Optimization of Maintenance Activity Using the World-Class Maintenance System in Skidder Forest Operations
Bibliographic record
Abstract
The objective of this paper was to evaluate technical and economically the use of a world-class maintenance system (WCM) in the forest skidding operations. The study was performed in a forest company located in the state of Paraná, inside forest plantations of Pinus taeda and Eucalyptus grandis. For the purpose of analysis, the mechanical availability, hydraulic oil consumption, average time between failures, average repair time, proactive maintenance index and maintenance costs were evaluated during 18 months, considering the stages of implantation, maturation and stabilization of the WCM system. As a result, there was an increase in the percentage of mechanical availability and reduction of 47.0% in the consumption of hydraulic oil from Skidder in the maturation stage. Also, the average time between failures and repairs increased in the maturation stage, caused by a quality improvement of maintenance activities. Moreover, in the maturation stage there was an increase of 45.0% in the proactive maintenance index. Additionally, it was verified that the hourly maintenance cost was reduced by 8.0% between the maturation and stabilization stages, underlining the WCM system’s potential to improve maintenance activities in the forest skidding operation. These results show that the WCM system can contribute to safety in wood harvesting operations, increasing the Skidder mechanical availability and a reducing the production costs.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".