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Record W4285099169 · doi:10.18280/jesa.550307

Present and Future Impacts of Computer-Aided Design/ Computer-Aided Manufacturing (CAD/CAM)

2022· article· en· W4285099169 on OpenAlexvenueno aff
Peter P. Ikubanni, Adekunle Akanni Adeleke, O.O. Agboola, Chiebuka T. Christopher, Boluwatife S. Ademola, Joseph Okonkwo, Olanrewaju Seun Adesina, Peter Omoniyi, Esther T. Akinlabi

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2022
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsCADComputer-aided manufacturingComputer Aided DesignManufacturing engineeringShipbuildingComputer-aided technologiesEngineeringProduct designAerospaceProduct (mathematics)Computer scienceEngineering drawingMechanical engineering

Abstract

fetched live from OpenAlex

The world is a growing place with great technological advancement in all areas of life. For some decades now, various disciplines and industries have been engaged in using Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM) across different nations. CAD/CAM utilizes computers to integrate design and manufacturing processes for quality product attainment. This review article examined the present impacts of CAD/CAM on some sectors such as architecture, manufacturing, engineering and design, electronics, automobile, shipbuilding, aerospace, and medicine. Highlights on some applications and future impacts of CAD/CAM have also been discussed. The numerous impacts of CAD/CAM are discussed in the study. It was concluded that CAD/CAM had become integral parts of our world to ease production against traditional methods. The study recommended more research focus on biomaterials for 3-D bioprinting for tissue engineering applications.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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 designOther design
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

Citations21
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal Européen des Systèmes AutomatisésSame topic3D Printing in Biomedical ResearchFrench-language works237,207