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Record W2019565232 · doi:10.1115/detc2003/dfm-48141

Systematic Life Cycle Design for Sustainable Product Development

2003· article· en· W2019565232 on OpenAlexaff
B. Lu, Peng Gu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProduct lifecycleProduct designProduct (mathematics)New product developmentProduct design specificationDesign review (U.S. government)Life-cycle assessmentQuality (philosophy)Process (computing)Design for the EnvironmentSystems engineeringComputer scienceRisk analysis (engineering)Sustainable productsSustainable developmentSustainable designManufacturing engineeringProcess managementEngineeringSustainabilityOperations managementBusinessProduction (economics)Product testing

Abstract

fetched live from OpenAlex

Sustainable product development (SPD) requires that product design achieves minimum or zero environmental impact, in addition to satisfying the traditional design criteria such as product functionality, quality, features, costs and time to market. Therefore, the environmental evaluations must be incorporated into design stage. In this research, a product design process model was proposed which includes three design requirements, two design tasks, and three comprehensive assessment streams. The functional requirement is derived from the customer needs to reflect the product’s functional purpose; the environmental requirement reflects the society’s needs of protecting natural resources and environment; and the economic requirement is to ensure the company’s basic business goals. Accordingly, SPD aims to simultaneously carry out two tasks of designing products’ physical structures and lifecycle structures. In the assessment phase of product design, three assessment streams, lifecycle quality (LCQ) analysis, lifecycle assessment (LCA), and lifecycle cost (LCC) are conducted with respect to the functional, environmental, and economic evaluations. A Process-Based Analysis concept is proposed for analysis of all three dimensions of LCQ, LCA, and LCC evaluations. Simplified LCA was used for environmental evaluations. The detailed assessment techniques are also developed for effective design evaluations. A case study will be provided to illustrate the methods and models.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.213
Teacher spread0.196 · 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 designTheoretical or conceptual
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

Citations10
Published2003
Admission routes1
Has abstractyes

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