Unifying Approaches To Mechanical Engineering Design Through A Multidisciplinary Effort
Bibliographic record
Abstract
The completely renewed Mechanical Engineering curriculum features nine credits in mechatronics, including two formal courses (Mechatronics I and Mechatronics II) and a Project of Mechatronics course, as well as fifteen credits in system and product design, including a three credit Design Methodology course and a twelve credit Major Design Project extended over the last three terms of the program.These two large components of the program were developed according to the characteristics of each discipline.This paper presents the results up to the present of a multidisciplinary effort to unify the approaches to mechanical engineering design.It presents the enriched version of the Product Development Process (PDP) which has been developed in order to integrate the two approaches.In this respect, specific tools will be introduced in order to join the design process of a mechatronics system with the design of more traditional mechanical engineering products.This will be illustrated using a pill counter designed by the students as an example.In addition to the Mechatronics and the System and Product Design courses, the scope of this Educational Improvement Project extends to a Computer Programming course and a Project Management course.This paper shows the extent of the changes which are to be brought to all these courses. The Sherbrooke Mechanical Engineering CurriculumCompetency development and integration are the key words of the new Mechanical Engineering curriculum.As shown in Figure 1, design projects are used to carry out the overall integration of different competencies along two thrusts: 1) vertical integration with specific semester-based projects for the first four terms of the program, 2) horizontal integration with projects in mechatronics and a major design project over the last four terms of the program 1,2 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".