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Record W2003080771 · doi:10.1108/02656711011009281

Avoiding rework in product design: evidence from the aerospace industry

2010· article· en· W2003080771 on OpenAlexaff
Isabelle Dostaler

Bibliographic record

VenueInternational Journal of Quality & Reliability Management · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsConcordia University
Fundersnot available
KeywordsContext (archaeology)OriginalityNew product developmentProduct designEngineering design processEngineeringProduct (mathematics)Process managementAerospaceMarketingKnowledge managementOperations managementBusinessQualitative researchComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to present the results of a study commissioned by an aircraft producer that is concerned about the efficiency of its new product development process and the high number of engineering changes generated during aerospace programs. Design/methodology/approach The paper focuses on nine structural design projects and explores the factors explaining the inter‐project differences in the number of engineering changes required after the structural drawings are released to the methods department. The method of inquiry used in this paper combines questionnaire‐based measurement of design performance with in‐depth semi‐structured interviews of managers and designers. Findings The research results suggest that, in an industrial context where both time pressure and labour shortage are considerable, design practices such as functional diversity, intense communication, collocation and strong project leadership, are associated with higher design performance. Furthermore, in a specific organizational context where the design work is divided among various companies located in different regions, effective partner integration is another key success factor. Research limitations/implications Although the strength of the findings is inevitably limited by the small number of observations, the results raise some important questions about the effect of time pressure and labour shortage on product development performance. Practical implications The results suggest that design performance is likely to increase if the production sustaining phase is actively promoted within aerospace companies, since this activity provides designers with considerable learning opportunities. Originality/value Using sensitive internal data on engineering changes and rich qualitative material, this paper indicates how design performance can be improved in organizations that tend to rely on design rework and other safety nets to achieve their quality objectives and comply with industry regulations.

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)0.036
metaresearch head score (Gemma)0.145
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.145
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0030.005
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.206
GPT teacher head0.458
Teacher spread0.251 · 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

Citations20
Published2010
Admission routes1
Has abstractyes

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