Page 31 |
Save page Remove page | Previous | 31 of 171 | Next |
|
small (250x250 max)
medium (500x500 max)
Large (1000x1000 max)
Extra Large
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
|
19
making iterative trade-offs, particularly as teams better understand their objectives,
requirements, and constraints change. In this sense, the design process can be thought
of as an evolution of preferences.
One of the necessary elements for assessing design preference evolution is a
sufficiently rich source of design information to draw upon. The language that
designers use during design discussion may reflect their design process and analysis of
it can provide valuable insights into the design process [32, 140]. Preference
information may be embedded in the qualitative design information that designers and
teams generate, such as logbooks [17], sketches [108, 136], prototypes [137], and
design documentation [84, 114]. These forms of design information represent data that
is generated only at selected intervals during design rather than continuously. For
example, designers may make notes in their logs once or twice a day, and write reports
only at the end of the project. These forms of information may only record the parts of
the design process that a particular designer is willing to commit to paper.
Furthermore, logbooks may reflect only the opinions of a single designer rather than
the overall thinking of an entire design team.
Teams are a common work group unit in engineering practice, and the
deliberation that goes on within a team can have major influence on the choices that
are made for a design. This work looks to verbal design team discussion as an
information source because it includes the opinions of multiple team members. In a
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 31 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | 19 making iterative trade-offs, particularly as teams better understand their objectives, requirements, and constraints change. In this sense, the design process can be thought of as an evolution of preferences. One of the necessary elements for assessing design preference evolution is a sufficiently rich source of design information to draw upon. The language that designers use during design discussion may reflect their design process and analysis of it can provide valuable insights into the design process [32, 140]. Preference information may be embedded in the qualitative design information that designers and teams generate, such as logbooks [17], sketches [108, 136], prototypes [137], and design documentation [84, 114]. These forms of design information represent data that is generated only at selected intervals during design rather than continuously. For example, designers may make notes in their logs once or twice a day, and write reports only at the end of the project. These forms of information may only record the parts of the design process that a particular designer is willing to commit to paper. Furthermore, logbooks may reflect only the opinions of a single designer rather than the overall thinking of an entire design team. Teams are a common work group unit in engineering practice, and the deliberation that goes on within a team can have major influence on the choices that are made for a design. This work looks to verbal design team discussion as an information source because it includes the opinions of multiple team members. In a |
