MétaCan
Menu
Back to cohort
Record W2011994858 · doi:10.1080/00207540600857367

A case study in productivity-cost trade-off in the design of paced parallel production systems

2006· article· en· W2011994858 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

VenueInternational Journal of Production Research · 2006
Typearticle
Languageen
FieldEngineering
TopicAssembly Line Balancing Optimization
Canadian institutionsUniversity of Calgary
FundersNational Science Foundation
KeywordsMachiningNumerical controlThroughputFlexibility (engineering)Production lineVolume (thermodynamics)Production (economics)ProductivityComputer scienceEngineeringManufacturing engineeringReliability engineeringMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

This paper examines the investment and operational cost differences between high-volume serial CNC-based machining lines and parallel CNC-based machining lines. With the progress of CNC technology and their descending cost, more CNC machines have been used in high-volume production systems. CNC machines increase the flexibility and machining capability of production lines, greatly increasing the number of line configurations. Parallel configurations improve system throughput and have the same effect as adding buffers to a pure serial line but without additional work-in-process inventory. This analysis is performed through a case study of a CNC-based automotive cylinder head machining line. Examining machine reliability, line balance, configuration throughput, and cost yields insight into the cost-benefit tradeoff of implementing parallelism. It is found that even with large increases in investment in automated material handling, parallel configurations can yield significant annual cost savings over pure serial lines through reductions in capital investment, especially in CNC machines, and improvements in efficiency, and on a per unit capacity basis, parallel configurations are the least expensive.

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)0.007
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: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.087
GPT teacher head0.366
Teacher spread0.279 · 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