AI and Machine Learning

Artificial intelligence in construction can improve productivity

Researchers at Texas A&M University are working to bring artificial intelligence (AI) to the construction industry, which has the lowest productivity rate of any manufacturing industry.
By Deana Totzke November 8, 2019
Courtesy: CFE Media

Researchers at Texas A&M University are working to bring artificial intelligence (AI) to the construction industry. The construction industry is booming and is one of the largest global industries, employing 7% of the world’s workforce and contributing more than $10 trillion annually to the world economy. However, it has the lowest productivity of any manufacturing industry due to labor-intensive jobs that have significant safety risks and rising costs of materials. Texas A&M University researchers have received a planning grant from the National Science Foundation (NSF) to prepare for bringing AI to the construction industry.

Dr. Zachary Grasley, director of the Center for Infrastructure Renewal (CIR) and professor in the Zachry Department of Civil and Environmental Engineering at Texas A&M, said new AI technologies have the potential to address many of the major challenges the construction industry faces, leading to a positive, economic and social impact. He believes AI is poised to revolutionize the construction industry similarly to how the assembly line revolutionized the automobile industry, leading to significant cost reductions, higher productivity and safer, better-paying jobs.

“There’s a lot of opportunity there, not only in terms of safety and in automating difficult tasks,” Grasley said. “Artificial intelligence can significantly help as we develop new materials and new methods of construction, like 3-D printing of structures, for instance. It opens the door to the optimization of both materials and structural design in a way that we’ve never done before.”

The Planning Grants for Engineering Research Centers competition is the first step to bringing AI to the construction industry. The competition was run as a pilot solicitation within the NSF Engineering Research Center (ERC) program and is intended to build capacity among teams to plan for convergent, center-scale engineering research.

Grasley’s $100,000 year-long planning grant will support the development of a research roadmap for implementing AI into the construction industry and the formation of a multi-institutional team working toward an ERC.

“ERCs are one of the largest grants that the National Science Foundation gives out to support game-changing, large-scale initiatives that transform society in some way, shape or form,” Grasley said. “The ERC grants are so large in scope, that in order to write a competitive proposal for them, you really have to start well in advance building a team, defining the theme, road-mapping and identifying the right industrial and academic partners.”

With the grant, Grasley said he and his team will create a 10-member advisory board of experts in AI, construction industry leaders and government representatives to identify and define their objectives. They will also hold a symposium on AI in construction to develop the roadmap to achieve the ERC vision and identify the academic partners. Finally, they will have a writing workshop to produce an outline of the proposal.

With the grant and other advantages they currently have at Texas A&M, Grasley feels they have a good chance of receiving the ERC from the NSF.

“The CIR is a brand-new, state-of-the-art center, and because of the size of our engineering program, the fact that we have the Texas A&M Transportation Institute, and such a large construction science department and civil engineering department, we have the breadth of expertise, particularly on the construction side, that no place else has across the country,” Grasley said. “We also have great connections to the construction industry, and it’s part of the CIR mission to develop technologies that will actually go out and be used and impact society through transforming the construction industry.”

Texas A&M University

www.tamu.edu

– Edited by Chris Vavra, associate editor, Control Engineering, CFE Media, cvavra@cfemedia.com.


Deana Totzke
Author Bio: Deana Totzke, Texas A&M University