Design of an order acceptance and scheduling module in a unified framework with product and process features
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
In manufacturing industry, advanced production planning becomes challenging when collaborative manufacturing is involved. First, manufacturing tasks are driven by the customer's requirements which are constantly changing. Therefore, order acceptance becomes a complicated problem because it is difficult to answer whether the order can be fulfilled or not. Further, each contractor's capacity becomes a factor to be considered constantly in the overall dynamic planning and scheduling activities. Such effort requires the mapping exercise between manufacturing tasks and contractors' capabilities with some detailed optimization. On the other hand, engineering configuration solutions for customers are constantly updated, so are the manufacturing tasks, and then supplier/contractor jobs. Customer-oriented manufacturing demands full integration of engineering design and production planning in an integrated environment. This paper proposes a generic framework in an advanced Enterprise Resource Planning (ERP) system for the unification of product and process models in order to fulfill the variety of customer orders. A feature-based production scheduling and capacity management data structure model is suggested accordingly. Based on the suggested framework, an order acceptance and scheduling (OAS) module within Visual Manufacturing (a commercial ERP system) is designed. Technologically, a new feature category, i.e. process features, including capacity and customer profile features, is introduced for further research and implementation.
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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