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Record W2097930904 · doi:10.1177/0037549712459772

Assessing design process in engineering consultancy firms using lean principles

2012· article· en· W2097930904 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

VenueSIMULATION · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsConcordia University
Fundersnot available
KeywordsInterconnectivityProcess (computing)Process managementLean project managementManufacturing engineeringDesign processLean manufacturingComputer scienceEngineering design processProcess designSystems engineeringEngineeringBusinessWork in processOperations managementMarketing

Abstract

fetched live from OpenAlex

The aim of this research is to provide a tool for assessing the impact of applying lean principles to the design process at construction consultancy firms. Through several interviews, a comprehensive model was built to simulate the design process, using data from a leading consultancy firm in Egypt. The model contains the main processes and activities that form different phases of the design process and depicts the interconnectivity of processes and activities needed to create a complete design package upon client request. The research describes how the five main lean principles are integrated in the model. A case study is considered to demonstrate the effect of using the proposed model on the design process and to illustrate how the design process performs differently when lean principles are introduced. Case study output analysis reveals 40% improvement in the lean process performance measured in terms of activity utilization rates.

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)0.002
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 score0.248
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.358
GPT teacher head0.459
Teacher spread0.100 · 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