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Record W2495974082 · doi:10.5539/mas.v10n8p230

A Combined Approach for Production Parameter Selection and On-site Energy Supply Management in Manufacturing Industry

2016· article· en· W2495974082 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsProduction (economics)Energy supplyComputer scienceInterdependenceSelection (genetic algorithm)Energy managementSite selectionManufacturingEnergy (signal processing)Manufacturing engineeringIndustrial engineeringRisk analysis (engineering)Environmental economicsBusinessEngineering

Abstract

fetched live from OpenAlex

Integrated management of manufacturing plant’s production and on-site energy supply systems has shown potential economic, environmental and resource efficiency advantages for the industry. However, existing approaches are solely based on pure mathematical models with a high degree of abstraction with limited applicability, which becomes impractical for industrial applications. In this paper a simulation methodology for production parameters selection and on-site energy supply management is presented. In this case, state-based models and operational strategies of manufacturing processes and on-site energy supply options are integrated to represent interdependency between production processes, technical building services and on-site energy supply system. As a result, the proposed methodology covers manufacturing system complexity without compromising the required accuracy. This is applied to a batch based manufacturing plant and the impact of particular production parameters on energy demand profile is evaluated. The results indicate the impact of production parameters on energy supply system. In addition, the proposed approach enables manufacturers to evaluate the implications of potential production approaches in order to select appropriate operational strategies for on-site energy supply systems.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.499

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 head0.014
GPT teacher head0.221
Teacher spread0.206 · 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