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33
were surprisingly consistent with qualitative assessments of the transcripts, and
seemed to accurately reflect the general decision-making process of the designers.
Interestingly, one of the findings of Yang [139] was that design language evolves
rapidly over time because of the inherently changing nature of conceptual design
process. For example, at the beginning of a project, a designer may refer to a
component more generically (a “thing”) and then become more specific as design and
function become clearer. However, the same pattern of changing terminology was not
found here, in part because large scale re-design projects tend be based on well-established
“legacy” projects, and the language used to describe the projects likewise
tends to be fairly fixed.
0
2
4
6
8
10
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 Time (in 10 minute intervals)
word occurrences
Figure 3.4 Word Frequencies for Alternative b1 of Problem B
Object Description
| Title | Extraction of preferential probabilities from early stage engineering design team discussion |
| Author | Ji, Haifeng |
| Author email | haifengj@usc.edu; haifeng.ji@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Industrial & Systems Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-08-19 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-10-07 |
| Advisor (committee chair) | Yang, Maria C. |
| Advisor (committee member) |
Lu, Stephen Jin, Yan |
| Abstract | Activities in the early stage of engineering design typically include the generation of design choices and selection among these design choices. A key notion in design alternative selection is that of preference in which a designer or design team assigns priorities to a set of design choices. However, preferences become more challenging to assign on both a practical and theoretical level when done by a group of individuals. Preferences may also be explicitly obtained via surveys or questionnaires in which designers are asked to rank the choices, rate choice with values, or select a "most-preferred" choice. However, these methods are typically employed at a single point of time; therefore, it may not be practical to use surveys to elicit a team’s preference change and evolution throughout the process.; This research explores the text analysis on the design discussion transcripts and presents a probabilistic approach for implicitly extracting a projection of aggregated preference-related information from the transcripts. The approach in this research graphically represents how likely a choice is to be "most preferred" by a design team over time. For evaluation purpose, two approaches are established for approximating a team's "most preferred" choice in a probabilistic way from surveys of individual team members. A design selection experiment was conducted to determine possible correlations between the preferential probabilities estimated from the team's discussion and survey ratings explicitly stated by team members. Results suggest that there are strong correlations between extracted preferential probabilities and team intents that are stated explicitly, and that the proposed methods can provide a quantitative way to understand and represent qualitative design information using a low overhead information extraction method. |
| Keyword | preferences; probabilities; concept selection; design process; design decision-making |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m1635 |
| Contributing entity | University of Southern California |
| Rights | Ji, Haifeng |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | cisadmin@lib.usc.edu |
| Filename | etd-Ji-2413 |
| Archival file | uscthesesreloadpub_Volume14/etd-Ji-2413.pdf |
Description
| Title | Page 45 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 33 were surprisingly consistent with qualitative assessments of the transcripts, and seemed to accurately reflect the general decision-making process of the designers. Interestingly, one of the findings of Yang [139] was that design language evolves rapidly over time because of the inherently changing nature of conceptual design process. For example, at the beginning of a project, a designer may refer to a component more generically (a “thing”) and then become more specific as design and function become clearer. However, the same pattern of changing terminology was not found here, in part because large scale re-design projects tend be based on well-established “legacy” projects, and the language used to describe the projects likewise tends to be fairly fixed. 0 2 4 6 8 10 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 Time (in 10 minute intervals) word occurrences Figure 3.4 Word Frequencies for Alternative b1 of Problem B |
