Robotic System for Automatic Dispensing and Cutting of Rubber Cord Into a Compression Mold
Bibliographic record
Abstract
Automation with the use of robotics is a crucial trend across industries, enhancing efficiency and quality while improving health and safety conditions by minimizing human exposure to hazardous tasks. Alfa Laval, a global provider of products within heat transfer, separation, and fluid handling, is embracing this trend by exploring how to solve labor-intensive processes like the production of rubber gaskets for gasketed plate heat exchangers (GPHE). The current manual process at Alfa Laval is labor-intensive and poses health risks because of exposure to potentially harmful fumes. This thesis investigates the feasibility and design of a robotic system for the automatic dispensing and cutting of rubber cord into a compression mold, utilizing an articulated robot arm to enhance safety and efficiency. A prototype robot tool was developed, built, and tested to perform the task of dispensing and cutting rubber cord into a compression mold. It included a feeding mechanism without feedback control and a cutting mechanism driven by a pneumatic piston. The feeding mechanism was developed by investigating existing solutions, comparing designs, and conducting tests. The final mechanism consisted of two belt-driven grooved wheels pushing the cord out, driven by a microcontroller in a non-blocking control loop that pulsates a stepper motor at a given interval when it receives a signal from the robot control cabinet. Furthermore, a stationary cutting mechanism was developed. Various designs, including a scissor driven by a stepper motor and linear actuators, were evaluated, resulting in the selection of a knife bracket driven by a pneumatic piston, which successfully cut the cord. Tests were conducted to evaluate the method of laying down rubber cord freely into a life-sized model of the real compression mold. The tests concluded that the method is not feasible in its current setup primarily because of two reasons: The first one being the difficulty in matching the feeding speed with the robot’s movement because of cord slippage, and the second one being, the twisting forces acting on the rubber cord causing it to move out of the mold once placed. Potential solutions for future work include fixating the cord, implementing feedback control, and improving the feeding mechanism.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".