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Record W7043538484

Success factors and organizational approaches for the implementation and the operational use of energy management systems according to ISO 50001: Paper presented at the 6th Canadian Quality Congress, September 29-30, 2014, University of Manitoba, Winnipeg, Manitoba, Canada

2014· other· en· W7043538484 on OpenAlexaboutno aff

Bibliographic record

VenueFraunhofer-Publica (Fraunhofer-Gesellschaft) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationQuality (philosophy)Success factorsKey (lock)Quality management systemEnergy managementManagement systemGerman
DOInot available

Abstract

fetched live from OpenAlex

Due to rising energy costs, increasing global competitive pressure and the demand for environmentally friendly products companies all over the world consider the implementation of an energy management system (EnMS) to meet future challenges. The purpose of this paper is to identify main success factors for the effective implementation, operation and certification of an EnMS in accordance with ISO 50001, which represents the fastest growing standard for management systems in the world. For that reason a survey among already certified German companies has been conducted focusing on organizational, teambuilding and technical aspects. The study provides best practice knowledge and gives interested companies the advantage to benefit from both the positive experiences of the participants as well as to prevent potential contra productive activities during the implementation, certification and operation of an EnMS. Results indicate that EnMSs are most commonly built on already existing management structures and therefore staff organization is crucial for the success of the project. Still, monetary aspects such as energy related cost savings seem to be the decisive criterion for the operation of an EnMS. Regarding teambuilding aspects specific technical expertise is required which leads to cross-functional teams focusing on the field of production. In addition key technical and administrative measures for an effective EnMS were identified.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.132
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.236
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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