Representing functionality and design intent in product models
SMA '93 Proceedings on the second ACM symposium on Solid modeling and applications
Parametric design and its impact on solid modeling applications
SMA '95 Proceedings of the third ACM symposium on Solid modeling and applications
An empirical evaluation of design rationale documents
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A review of web-based product data management systems
Computers in Industry
Parametric and Feature Based CAD/Cam: Concepts, Techniques, and Applications
Parametric and Feature Based CAD/Cam: Concepts, Techniques, and Applications
Evaluating the learning process of mechanical CAD students
Computers & Education
A process-oriented approach to design rationale
Human-Computer Interaction
Parametric Modeling with Autodesk Inventor 2011
Parametric Modeling with Autodesk Inventor 2011
Toward predicting the performance of novice CAD users based on their profiled technical attributes
Engineering Applications of Artificial Intelligence
Explicit reference modeling methodology in parametric CAD system
Computers in Industry
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Computer-aided design (CAD) is a ubiquitous tool that today's students will be expected to use proficiently for numerous engineering purposes. Taking full advantage of the features available in modern CAD programs requires that models are created in a manner that allows others to easily understand how they are organized and alter them in an efficient and robust manner. The results of a class-based exercise are presented to examine the role of model attributes on model creation, alteration, and student perception. Two popular CAD programs are used for the exercise: SolidWorks and Pro|Engineer. General results from both programs are reported. Fewer more complex features are found to be correlated with reduced modeling time. Simple features are shown to be positively correlated with the number of features retained without change. More complex features are found to be negatively correlated with the number of new features. Student perceptions of model quality and intuitiveness are positively correlated with the amount of feature reuse. Student survey data shows a preference for simpler features, the naming of features, and the use of reference geometry. The results do not allow for a generic approach regarding feature complexity to be prescribed. Overall, properly conveying design intent is shown to be positively correlated with design retention and negatively correlated with alteration time.