groups. Error bar represents ±1 standard error.

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