Implementación del mantenimiento centrado en la confiabilidad (RCM) al sistema de izaje mineral, de la compañía minera Milpo, unidad El Porvenir
Bibliographic record
Abstract
Traditionally in plants stationary equipment maintenance plans are based on manufacturer recommendations, certain fixed periods, based on internal policies of the plant or simply applying corrective maintenance, ie repair until it fails.However, the goal of all contemporary head of maintenance is always to keep your equipment or assets in high availability and reliability, in order to ensure continuous production.In the research the following problem what technical and / or methodology should be applied to improve the maintenance plan Hoist System Co. Ore addressed.Milpo, unit "El Porvenir".They included 18 technicians from the area Hoist Maintenance Cia.Milpo, unit "El Porvenir" Company Specialized Tiley in Canada and Peruavians Hydraulic Company Specializes in Peru SAC, plan development took place from 10 january 2011 until 31 december 2011 in the firm.Milpo Unit: El Porvenir ".There 6 face meetings and field visits were conducted to arrive finally finish the maintenance plan based on trust.It was a quantitative research, which steps were data collection, assessment and methodology of applying RCM plan.It has used a risk analysis, applying the methodology of analysis of failure modes, effects and criticality (FMECA or FMECA) in order to identify failure modes that represent a higher risk, and later select the best kind of maintenance either preventive, predictive, corrective or if system redesign.Within this assessment classification of critical assets, Lifting system was performed to select the kinds of preventive, predictive and corrective measures to be applied by each team to join Hoist System Co. Ore maintenance.Milpo, unit "El Porvenir".vi After completing this application maintenance plan prepared by RCM effect has been improved scheduled maintenance intervals, considering that formerly engaged 3 times a week and now intervenes only 2 times per week.The detail of this reduction is held in conduct effective and necessary for each type of asset that forms the Lifting System Mineral activities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".