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Record W1537491965 · doi:10.1109/icsmc.1996.571284

Modeling and analysis of flexible fixturing systems for agile manufacturing

2002· article· en· W1537491965 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsClampingFlexibility (engineering)ObstacleAgile software developmentConstraint (computer-aided design)Process (computing)Manufacturing engineeringEngineeringAgile manufacturingKey (lock)Computer scienceIndustrial engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Manufacturing systems must provide flexibility and rapid response to market demands. Flexible fixturing is a key technology in the integration of agile manufacturing systems and the lack of effective flexible fixturing can be a significant obstacle to implementation. This paper highlights portions of our research dealing with fixturing systems for agile manufacturing. We apply the spatial point contact constraint theory to develop a mathematical model of flexible fixturing systems. The process of locating and clamping by fixturing systems is described. A representation is obtain for the locating and clamping matrix. Conditions and criteria for a deterministic location, clamping total constraint, accessibility and detachability are obtained. Location errors for the workpiece-fixturing systems are analyzed and the error gain matrix is derived. Illustrative examples are shown using this methodology.

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 score0.731
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.021
GPT teacher head0.211
Teacher spread0.190 · 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

Quick stats

Citations26
Published2002
Admission routes1
Has abstractyes

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