Using look-ahead plans to improve material flow processes on construction projects when using BIM and RFID technologies
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".