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A Platform Independent Methodology For Teaching Students To Leverage The Power Of Parametric Design Tools
Author(s) -
Michael Johnson,
Udaya Bhanu Prakash Sunku
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--15837
Subject(s) - leverage (statistics) , cad , computer science , parametric statistics , computer aided design , software engineering , electronic design automation , engineering drawing , engineering management , industrial engineering , engineering , machine learning , statistics , mathematics , embedded system , operating system
One of the great contributions to engineering productivity over the last two decades has been the introduction of parametric computer-aided design (CAD) programs. In an increasingly competitive environment where more and more products have ever decreasing lifetimes, these programs allow engineers to make rapid design changes and quickly communicate designs to various customers and vendors. CAD has become an indispensable tool for most engineering professionals. Too often CAD courses are taught as platform specific means to reach some geometric end. Conveying design intent and leveraging the parametric nature of these tools is not emphasized. This reduces the ability of students to produce designs which others can quickly change; the capacity of others to comprehend the organization of the model is also limited. This focus on a geometric end also causes students to concentrate on expedient platform specific means of reaching that end. In this paper a methodology is detailed for teaching CAD in a manner that demonstrates the importance of design intent. The production of models that are clearly organized and easily changed is emphasized. Platform independent exercises which can be used to demonstrate and emphasize these goals are detailed. Data collected at the beginning and the end of the semester to assess the students’ confidence with the parametric and feature-based nature of CAD are presented. Students showed a significant increase in their confidence and ability to describe parametric and feature-based concepts.

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