PHYSICAL AND VIRTUAL ENVIRONMENT FOR AUTOMATION EDUCATION ENGINEERS AND TECHNICIANS PART 1: ENGINEERING AN AUTOMATED RECYCLING FACILITY FOR BOTTLES AND CANS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nowadays, production equipments are controlled by programmable logic controllers (PLC) that can communicate over Ethernet. The technicians and engineers of the industry work together in order to develop, support, diagnose, solve, and optimize automated production systems. Current technology has attained such a level of sophistication that it is now possible to interact with a machine without having to move from ones chair. Faced by these observations, the Université du Québec à Rimouski(UQAR), the Cégep de Rivière-du-Loup, and Premier Tech Company, a world leader in the field of bagging equipment, have decided to join forces in order to improve the training of future engineers and technicians in the field of Industrial Automation and Control. The aim of the project is to allow university and CEGEP (college) students to work together on practical problems while being in two separate sites. The first step consists of designing an automated mini plant for the recycling of containers. The mini plant, designed and manufactured by UQAR's engineering students, has been installed in the CEGEP building located 100 km away from the University. The aim of the following step is to create a virtual environment allowing the follow up and visualization of the mini plant, to diagnose problems from a remote location, etc. Finally, the project focus on the development of training situation scenarios related to breakdown diagnostics, parameter adjustments, performance tests, security aspects, and process optimization. This article offers an overview of the project and of the mini plant as designed by the engineering students of UQAR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it