Human-Centered Innovative Technology for Resilient Built Environment
M.E. Rinker, Sr. School of Construction Management University of Florida
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BIM-based Life Cycle Information Management
BIM-based Life Cycle Information Management
1. BIM and Digital Twin Implementation (GOAA Project), 2023
1. BIM and Digital Twin Implementation (GOAA Project), 2023
Objective:
The Embedded Research Project had the goal of streamlining capital project financial planning, proactively monitoring construction costs, and facilitating the integration of construction data into airport space management and facility management systems using BIM-enabled processes and technology.
Project results:
The team successfully developed BIM-enabled workflows, standards, and guidelines that included a financial digital twin framework for capital project planning, a BIM-enabled construction cost monitoring approach for pay application decision-making, BIM-GIS integration methods, and BIM-FM integration approaches. The project results laid the foundation for a push towards the implementation of an airport digital twin for the Orlando International Airport.
2. Facility Management System Automated Population from BIM
2. Facility Management System Automated Population from BIM
A survey was conducted in the AECO industry and included BIM authors (architects) and users (contractors) to validate the proposed initial list of metrics. The responses from the suts for the benchmarking system. In addition, an analysis of the differences in perception among different groups of respondents showed that out of 26 variables used, the perceived importance of 6 variables was statistically different between BIM authors and BIM users. This result indicates that the surveyed architects and contractors were in agreement with the importance level for most of the variables proposed including model usefulness, model economy, and model productivity. Future adjustments of the metric weights might be needed in the implementation based on the different intended purposes for the BIM models.
Distribution of Evaluation Variables (Liu et al. 2016)
BIM model performance metrics’ weights (Liu et al. 2016)
3. Common Knowledge in BIM-FM
3. Common Knowledge in BIM-FM
The total cost impact of inadequate transfer of information across phases was $15.8 B/ year, with two-thirds happening in the operation and maintenance (O&M) phase (NIST, 2014). There is a cost burden in repurchasing information developed and available in BIM for any specific facility. Efforts should be spent to reduce the data reentry and transfer from the BIM model to the operation software which will smooth the business process and improve the productivities for the O&M staff. As a result, the potential savings can become reality.
The total cost impact of inadequate transfer of information across phases was $15.8 B/ year, with two-thirds happening in the operation and maintenance (O&M) phase (NIST, 2014). There is a cost burden in repurchasing information developed and available in BIM for any specific facility. Efforts should be spent to reduce the data reentry and transfer from the BIM model to the operation software which will smooth the business process and improve the productivities for the O&M staff. As a result, the potential savings can become reality.
Research goals:
This study was among the first efforts in bringing the gaps of knowledge sharing throughout a building's life-cycle through a survey of industry practitioners. The aim was to clarify the frequently occurring maintainability problems and the data requirements of FM professionals for maintenance purposes. This study investigated the potential areas that can use BIM technology to solve the maintenance problems in the early design phase.
Results:
The industry practitioners believed that maintainability issues should be considered in the design and construction phases and they put forward the efforts to make it happen. The perceived areas determined by the survey would be a starting point for a BIM-FM knowledge sharing database. Maintainability problems are still frequently happens in facility management practice. Cooperation in the AECO industry is still segmented and different stakeholders are working in their own areas without sharing technology and information with others. BIM practices and technologies are needed to carry knowledge from the operation phase to the design and construction phases to better implement the design for maintenance (D4M) rules.
4. Design for Maintainability
4. Design for Maintainability
Research goals:
The purpose of this study is to investigate the design for maintenance accessibility (DFMA) method, and the opportunities offered by the application of building information modeling (BIM) software to accomplish this design.
Results:
This paper illustrated with a case study to transform the concept of "design for maintenance accessibility" into reality. Both Solibri Model Checker (SMC) and Revit Accessibility Checker Add-in were designed and tested. This paper proved that BIM tools were usefull to anticipate and sovle accessibility issues. Comprehensive maintainability checking in the design phase would result in a big savings in maintenance cost during a facility’s lifecycle.
Accessibility checking in SMC (Liu and Issa 2014)
Steps for accessibility checking in Revit Accessibility Checker AddIn (Liu and Issa 2014)
5. BIM Performance Benchmarking Assessment Application
5. BIM Performance Benchmarking Assessment Application
Research goals:
A cloud-based BIM performance benchmarking application, BIM Cloud Score (BIMCS) is proposed to collect BIM performance data from BIM users nationwide in order to allow BIM users to compare their BIM performance with the results collected from their industry peers.
Results:
Benchmarking, compared to internal evaluation, was found to be more helpful for BIM utilizers to make decisions for improvement plans. Twenty validated benchmarking metrics were used to quantify BIM utilization performance in terms of the BIM model (the product) and BIM modeling (the production). BIMCS is a community cloud environment that utilizes software as a service (SaaS) to make the collection, aggregation, and presentation of benchmarking data autonomous and interactive. Based on the Big Data collected from the BIMCS database, an overall view of the industry status quo of BIM utilization can be obtained, and ultimately, a protocol for BIM performance could be developed on the basis of this improved knowledge discovery process.
Architecture of BIM cloud score (Liu and Issa 2014)
BIM Benchmarking results in BIM (Liu and Issa 2014)
6. BIM and FM System Integration and Automation
6. BIM and FM System Integration and Automation
Research goals:
As the first step of development of BIM-supported project life cycle information management, this study aimed to bridge the communication gap between design and facility management professionals. It focused on automatic bidirectional communications between Computerized Maintenance Management Systems (CMMS) and BIM models on a database level. This study aimed to validate the feasibility of using BIM to populate facility maintenance software automatically through the database automation process. In addition, this study attempted to prove that this communication process could avoid unnecessary costs for facility owners.
Results:
With the process proposed above, the template is built once in Revit and it can be used repetitively without rebuilding in the succeeding projects if the FM software does not require different data. The template can be populated automatically and be ready to export. The case study summarized in this paper provides some evidence that BIM holds potentials for providing information and creating value for owners and facility management. Moreover, this paper identified the data attributes required for facility SMS and proposed a way to embed this attribute in BIM creation platforms.
Acknowledgement:
We would like to acknowledge and thank Fiatech to sponsor this project. The author specifically acknowledges the support of Aaron Farmer and Lance Marrano of the U.S. Army Corps of Engineers for their time and dedication to this research project.
Information loss in project life cycle stages (Liu and Zettersten 2016)
Relationships of Revit Classes (Liu and Issa 2012)
MEP Model and Shared Parameters Editing (Liu and Issa 2012)
References
References
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