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Record W4234186239 · doi:10.1002/9780470061572.eqr292

Process Capability Indices, Comparison of

2007· other· en· W4234186239 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEncyclopedia of Statistics in Quality and Reliability · 2007
Typeother
Languageen
FieldDecision Sciences
TopicAdvanced Statistical Process Monitoring
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPerspective (graphical)Process (computing)Variety (cybernetics)Process capabilityFunction (biology)Yield (engineering)Interpretation (philosophy)Quality (philosophy)Process capability indexManagement scienceStatisticsComputer scienceEconometricsMathematicsEngineeringEpistemologyWork in processArtificial intelligenceOperations managementBiologyPhilosophyThermodynamicsEvolutionary biology

Abstract

fetched live from OpenAlex

Abstract The most common process capability indices are examined from several perspectives. A brief historical review outlines recent developments from simple variability measures to today's more sophisticated indices. The behavior of the indices C pk , C pm , and C pmk is compared with C p for processes that are not necessarily centered at target, illustrating the relationships among the various indices. A weight function is presented that allows the functional form of a variety of indices to be examined. A discussion of process yield and the resulting interpretation from a quality loss perspective is presented and the differing philosophies represented by the competing indices are highlighted.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.096
GPT teacher head0.484
Teacher spread0.388 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it