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Record W4367022492 · doi:10.1007/978-3-031-28839-5_38

Integrating Lean Management Principles into Human-Robot Collaboration in Disassembly Cell

2023· book-chapter· en· W4367022492 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

VenueLecture notes in mechanical engineering · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRemanufacturingReuseManufacturing engineeringLean project managementCircular economyRobotEngineeringProcess managementCost reductionProduct (mathematics)Process (computing)Lean manufacturingSystems engineeringBusinessKnowledge managementComputer scienceMarketingArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Integrating Industry 4.0 technologies into the circular economy has received much attention in the literature in recent years. Considering the ladder of lansink and circular economy technical cycle, reusing and remanufacturing are preferable to recycling. Disassembly is a crucial process in remanufacturing. Collaborative robots provide semi-autonomous disassembly and could enhance product remanufacturing considering the uncertainties, cost reduction, and circularity of materials. This paper aims to discuss the application of lean practices in a disassembly cell with operators-robots collaboration. A conceptual framework based on the house of lean is proposed to highlight the research perspectives on opportunities of lean philosophy in disassembly operation enabled with industry 4.0 technology.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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