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Record W1993705904 · doi:10.1115/detc2013-13529

Study on Life Cycle Assessment of Servo Press With Comparison to Flywheel Press

2013· article· en· W1993705904 on OpenAlexaff
Suiran Yu, Yu Liu, Lu Li, Qingjin Peng

Bibliographic record

VenueVolume 4: 18th Design for Manufacturing and the Life Cycle Conference; 2013 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications · 2013
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of Manitoba
FundersNational Science Foundation
KeywordsFlywheelLife-cycle assessmentInventory analysisProduct (mathematics)Manufacturing engineeringComputer scienceProcess (computing)Product lifecycleOperations researchEngineeringProduction (economics)Automotive engineeringNew product developmentMathematics

Abstract

fetched live from OpenAlex

Heavy duty machines consume a tremendous amount of energy during their life cycle. Therefore, designing an energy efficient machine is of great importance. This paper presents a method for the comparative life cycle assessment (LCA) of two different types of press machines: servo press and flywheel press to understand quantitatively the environmental emissions during their life cycles. To make a fair comparison of the two machines, the same amount of production is used as the basis for comparison. Assessment scopes and boundaries are defined first, then detailed product structures and manufacturing processes are investigated. After data collection from visiting enterprises, related project reports, academic papers, and commercial software databases, analysis of the life cycle inventory is performed. Comparative inventory tables for each life cycle stages and whole life cycle are presented. The results of the study can be used for decision making during the product purchase, planning and design process.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.713
Threshold uncertainty score0.981

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 head0.051
GPT teacher head0.291
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueVolume 4: 18th Design for Manufacturing and the Life Cycle Conference; 2013 ASME/IEEE International Conference on Mechatronic and Embedded Systems and ApplicationsSame topicManufacturing Process and OptimizationFrench-language works237,207