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Research Papers: Design Theory and Methodology

Comparing Functional Analysis Methods for Product Dissection Tasks

[+] Author and Article Information
Joran W. Booth

Mechanical Engineering,
Purdue University,
West Lafayette, IN 47906
e-mail: boothj@purdue.edu

Tahira N. Reid

Mechanical Engineering,
Purdue University,
West Lafayette, IN 47906
e-mail: tahira@purdue.edu

Claudia Eckert

Mechanical Engineering,
The Open University,
Milton Keynes,
Buckinghamshire MK7 6AA, UK
e-mail: c.m.eckert@open.ac.uk

Karthik Ramani

Mechanical Engineering and
Electrical/Computer Engineering (by courtesy),
Purdue University,
West Lafayette, IN 47906
e-mail: ramani@purdue.edu

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received June 4, 2014; final manuscript received March 23, 2015; published online June 8, 2015. Assoc. Editor: Irem Y. Tumer.

J. Mech. Des 137(8), 081101 (Aug 01, 2015) (10 pages) Paper No: MD-14-1324; doi: 10.1115/1.4030232 History: Received June 04, 2014; Revised March 23, 2015; Online June 08, 2015

The purpose of this study is to begin to explore which function identification methods work best for specific tasks. We use a three-level within-subject study (n = 78) to compare three strategies for identifying functions: energy-flow, top-down, and enumeration. These are tested in a product dissection task with student engineers who have minimal prior experience. Participants were asked to dissect a hair dryer, power drill, and toy dart gun and generate function trees to describe how these work. The function trees were evaluated with several metrics including the total number of functions generated, the number of syntactical errors, and the number of unique (relevant and nonredundant) functions. We found no statistical, practical, or qualitative difference between the trees produced by each method. This suggests that the cognitive load for this task for novices is high enough to obscure any real differences between methods. We also found some generalized findings through surveys that the most difficult aspects of using functional decomposition include identifying functions, choosing function verbs, and drawing the diagram. Together, this may also mean that for novice engineers, the method does not matter as much as core concepts such as identifying functions and structuring function diagrams. This also indicates that any function identification method may be used as a baseline for comparison between novices in future studies.

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Figures

Grahic Jump Location
Fig. 1

A hair dryer, power drill, and toy dart gun

Grahic Jump Location
Fig. 2

The pair of GD metrics (AGD and MGD) is lower for the flat tree than for the bushy tree, even when the number of tree levels is the same. This approach is also robust to nonhierarchy diagrams.

Grahic Jump Location
Fig. 3

The pair of GDs (AGD and MGD) is still lower for the flatter trees even when one of the two is the same

Grahic Jump Location
Fig. 4

These three function trees are digitized submissions of raw data collected from three participants. All three of these trees are for the toy dart gun, but each tree is generated using a different function identification strategy.

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