Production Planning and Opportunistic Preventive Maintenance for Unreliable One-Machine Two-Products Manufacturing Systems
Why this work is in the frame
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Bibliographic record
Abstract
This paper develops an effective joint production, setup and maintenance control policies in an unreliable one-machine two-products manufacturing system. The main objective is to reach a higher synchronization level of the preventive maintenance (PM) interventions in the planning of production activities. The proposed joint control policy integrates the concept of the opportunistic maintenance by taking advantage of the machine stoppage during setup operations in order to conduct preventive actions. This aims to increase the machine availability and to reduce the risk of shortages. Performance evaluation of the proposed control policy is carried out using a combined continuous/discrete event simulation model. It is subsequently analyzed by statistical techniques of optimization such as design of experiments, analysis of variance and response surface methodology. An illustrative numerical example followed by an in-depth comparison study for a wide range of the system configurations are performed in order to demonstrate the usefulness and the robustness of the results.
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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 | 0.001 | 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