An integrated control policy for cost and waste minimization in unreliable hybrid manufacturing-remanufacturing systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper addresses production‑planning and control in a mixed‑configuration hybrid manufacturing – remanufacturing system where one dedicated facility manufactures, while a second shared facility alternates – via setup operations – between manufacturing and remanufacturing modes. This configuration provides valuable flexibility and superior resource utilization but must still contend with capacity limits, stochastic demand and returns, machine failures, and setup‑induced downtime. The objective is to establish an integrated control policy that synchronizes manufacturing, remanufacturing, setup, and disposal through hedging‑point production rules and stock‑threshold triggers for setup and disposal. A multi‑objective simulation – optimization approach, combining response‑surface methodology with a desirability function, optimizes the policy parameters to minimize total cost and disposed returns. Sensitivity experiments confirm robustness under different managerial priorities; emphasizing remanufacturing reduces waste, whereas favoring manufacturing mitigates stockouts and holding costs. These guidelines enable decision‑makers to leverage the mixed configuration’s capabilities while maintaining a practical balance between cost efficiency and sustainability in failure‑prone environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 it