Building Information Modeling (BIM) 'Best practices' project report: An investigation of 'best practices' through case studies at regional, national, and international levels
Bibliographic record
Abstract
Building Information Modeling (BIM) involves a new approach to project delivery that focuses on developing and using an information‐rich model of a facility to improve the design, construction and operation of a facility. Many projects have now successfully implemented BIM with significant benefits, including increased design quality, improved field productivity, cost predictability, reduced conflicts and changes, and reduced construction cost and duration to name a few. However, successful implementation of BIM requires drastic changes in the organization of work that cannot be achieved without redefining work practices, which might explain the slow adoption rate, particularly in Canada. The mandate of this research project was to investigate BIM ‘best practices’ for the Canadian industry to better understand what is working and what might be the obstacles. The research team identified seven projects at regional, national and international levels and analyzed these projects along three dimensions: Technology, Organization and Process. It is our belief that successful implementation of BIM requires a balance between these three dimensions. We also investigated existing BIM guidelines and standards to see how other countries are driving BIM adoption and measuring the return on investment. <br/><br/>The following highlights some of the ‘best practices’ identified along the three dimensions: <br/>Technology <br/>• Owner: specify clear, complete, and open requirements. • Owner/Project Team: determine uses/purposes of the model. • Owner/Project Team: determine the scope of the model and the level of detail of the modeling effort required to support each purpose.<br/><br/> Organization<br/> • Owner: rethink the organizational structure/practices for managing its construction projects and real estate portfolio. • Owner/Project Team: early involvement of all key disciplines is essential. • Owner: implement the appropriate incentives to enable collaborative BIM. <br/><br/> Process<br/> • Owner/supply chain: devise and agree on shared goals regarding what is expected to be achieved. • Supply chain: devise and agree on a BIM execution plan. • Supply chain: clearly define roles and responsibilities including handoffs between disciplines.<br/><br/>This report demonstrates that although BIM is quite new in the Canadian landscape, there already exists an abundance of information (guidelines and standards) from other countries, which we can leverage to advance BIM adoption in Canada. The UK initiative, in particular, provides an excellent example of a thoughtful, deliberate and well‐resourced process that the government initiated to investigate the appropriate application of BIM for public projects, and to develop a long‐term strategy for how to help the industry make the transition to this new way of working. Our intent with this report was to first capture the essence of these international efforts to make sense of and document how BIM is changing our industry; and second, to make knowledge tangible through the description of cases that outline some or many of these best practices while also presenting lessons learned. There are still major challenges ahead, particularly in terms of procurement and education. To reap the full benefits of BIM, contracts encouraging collaboration and partnership such as Integrated Project delivery (IDP) should be adopted. Proper training at the university and professional levels has to be initiated. BIM has to be built around trust and sharing. The government of Alberta is leading the way in Canada in its initiatives to support its industry in adopting BIM, involving universities to participate in this process. Additional efforts are needed to develop a strategy for driving BIM adoption, continue to document emerging best practices in Canadian BIM projects, and to develop and formalize tools to help industry measure their performance and maturity in using BIM.
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How this classification was reachedexpand
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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".