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Record W1912722213 · doi:10.1109/isee.2001.924540

Analysis of remanufacturer waste streams for electronic products

2002· article· en· W1912722213 on OpenAlexaff
Julie Ann Stuart Williams, L. H. Shu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRemanufacturingReuseProduct (mathematics)Automotive industryElectronic equipmentDesign for the EnvironmentManufacturing engineeringProduct designElectronic wasteEmbodied energyElectronicsComputer scienceWaste managementEngineering

Abstract

fetched live from OpenAlex

The long-term goal of this work is to enable design of durable products that facilitates remanufacture. Remanufacturing, or recycling at a part level, involves the production-batch disassembly, restoration to like-new condition and reassembly of used products. Remanufacturing offers significant environmental benefits by retaining the energy, as well as material, embodied in the product during original manufacture, while diverting solid waste from landfills. Since the essential goal of remanufacture is to reuse parts, parts that are not reused enter the waste streams of remanufacturers and represent the ultimate obstacles to remanufacture. Study of these waste streams reveals insights about difficulties in remanufacture and how to avoid these difficulties through product design. Traditionally, remanufacturing has centered on products such as automotive parts and electrical motors, However, the growth in electronic and electrical product sectors has triggered a corresponding growth in the remanufacturing in these sectors. To support design for remanufacture in these sectors, waste streams of remanufacturers of different electronic products, namely laser-printer toner cartridges and telephones, were studied and quantified. This paper presents the results of these waste-stream analyses, including the identification of discard reasons, associated root causes for these discard reasons, and consequently, product design and other characteristics that are problematic for remanufacturing.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.999

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)0.0010.000

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 head0.222
Teacher spread0.210 · 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

Citations22
Published2002
Admission routes1
Has abstractyes

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