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Record W2529628077 · doi:10.1504/ijplm.2016.10000584

Elements of managerial integration for sustainable product lifecycle management

2016· article· en· W2529628077 on OpenAlexaff
Raimundo Kennedy Vieira, Milena Chang Chain, Darli Rodrigues Vieira

Bibliographic record

VenueInternational Journal of Product Lifecycle Management · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsProduct lifecycleTraceabilitySupply chainSustainabilityProduct managementProcess managementBusinessSupply chain managementProduct (mathematics)Cleaner productionQuality (philosophy)Production (economics)Sustainable developmentNew product developmentEngineeringMarketingEconomics

Abstract

fetched live from OpenAlex

The aerospace industry currently demands environmental sustainability, especially because of the complexity of new product development, the structure of its supply chain and its commitment to product quality. The implementation of sustainable product lifecycle management (PLM) seems to be an adequate strategy for this purpose because this approach is indicated for projects that demand a holistic and sustainable production system. Hence, the aim of this study is to discuss the dynamics of integrating the managerial elements (cleaner production, green design, green supply chain management - GSCM), which are supported by traceability, in a sustainable PLM. This study explores the connections among the approaches that could help to improve the development of sustainability throughout the entire production process in the industry and along the supply chain. This integration would benefit all production stages by facilitating the implementation of PLM and increasing the quality and safety of the aerospace sector.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0020.001
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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations4
Published2016
Admission routes1
Has abstractyes

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