Developing a bi-objective imperfect selective maintenance optimization model for multicomponent systems
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Bibliographic record
Abstract
This paper develops a bi-objective imperfect selective maintenance optimization model for a multicomponent system, which carries out missions interspersed with scheduled breaks. Imperfect maintenance (IM) actions are performed on the components during the break to increase the system reliability during the following mission. The level of maintenance performed determines the improvement of the component's health. A mathematical model with two objective functions is developed to optimize the tradeoffs between the total maintenance cost and the system reliability based on the decision maker's preferences. Numerical examples are provided to show that the proposed model reaches valid maintenance decisions. Furthermore, it is shown that when high system reliability is required, the optimal decision is not significantly affected by the decision-maker's preference for one objective or the other.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it