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Record W2000920588 · doi:10.1108/14725961111148117

The influence of work‐cells and facility layout on the manufacturing efficiency

2011· article· en· W2000920588 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Facilities Management · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceProduct (mathematics)Work (physics)Order (exchange)Quarter (Canadian coin)Cellular manufacturingIndustrial engineeringManufacturing engineeringBusinessEngineeringMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to analyse the use of a product‐oriented layout and a work‐cell strategy in order to maximise efficiency. These two categories of layout strategies are discussed separately, and are then used collectively in an analysis of the company. The aim is to understand how improvements on layout design could positively impact the future efficiency of the case study company. Design/methodology/approach A model was developed and measured using 26 weeks of data between the fourth quarter of 2009 and the first quarter of 2010 during layout transformations at the case study company based in upstate New York. The model compared variables such as the distance traveled to retrieve parts, average daily output of engines, labour cost per unit produced, and the amount of time the engine remains in each cell; the aim of which is to increase the efficiency of the facility. Findings The findings indicate that there is a strong correlation between the variables improved at both the cell‐structures and the product‐structures of the facility and the overall efficiency of the manufacturing facility itself. The results also show that an overall higher efficiency allows for the facility to handle much larger workloads and also drives down both short‐run and long‐run costs. The outcomes also allow for a suggestive redesign of the facility in order to further maximise efficiency. However, it was found that the amount of time a product remains in each cell on the assembly line does not have an effect on the overall output of diesel engines. Research limitations/implications Various studies have been conducted focusing on the “facility layout problem,” yet thorough analyses of the redesigning of layout in regards to efficiency are not as available. Instead, an understanding of the topic was derived through sources focusing on the specificities of manufacturing layout. Originality/value This paper describes layout efficiency through redesigns and layout using work‐cells in a product‐oriented environment. This study would be useful to manufacturers having low variability in their product and having the ability to use work‐cell layout within their facility.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.236

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 head0.016
GPT teacher head0.185
Teacher spread0.170 · 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