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Record W1997469376 · doi:10.1088/1757-899x/26/1/012016

Design for Manufacturing – One-Piece, Fibre-Placed Composite Helicopter Tailboom

2011· article· en· W1997469376 on OpenAlexaff
Catharine Marsden, R.C. Fews, P W J Oldroyd, AH Yousefpour

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsNational Research Council CanadaBell Helicopter Textron (Canada)
Fundersnot available
KeywordsAerospaceManufacturing engineeringAutomotive industryAutomationQuality (philosophy)Advanced manufacturingEngineeringProcess (computing)New product developmentCertificationComputer scienceMechanical engineeringBusiness

Abstract

fetched live from OpenAlex

Recurring cost has become a critical driver in the design of helicopter airframes, and although composite materials have become widely used in aircraft structures, the hand lay-up manufacturing process in many cases prevents these applications from being cost-effective. Automated manufacturing technologies promise not only reduced production costs but also higher quality, repeatable parts. The introduction of existing automated manufacturing techniques and technologies from industries such as the automotive sector into aerospace can be challenging due to the unique product characteristics as well as the stringent certification and quality control requirements of the industry. The aerospace industry is a low-volume, high value production environment where "hand-made" products are produced by highly experienced and qualified trades-people. Both metallic and composite components are subjected to precise manufacturing control and documentation requirements. The introduction of automated manufacturing technologies must be done in such a way as to respect these often demanding constraints. The introduction of automation to industrialized processes impacts not only the way parts are produced, but also the way they are designed. Successful composite design and manufacturing automation in the aerospace industry requires the engineering designer and analyst to become increasingly involved in the manufacturing of the product, as machine limitations and producibility become increasingly important drivers for design. This paper presents an overview of a development project intended to evaluate the effectiveness and benefits of the automated fibre placement technology through the design, prototype build and testing of a composite tailboom. The discussion centres on the "design for manufacturing" concept and provides a perspective on the project objectives, material and process selection and trade-offs, geometric and structural considerations, and component assembly and fastening.

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)0.000
metaresearch head score (Gemma)0.000
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.202
Teacher spread0.173 · 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
GenreMethods

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

Citations9
Published2011
Admission routes1
Has abstractyes

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