Improving the broke recirculation strategy in a newsprint mill
Bibliographic record
Abstract
HEET BREAKS are a major disturbance in the newsprint process and cause costly paper machine downtime. Fluctuations in the pulp furnish can upset the stability of a paper machine and are one of the causes of breaks. These fluctuations can be the result of the broke recirculation strategy applied at the mill. Specifically, sudden changes to the broke ratio can induce considerable variations in the properties of the mixed pulp at the paper machine headbox [7]. Broke recirculation strategies can be quantified and explored by the application of simulation-based optimization. This technique is increasingly being used in other applications, and has been shown to yield significant economic benefits at low investment cost and little disturbance to the actual process [3,6]. This study focuses on developing a dynamic simulation of the papermaking section of an integrated newsprint mill, and using an objective function to quantify fluctuations at the headbox. Direct search optimization was then applied to identify opportunities for improving the broke recirculation strategy at the mill. The overall goal was to reduce headbox variability caused by adjustments in the broke ratio.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".