BIM for Facility Management: Design for Maintainability with BIM Tools
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.
Bibliographic record
Abstract
BIM for Facility Management: Design for Maintainability with BIM Tools R. Liu, R. R. A. Issa Pages 321-328 (2013 Proceedings of the 30th ISARC, Montréal, Canada, ISBN 978-1-62993-294-1, ISSN 2413-5844) Abstract: As Building Information Modeling (BIM) becomes widely adopted by the construction industry, it holds undeveloped possibilities for supporting Facility Management (FM). Some FM information systems on the market claim to address the needs for FM requirement. However, the question of whether the functionalities provided by the current BIM-based FM software companies are those actually required by the FM Professionals still need to be answered. The data is required by FM professionals in the operation and maintenance phases of facilities and type of maintainability problems that frequently occur, which can be solved early in design phase, have not yet been addressed. The aim of this paper is to clarify the frequently occurring maintainability problems and to investigate the potential areas that can use BIM technology to solve the maintenance problems in early the design phase. A survey was conducted to collect perspectives from the industry practitioners for the maintenance problems and their frequency. The survey results indicated that maintainability considerations should be taken into consideration during the facility design phase. The results also address the perceived areas by practitioners that need maintainability consideration in design phase. Keywords: Building Information Modeling, Facility Management, Design for Maintainability DOI: https://doi.org/10.22260/ISARC2013/0035 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it