Trying to Resolve Manufacturing Performance Trade‐Offs: The Case of British Contract Electronics Assemblers
Bibliographic record
Abstract
Abstract The changing nature of competitive pressure now requires companies to compete on several aspects of performance simultaneously. This reality departs from the traditional idea that organizations must find a specific area of competency and choose between objectives such as low cosT., quality, or flexibility. Hence, the degree to which companies resolve manufacturing performance trade‐offs, and the understanding of the processes whereby companies manage to achieve this, emerge as a set of research questions. This paper presents the results of a benchmarking study carried out to assess and compare the levels of manufacturing performance achieved by 16 British contract electronics assemblers. Case studies conducted in three of these companies highlighted structural and cultural aspects that may explain intercompany differences in the resolution of manufacturing performance trade‐offs. Résumé La nature changeante des règies de la compétition oblige les entreprises à maǐtriser simultanément plusieurs aspects de la performance manufacturière. Cette réalité diffère de l'idée reçue selon laquelle les organisations doivent choisir entre des objectifs tels la réduction des coǔts, la qualité, ou la flexibilité. Ainsi, l 'évaluation du degré de résolution des arbitrages tradi‐tionnels entre les objectifs de performance manufacturière et la compréhension des facteurs favorisant cette résolution constituent des thèmes de recherche pertinents. Les résultats d'une étude de benchmarking menées auprès de 16 sous‐traitants électroniques britan‐niques et ayant pour but de comparer leur performance manufacturière sont présentés dans cet article. Trois études de cas ont ensuite permis d'identifier différents aspects structurels et culturels qui semblent expliquer les différents niveaux de résolution des arbitrages opéra‐tionnels.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".