Design of Dual Core Plus (TM) Sheet Collation System
Bibliographic record
Abstract
Tempeff is a Winnipeg-based heating, ventilation, and air conditioning (HVAC) engineering firm and manufacturer which markets energy recovery systems across North America. An important component of their recovery systems are energy cores – a mechanical assembly responsible for capturing and storing heat in air that is exhausted from a building. These energy cores are made from aluminum sheet metal that is contained inside a frame. Tempeff has commissioned a design challenge through the University of Manitoba Innovative Design for Engineering Applications (UMIDEA) program to increase the manufacturing efficiency of their DualCorePlusTM energy cores. DSQV and Associates partnered with Tempeff to complete their design challenge over the course of the University of Manitoba's Fall 2021 semester. This project was completed for credit in MECH4860: Engineering Design. The current process of manufacturing cell frames sees a shop floor employee physically catch aluminum sheets that exit a corrugation machine (i.e., corrugator) via a conveyor belt. The employee then collates the aluminum sheets into an organized stack and places the sheets inside a frame. Tempeff requested that DSQV and Associates develop an automated solution that collects and stacks aluminum sheets inside the frame in order to increase manufacturing efficiency and decrease cycle time. Moreover, the solution had to accommodate variation in cell frame dimensions. While the frames are always 12 inches in width, their length varies from 6.1" to 21.5" and height varies from 4.7" to 23.65". Tempeff agreed to the following deliverables: a final design report, CAD models of custom parts, CAD assembly of the entire solution, bill of materials, explanation of the operational principles of the machine, and preliminary engineering drawings. On completion of the project, these deliverables were provided to Tempeff. The proposed solution to this design challenge is an automated sheet collation machine. This machine transports sheets from Tempeff's corrugator using conveyor belts with rails on each side. The aluminum sheets are placed inside a cell frame using a combination of retracting horizontal ledges, retracting vertical actuators, and a cell frame fixture system that accommodates the noted size variation. Automation of this sheet collation machine is achieved using a PLC, appropriate sensors, and actuation control equipment. DSQV and Associates' automated sheet collation machine measures 14.75' x 2' x 6.5' and can be integrated with the existing corrugation machine. The total cost of the solution is $48,043.77, and it can process up to 37 sheets per minute.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".