Joint economic design of production, continuous sampling inspection and preventive maintenance of a deteriorating production system
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
Standard continuous sampling procedures and tables are conventionally applicable only to continuous production processes that are statistically ‘in-control’. Consequently, these standards cannot be used to control quality in deteriorating production processes. Moreover, existing continuous sampling models do not consider interactions with production, inventory and maintenance aspects. In this paper, we attempt to fill these gaps in the literature. We investigate the joint design and optimization of a type-1 continuous sampling plan (CSP-1), make-to-stock production and preventive maintenance of a stochastic production system subject to both quality and reliability deteriorations. Two models of CSP-1 are considered and compared: the classical CSP-1 as in the standard procedures, and a CSP-1 plan with a stopping rule that is combined with condition-based maintenance. For both models, the optimization problem is to minimize the total incurred cost under a constraint on the outgoing quality. A combination of mathematical formulation, simulation and optimization techniques is used to solve such stochastic and constrained problems. Numerical examples are given to illustrate the resolution approach and to highlight some interesting aspects in the interactions between production, inventory, quality, maintenance and reliability. The results obtained demonstrate that sampling inspection plans realize significant cost savings compared to the 100% inspection which is commonly used in the literature of integrated models, and that using the CSP-1 with an inspection stopping rule for deteriorating processes is more cost-effective than the classical CSP-1.
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 | 0.000 | 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