Song Zhang, assistant professor of mechanical engineering, has been awarded a National Science Foundation grant to explore solutions for a growing need in manufacturing industries: a fast, accurate, and reliable way of inspecting parts.
The $200,000 grant will fund research to develop a high-speed 3D metrology method that can take real-time optical measurements of parts during the manufacturing process, streamlining inspections processes that are often mandated by government regulation.
Traditionally, Zhang explained, when manufacturers make parts only a sampling of them is inspected.
“The samples are perhaps one or two percent of the total,” Zhang said. “They inspect a sample, and then a statistical analysis tells them that, within a certain degree of probability, all the parts are good.”
Stricter government regulations will soon be requiring aerospace industries to inspect 100 percent of their manufacturing product.
“We want to find out if we can find a partial replacement for the coordinate measuring machine (CMM), which is a very slow, very expensive device and the current method for measuring manufacturing samples,” Zhang said. “If inspections can be done as part of the production line, optically instead of a sensor physically touching the object, we can complete inspections in milliseconds.”
Zhang expects the technology to have other industrial applications as well.
The research is a continuation of Zhang’s work to create high-resolution, superfast imaging and sensing technologies, which have applications in industry, medicine, security, biometrics, and entertainment.