A best-worst-method-based performance evaluation framework for manufacturing industry
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance. Design/methodology/approach The best-worst method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance. Findings The proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% and 70% throughout the year. Management performance can be seen high in the 1st and 2nd quarter of the financial year ranging from 70% to 80%, whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year. Originality/value This paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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