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Record W3034774777 · doi:10.1108/ci-11-2019-0133

Using look-ahead plans to improve material flow processes on construction projects when using BIM and RFID technologies

2020· article· en· W3034774777 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

VenueConstruction Innovation · 2020
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWorkflowBuilding information modelingWorkflow technologyComputer scienceWorkflow engineSystems engineeringProcess (computing)Information flowBusiness processWorkflow management systemProcess managementSoftware engineeringEngineeringDatabaseOperations managementWork in process

Abstract

fetched live from OpenAlex

Purpose Building information modelling (BIM) and radio frequency identification (RFID) technologies have been extensively explored to improve supply chain visibility and coordination of material flow processes, particularly in the pursuit of Industry 4.0. It remains challenging, however, to effectively use these technologies to enable the precise and reliable coordination of material flow processes. This paper aims to propose a new workflow designed to include the use of detailed look-ahead plans when using BIM and RFID technologies, which can accurately track and match both the dynamic site needs and supply status of materials. Design/methodology/approach The new workflow is designed according to lean theory and is modeled using business process modeling notation. To digitally support the workflow, an integrated BIM-RFID database system is constructed that links information on material demands with look-ahead plans. The new workflow is then used to manage material flows in the erection of an office building with prefabricated columns. The performance of the new workflow is compared with that of a traditional workflow, using discrete event simulations. The input for the simulations was derived from expert opinion in semi-structured interviews. Findings The new workflow enables contractors to better observe on-site status and differences between the actual and planned material requirements, as well as to alert suppliers if necessary. The simulation results indicate that the new workflow has the potential to reduce the duration of the material flow processes by 16.1% compared with the traditional workflow. Research limitations/implications The new workflow is illustrated using a real-world-like situation with input data based on expert opinion. Although the workflow shows potential, it should be tested on a real-world site. Practical implications The new workflow allows project participants to combine detailed near-term look-ahead plans with BIM and RFID technologies to better manage material flow processes. It is particularly useful for the management of engineer-to-order components considering the dynamic site progress. Originality/value The research improves on existing research focused on using BIM and RFID technologies to improve material flow processes by showing how the workflow can be adapted to use detailed look-ahead plans. It reinforces data-driven construction material management practices through improved visibility and reliability in planning and control of material flow processes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.034
GPT teacher head0.239
Teacher spread0.205 · 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