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BFRL Program
Construction Integration and Automation Technologies
This program was initiated with the investigation of the challenges and evolving technologies which might be applicable for construction integration and automation. The program strategy is to develop, in parallel, metrics for multifactor construction productivity, real-time control, and data model characterization. These new metrics will be applied to high priority tasks and technologies identified in collaboration with industry. Those specific tasks and technologies will serve as test cases for evaluating the application of the measurement science in the Intelligent and Automated Construction Research Testbed.
BFRL is developing and using baseline measures and data on project cost, schedule, and field rework to identify tasks and processes (e.g., automated assembly, materials tracking) for targeting breakthrough improvements in construction productivity. BFRL is partnering with the Construction Industry Institute (CII), to measure how combinations of industry best practices and automation and integration technologies impact task and project productivity. In collaboration with the Bureau of Labor Statistics, BFRL is using a multifactor productivity approach to produce industry-level metrics for selected construction industry sectors (e.g., steel erection). Multifactor productivity metrics enable separable estimates of the contribution of labor, capital, and technology.
The U.S. manufacturing industry has successfully developed integration and automation technologies to gain real-time control of its processes, resulting in increased productivity, decreased time-to-market of new products, and greater customer satisfaction. The U.S. construction industry has tried to employ many of these same technologies but with only limited success. A key contributor to this failure is the lack of an overall conceptual framework and supporting reference model architecture for the end-to-end monitoring and control of the construction process. NIST will adapt its open and scalable reference model architecture for real-time control systems (RCS) to support the construction domain’s loosely-coupled, distributed system components and arbitrary mixes of automated and manual task work. To achieve this level of monitoring and control, NIST is developing the enabling measurement science and performance metrics for evaluating individual sensors (e.g., 3D imaging, calibrated camera networks, RFID, ultra-wideband tracking), construction object recognition and tracking algorithms, and combined real-time sensing and control systems for maintaining robust situational awareness of cluttered and dynamic construction sites.
One of the features of the construction industry’s complexity and variability is the extraordinarily large number of highly diverse information systems that are used over the lifecycle of the built product. BFRL is developing and evaluating data model characterization techniques and measurement science to determine commonalities, differences and alignment mechanisms for enabling interoperability and integration. BFRL is also developing measurement science to enable validation of data models and data exchange protocols, conformance assessment of construction information systems and interoperability testing, with the ultimate goal of enabling automated access to and integration of those systems.
BFRL is developing an Intelligent and Automated Construction Research Testbed to demonstrate and transfer the resulting productivity metrics and tools to industry. In addition, industry, academia, and other research organizations are partnering with BFRL to use the testbed for measuring the productivity impacts of new construction technologies and processes, and for testing new construction standards and protocols. The capabilities of the testbed under development include: world-class sensing for monitoring real-time status of construction processes; control of construction equipment and processes (real, scaled, and simulated); advanced communication and information exchange; and modeling, simulation and visualization. The Intelligent and Automated Construction Research Testbed will enable the transfer of construction productivity measurement science to the field, which will enable industry to develop best practices, protocols, and standards to achieve breakthrough improvements in productivity.
Component Projects:
Construction Control Using 3D Imaging and Building Information Models
Methods and Metrics for Conformance Testing of Construction Project Data Standards
- Data Model Characterization and Alignment (joint project proposed by BFRL with MEL, EEL and ITL)
Contact:
Mark Palmer
(301) 975-5858
mark.palmer@nist.gov
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Last updated: 8/5/2009