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Record W2075302088 · doi:10.1108/01443570610678666

Production system design elements influencing productivity and ergonomics

2006· article· en· W2075302088 on OpenAlexaff
Patrick Neumann, Jörgen Winkel, Lars Medbo, Rutger Magneberg, Svend Erik Mathiassen

Bibliographic record

VenueInternational Journal of Operations & Production Management · 2006
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsProductivityWork systemsWorkloadHuman factors and ergonomicsComputer scienceWorkstationWork (physics)Operations managementManufacturing engineeringProcess managementIndustrial engineeringPoison controlBusinessEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to investigate a strategic change from parallel cell‐based assembly (old) to serial‐line assembly (new) in a Swedish company with special reference to how production system design elements affect both productivity and ergonomics. Design/methodology/approach Multiple methods, including records and video analysis, questionnaires, interviews, biomechanical modelling, and flow simulation were applied. Findings The new system, unlike the old, showed the emergence of system and balance losses as well as vulnerability to disturbances and difficulty handling all product variants. Nevertheless, the new system as realised partially overcame productivity barriers in the operation and management of the old system. The new system had impaired ergonomics due to decreased physical variation and increased repetitiveness with cycle times that were 6 per cent of previous thus increasing repetitiveness, and significantly reducing perceived influence over work. Workstations' uneven exposure to physical tasks such as nut running created a potential problem for workload management. The adoption of teamwork in the new system contributed to significantly increased co‐worker support – an ergonomic benefit. Practical implications Design decisions made early in the development process affect both ergonomics and productivity in the resulting system. While the time pattern of physical loading appeared to be controlled by flow and work organisation elements, the amplitude of loading was determined more by workstation layout. Psychosocial conditions appear to be affected by a combination of system elements including layout, flow, and work organisation elements. Strategic use of parallelisation elements in assembly, perhaps in hybrid forms from configurations observed here, appears to be a viable design option for improved performance by reducing the fragility and ergonomic problems of assembly lines. Originality/value The interacting design elements examined here pose potential “levers” of control by which productivity and ergonomics could be jointly optimised for improved total system performance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations126
Published2006
Admission routes1
Has abstractyes

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