02/19/2022
CAN ROBOTS SOLVE THE AFFORDABLE HOUSING CRISIS?
The technology, after all, would seem to have wide-ranging appeal to potential customers: radically lower costs thanks to savings on labor and materials, and a construction window measured in weeks (or even days) rather than months. Some have speculated it could be the solution to the country’s affordable housing crisis by providing a quick infusion of lower-priced homes in areas starved for housing inventory.
Some affordable housing experts, however, caution that the technology is not a panacea.
3D-printed homes won’t solve the problem of homelessness, but they are another “tool in the toolbox for housing development,” said Dee Walsh, chief officer of strategic development for the national affordable-housing nonprofit Mercy Housing, based in Denver.
“The cost to build housing and the amount of subsidy or low-cost financing available to make it affordable—there’s a gap there,” Walsh said. “We don’t have enough subsidy and soft financing to make traditional housing affordable. … The low markets are probably around $150,000 to $200,000 a unit; that would be in the Southeast U.S. In California, you’re looking at between $600,000 and $700,000 a unit to build an apartment. Clearly that’s not an affordable price for most folks.” That’s where 3D-printed houses come in.
While the words “3D-printed home” have understandably caught attention, a better term is additive manufacturing, says Bradley Rothenberg. Rothenberg is the CEO of nTopology, a software engineering company focused on enabling digital manufacturing. The key component that defines 3D-printing is the aspect of digital manufacturing, which builds from a 3D-solid model rather than from drawings. This kind of technology, Rothenberg said, is a “game changer.”
As with any technology, however, it has both limitations and potential. A net positive is less wasted material, which is more efficient and more cost-effective. On the flip side, it’s difficult to tell how the parts will perform. “It’ll take years to be able to tell,” Rothenberg said.