Collaborative Research: FW-HTF-RM: Human-in-the-Lead Construction Robotics: Future-Proofing Framing Craft Workers in Industrialized Construction 

PI (Alwisy), 2023/10 - 2026/09

Total Budget: $963,165

Collaborative Research. UF Lead  Organization ($699,570), Penn State ($263,595).

https://www.nsf.gov/awardsearch/showAward?AWD_ID=2326159&HistoricalAwards=false

Industrialized construction (IC) can address the pressing productivity and safety issues facing the construction industry by transferring many tasks to offsite manufacturing facilities that leverage the power of advanced robotic technologies. However, highly customizable building designs, the inherent variability in construction materials, and labor-intensive construction tasks complicate the integration of traditional craftwork and robotic automation. This research aims to address these challenges by introducing a revolutionary approach to human-robot collaboration, named Human-in-the-Lead Construction Robotics (HiLCR). The proposed HiLCR empowers craft workers to take the lead in industrialized tasks that require design-making or fine motor control, while leveraging the fundamental physical capacities of industrial robotic arms in a support role. HiLCR will ensure that advanced technologies and machines serve as tools that nourish the ingenuity of craft workers instead of suppressing it. This balanced approach of HiLCR will help future workers overcome the looming crisis of job loss to machines, one of the greatest workforce fears caused by the current trends in automating human-centric tasks. Furthermore, HiLCR can reduce potential physical barriers to entry into the construction industry by delegating manual work that requires certain physical abilities, such as hand dexterity and lifting of materials, to the robotic system. 

With $2.5 Million in Strategic Funding Million from Autodesk, UF Plans to Advance the Field of Industrialized Construction Engineering 

University of Florida faculty and students will help advance the field of industrialized construction engineering with $2.5 million in strategic funding from the office of UF President Ben Sasse. 

Working together, UF’s College of Design, Construction and Planning, and the Herbert Wertheim College of Engineering will seek to revolutionize how the world conceptualizes, designs, and builds affordable and resilient buildings and civil infrastructure. 

“The construction and engineering industries are rapidly changing with advances in technology, and we need to adapt and evolve to keep up with that pace,” Sasse said. “The Industrialized Construction Engineering (ICE) project will help UF’s experts use tools like artificial intelligence (AI) and robotic automation to transform the way we design and build.” 

The College of Design, Construction and Planning will use its future 50,000-square-foot Bruno E. and Maritza F. Ramos Collaboratory to harness the power of AI, design automation, and robotic construction to enhance productivity, safety, and quality in residential and commercial construction. 

“This funding gives us an excellent opportunity to partner with the College of Engineering to make UF the premier institution for industrialized construction,” said Chimay Anumba, Ph.D., dean of the College of Design, Construction and Planning. “There will be huge societal benefits as we can tackle productivity, safety, quality, and resilience issues in the construction project delivery process.” 

UF’s Center for Advanced Construction Information Modeling and the Smart Industrialized Design and Construction Lab will expand their educational offerings and research related to emerging technologies for the design, construction, and maintenance of civil infrastructure.  

“The Industrialized Construction Engineering program represents a pioneering, multidisciplinary initiative that will revolutionize the construction sector by reconceptualizing education, research, and industry outreach,” said Aladdin Alwisy, Ph.D., the director of the Smart Industrialized Design and Construction Lab.

https://news.ufl.edu/2024/01/advancing-construction-engineering/

Robots Lend a Helping Hand

DCP - PERSPECTIVE - Alumni Magazine 

The first thing most people think about robots and Artificial Intelligence (AI) is the technology will replace the need for humans in the workforce. However, that is not the case in Dr. Aladdin Alwisy’s Smart Industrialized Design and Construction (IDC) Lab.

Dr. Alwisy, an assistant professor in the M.E. Rinker, Sr. School of Construction Management, aims to have his patented robotic technology work as a supplement to humans, not replace them.

“We don’t want a fleet of robots to come and take over human jobs,” Alwisy said. “We want to find balance between robots and the job and make sure we improve productivity without losing human jobs.”

Alwisy’s strategy is the opposite of the automotive industry. Instead of mass production with each robot having a specialized task, he focuses on his robots being multifunctional since the construction industry necessitates being flexible and agile. This strategy also comes with the bonus of being more cost-effective than the traditional assembly line.

“Instead of spending millions of dollars on a long production line to produce a wall panel or series of wall panels, the system that we have can do the exact same thing for less than half a million dollars,” Alwisy said. “Based on our preliminary estimates, the return on investment can be as early as three to six months.”

"Read more at DCP alumni magazine, Perspective!" 

DCP, UF Engineering Sign Agreement with Autodesk Inc. to Drive Student Success and Innovative Integration

UF students will benefit the most from Autodesk further enhancing their strategic partnership with DCP and Engineering. The $150,000 given to DCP will help the college develop micro-credential and regular courses on IC, eventually leading to a certificate and graduate degree in industrialized construction. The gift from Autodesk will also help fund peer mentors for UF Engineering’s First Year Design and Society course. 

https://dcp.ufl.edu/news/autodesk041123/

A BIM-based automation of design and drafting for manufacturing of wood panels for modular residential buildings 

This research introduces a systematic methodology for automating the drafting and design for manufacturing of wood-framed panels for modular residential buildings. It utilizes 2D computer-aided design (CAD) drawings to automatically generate BIM and construction manufacturing BIM; subsequently, shop drawings for the wood-framed panels are developed according to the platform framing method. The proposed framework is incorporated into a computer application called MCMPro, which is developed using visual basic application within CAD environment. Reduced design cost, improved layout accuracy and enhanced productivity are expected advances of MCMPro. 

This research utilizes survival analysis and the Cox proportional-hazards regression (CPHR) to analyze condo sales data provided by the REALTORS® Association of Edmonton (RAE) (Alberta, Canada).

The analysis of the provided data shows that the listed price, building age, appliances, and condo fees have less effect on the time a condo spends on the market compared to the condo’s physical features, such as construction material, interior finishing, heating type and source. 

The proposed TCEng is utilized during the design stage to evaluate the available energy systems, and the selected energy system will be monitored during building operation in order to verify and modify TCEng. Advances are expected in terms of reduced fuel consumption, reduced CO2 emissions, and promotion of automation in building construction.

The proposed research establishes novel solutions for the standardization of best practices by front-loading the 3D-virtual model with information, where a comprehensive model of the project is developed dynamically and interactively as the design/construction matures. Advances are expected in terms of increased productivity, enhanced automation, materials optimization, and the mitigation of risks throughout the manufacturing and construction process.