Integration of Computer Aided Design and Manufacturing at Second Year level in Undergraduate Program
Bibliographic record
Abstract
Computer Graphics for Mechanical and Manufacturing Engineering at the University of Manitoba has evolved from a generic first year program to a second year design course that simulates real world experience through the development of a team based project. This challenging and comprehensive program integrates two separate course into one, CAD (Computer Aided Design) and Computer Aided Manufacturing (CAM) Concepts. The latter provides a framework to the process of computer-controlled manufacturing with an emphasis on use of advanced computerized machines. The CAD portion is taught in three stages; the first stage builds proficiency in 3D modeling techniques to create working virtual models. The second stage focuses on the language and communication of mechanical design, and the third stage develops practical skills on a host of modern technology, including CNC (Computer Numerical Control) and rapid prototyping equipment. The second part provides a series of lectures establishing the link between CAD and CAM and culminates in a design project that links the two modules. These complementary programs work hand in hand to provide the necessary theory and practical skill for the students to work in teams, to develop and conclude the term with a working device that they designed, fabricated and tested in one of the two production laboratories allocated to this course. At the conclusion of this program, each device is authenticated to ensure that it has met the criterion which validates both the design as well as the student’s learning experience. This paper will endeavour to be candid in sharing our experiences with you. We will cover everything from looking at the history behind this program, to the challenges we met. Most notably, the number of students compared to the equipment available in both the learning and production stages of this course. We will also explore the principals and thinking that constituted the curriculum with the goal that each facet of learning, both in its theory and application directly relates to real world practice that would contribute to the student’s field of study and their preparation for industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".