Date of Award
12-2009
Document Type
Thesis
Degree Name
Master of Science (MS)
Legacy Department
Mechanical Engineering
Committee Chair/Advisor
Summers, Joshua D
Committee Member
Mocko , Gregory
Committee Member
Garrett , Sandra
Abstract
It is important for designers to understand the usefulness of different engineering representations in order to save time and money throughout a project. Designers often rely on past experience to decide which model to construct; yet students without this experience have no help. Interestingly there are noticeable gaps in the research literature with respect to how and when to select representations and modeling approaches for engineering designs. This thesis examines the differences between three types of engineering representations, specifically sketches, drawing packages, and physical prototypes. The amount of information designers can extract from these representations and also the correctness and confidence of the designers when examining these representations is studied. Design reviews of concepts with respect to requirements verification serves as the design task of this investigation. The data from this user study is analyzed using descriptive and nonparametric statistics. The results reveal that designers are more confident and correct in making conclusions about whether a design meets requirements when using high fidelity representations and physical representations, specifically high fidelity prototypes. Low fidelity representations appear to be useful for determining if a design meets functional requirements, but not geometric or manufacturing requirements. The relationship between drawing packages and low fidelity prototypes is still somewhat unclear and thus is an area for further research. The results from this experiment lay the foundation for further research into the amount and types of information contained within these representations.
Recommended Citation
Hannah, Rachel, "User Study of Information Extracted from Engineering Representations" (2009). All Theses. 672.
https://open.clemson.edu/all_theses/672