Capability index of a complex-product machining process
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
A complex product often requires a high machining precision. This is often achieved by a close-loop machining process to be carried out in several stages, and the measurements, fixture adjustments, and feedback or feed-forward control are inserted after each of these stages. The Complex Product Machining Process (CPMP) Capability Index (CPMPCI) is affected by the control and adjustments in a CPMP, and hence the calculation results of CPMPCI can be used as references to select a proper CPMP. In this paper, we present a novel calculation method of CPMPCI as quality control and improvement technology in a CPMP. A linear model is proposed for describing the variation propagation effect throughout all stages in a CPMP, and an observation model with the pre-specified control and adjustment strategy is employed to calculate the process mean and variation during a CPMP. Finally, through application of Taguchi's quality loss function, the CPMPCI calculation method is derived. The feasibility and effectiveness of this method are validated by a case study on a three-stage CPMP.
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 | 0.000 |
| 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