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Record W2128033157 · doi:10.24908/pceea.v0i0.5827

DESIGN OF A ROBOTIC ARM FOR TEACHING INTEGRATED DESIGN

2015· article· en· W2128033157 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldEngineering
TopicMechatronics Education and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRobotic armAutomationIntegrated designProcess (computing)SoftwareScalabilityComputer scienceElectronic design automationFocus (optics)Systems engineeringEngineering design processEmbedded systemEngineeringSoftware engineeringArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

Automation systems are generally made upof three main subsystems, namely mechanical, electricaland software. The interactions among these componentsaffect the integrated system in terms of reliability, quality,scalability, and cost. Therefore, it is imperative that thethree components of automation systems are designedconcurrently through an integrated design paradigm.This leads to the need to teach integrated design conceptsto students in programs such as process automation,electrical and computer engineering, and mechanicalengineering. However, due to the time constraint, it isalmost impossible to run full integrated design classprojects. Therefore, instructors have to decide on theparts of the design process that their class projects haveto focus on, and the parts that have to be reviewed for thecompleteness of the integrated design process. In thispaper we present the design and implementation of amicrocontroller based, 3D printable, low cost robotic armsuitable for teaching integrated design. Moreover, thepaper presents how the robotic arm design is used in anintegrated design project of an Industrial Networks andControllers course. Since the focus of this course is theelectrical and software subsystems of the robotic arm,and we do not have enough time to do a full design,students review the design of the robotic arm presented inthis paper and use it to either 3D print the robotic arm orpurchase the mechanical subsystem of the robotic armthat meets the specification.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.022
GPT teacher head0.227
Teacher spread0.206 · 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