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Production Routes for Impact Extruded Aluminum Parts for the Automotive Industry

2016· article· en· W2521832357 on OpenAlexaff
Alexander Wimmer, Bernhard Schwarz

Bibliographic record

VenueKey engineering materials · 2016
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsImpact
Fundersnot available
KeywordsAutomotive industryCompetitor analysisProduction (economics)RivalryWork (physics)Manufacturing engineeringProcess (computing)Technological changeBusinessComputer scienceEngineeringMechanical engineeringEconomics

Abstract

fetched live from OpenAlex

In the past months due to decreasing fuel prices the brisance of light weight design got lost, however climate change is still continuing and there is an increasing demand for aluminum parts for mobile applications. There is a strong rivalry between well-known materials such as aluminum, steel and plastic, however technical progress features new materials such as carbon fiber laminates (CFK). New competitors in North America and China are increasing the cost pressure, which requires further process optimizations. In this work different fabrication methods for impact extruded parts are analyzed and economical and technological aspects are compared. A comparison between traditional and state-of-the-art production routes is done. Based on an input-output analysis the alternatives are compared by economic and ecologic aspects, allowing a substantiated examination. Through the comprehensive analysis, options for technological optimizations are revealed to attenuate disadvantages of alternatives with economic advantages, ensuring technological leadership.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.568

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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 designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

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