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Research Papers: Design Theory and Methodology

A Systematic Method for Design Prototyping

[+] Author and Article Information
Bradley Camburn

Engineering Product Development,
Singapore University of Technology and Design,
20 Dover Drive, Singapore 138682
e-mails: bradley_camburn@sutd.edu.sg;
bcamburn@gmail.com

Brock Dunlap

Department of Mechanical Engineering,
The University of Texas at Austin,
204 E. Dean Keeton St. C2200,
Austin, TX 78712
e-mail: bdunlap@utexas.edu

Tanmay Gurjar

Department of Mechanical Engineering,
The University of Texas at Austin,
204 E. Dean Keeton Street, C2200,
Austin, TX 78712
e-mail: tanmaygurjar@utexas.edu

Christopher Hamon

Department of Mechanical Engineering,
The University of Texas at Austin,
204 E. Dean Keeton Street, C2200,
Austin, TX 78712
e-mail: xamon@utexas.edu

Matthew Green

Department of Mechanical Engineering,
Le Tourneau University,
2100 South Mobberly Avenue,
Longview, TX 75602
e-mail: matthewgreen@letu.edu

Daniel Jensen

Department of Engineering Mechanics,
United States Air Force Academy,
U.S. Air Force Academy,
Colorado Springs, CO 80840
e-mial: dan.jensen@usafa.edu

Richard Crawford

Department of Mechanical Engineering,
The University of Texas at Austin,
204 E. Dean Keeton Street, C2200,
Austin, TX 78712
e-mail: rhc@mail.utexas.edu

Kevin Otto

Engineering Product Development,
Singapore University of Technology and Design,
20 Dover Drive,
Singapore 138682
e-mail: kevin_otto@sutd.edu.sg

Kristin Wood

Engineering Product Development,
Singapore University of Technology and Design,
20 Dover Drive,
Singapore 138682
e-mail: kristinwood@sutd.edu.sg

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received August 12, 2014; final manuscript received March 30, 2015; published online June 8, 2015. Assoc. Editor: Kristina Shea.

J. Mech. Des 137(8), 081102 (Aug 01, 2015) (12 pages) Paper No: MD-14-1487; doi: 10.1115/1.4030331 History: Received August 12, 2014; Revised March 30, 2015; Online June 08, 2015

Scientific evaluation of prototyping practices is an emerging field in design research. Prototyping is critical to the success of product development efforts, and yet its implementation in practice is often guided by ad hoc experience. To address this need, we seek to advance the study and development of prototyping principles, techniques, and tools. A method to repeatedly enhance the outcome of prototyping efforts is reported in this paper. The research methodology to develop this method is as follows: (1) systematically identify practices that improve prototyping; (2) synthesize these practices to form a guiding method for designers; and (3) validate that the proposed method encourages best practices and improves performance. Prototyping practices are represented as six key heuristics to guide a designer in planning: how many iterations to pursue, how many unique design concepts to explore in parallel, as well as the use of scaled prototypes, isolated subsystem prototypes, relaxed requirements, and virtual prototypes. The method is correlated, through experimental investigation, with increased application of these best practices and improved design performance outcomes. These observations hold across various design problems studied. This method is novel in providing a systematic approach to prototyping.

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References

Figures

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Fig. 1

Representation of overall research method employed in this study

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Fig. 2

(a) Use of iteration in design for spoke holes on a conveyor belt: schematics of four tested design generations and image of the final design. Iteration was employed to achieve target performance. (b) Parallel load testing of three strut design concepts for a prosthetic limb. Parallel testing highlights differences in performance.

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Fig. 3

(a) Scaled (left) and full (right) model of fluid chamber for testing interfaces, (b) isolated prototypes for joint interfaces to reduce effort, (c) relaxed requirement model for a three-dimensional white board, to test usability, and (d) virtual design of a Baja vehicle for structural analysis and part design

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Fig. 4

Survey tool for implementation of prototyping method

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Fig. 5

(left) Depiction of design problem and (right) example prototype from study 1—binary design objective. This design acts like a drawbridge, dropping the coin into place.

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Fig. 6

(left) Design problem and (right) example prototype from study 2—open design objective. The design acts like a ramp, guiding a disk into a rolling motion along the track.

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Fig. 7

(left) Depiction of design problem and (right) example prototype from study 3—virtual prototyping. This sample from the physical prototyping condition will trace the pencil in a desired pattern.

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Fig. 8

An example prototype from the capstone design study, a cam phaser

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Fig. 9

Performance with respect to increasing number of cycles of iteration. ±1 Standard error shown. Source: study 2—open design objective. Each point represents the average performance of the ith iteration, across all teams.

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Fig. 10

Time spent to develop each iteration with respect to ith iteration. ±1 Standard error shown. Source: study 2—open design objective.

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Fig. 11

Four metrics to evaluate prototypes, with regard to scaling, subsystem isolation, and requirement relaxation. ±1 Standard error shown. Results are for each prototype on average in class study with regard to: (top left) cost expended, (top right) time spent, (bottom left) performance achieved, (bottom right) information gained. Source: study 4—capstone design.

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Fig. 12

Comparison of how closely teams followed their suggested approach, and outcome performance of prototyping efforts. ±1 Standard error shown. Source: study 4—capstone design.

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