MétaCan
Menu
Back to cohort
Record W4213009345 · doi:10.30958/ajte.9-1-1

Flexible Robot Programming using Solid Edge’s “Alternative Assemblies”

2022· article· en· W4213009345 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAthens Journal of Τechnology & Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsCADRobotTask (project management)Enhanced Data Rates for GSM EvolutionComputer scienceEngineering drawingSoftwareTree (set theory)Computer Aided DesignManufacturing engineeringEngineeringSystems engineeringArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

Many assembly processes in small and medium-sized enterprises are still performed by human labour. One reason for this is the need for another expert to program the robot, which would simply not fit into the company structure. To address this issue a solution is developed, which allows to program the robot directly out of the CAD software. The positions of the parts are read out of the CAD file. Specific assembly instructions have to be given by the assembly developer and integrated in the tree structure of the CAD. To avoid collisions and ensure correct insertion angles, additional waypoints are given by alternate assemblies, a functionality within Solid Edge to create and use variations of an assembly. Keywords: assembly, task planning, intelligent and flexible manufacturing, CAD

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.

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 score0.500
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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