MétaCan
Menu
Back to cohort
Record W2165915202 · doi:10.1109/cca.2011.6044512

Process variability and inherent efficiency enhancement in industrial processes: Two case studies in pulp and paper industry

2011· article· en· W2165915202 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsCentre de Recherche Industrielle du Québec
Fundersnot available
KeywordsCapital investmentProcess (computing)Process controlProductivityWork in processComputer scienceEconometricsVariable (mathematics)Industrial engineeringEngineeringProcess engineeringManufacturing engineeringMathematicsOperations managementEconomics

Abstract

fetched live from OpenAlex

In this paper, the correlation between process variability attenuation and efficiency enhancement in industrial processes is studied. The starting hypothesis of this work states that process variability attenuation brings about efficiency enhancements in both energy and productivity aspects. To test the hypothesis, a multi-variable statistical approach requiring no process model is proposed. The approach is applied to two case studies in pulp and paper industry. The results approve the starting hypothesis while they can further be used to justify any capital investment in advanced control systems to attenuate process variability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

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

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 head0.073
GPT teacher head0.308
Teacher spread0.235 · 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

Quick stats

Citations3
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicProcess Optimization and IntegrationFrench-language works237,207