Manufacturing gets a makeover
New faculty in advanced manufacturing revamp courses, bring research expertise to growing area in Nevada
A 2014 study by The Manufacturing Institute reported that while most American believe manufacturing is a critical part of a strong economy, it ranked dead last among Generation Y respondents as a possible career path. The number one career choice for participants aged 19-33 was technology.
Yiliang Liao, who received the Ralph E. Powe Junior Faculty Award this spring, joined the College in 2014.
A number of new faculty in the College of Engineering are looking to change that perception, combining technology-intensive approaches to manufacturing with an underlying belief in the innate coolness of being able to make things.
"If you don't have advanced manufacturing, you don't have novel products in everyday life," said Yiliang Liao, an assistant professor of mechanical engineering. "The designer can always design something fancy and it looks good, but if you don't have advanced manufacturing processes, you won't make it happen. People can dream big, but when you want to put it into practical application, it depends on the process you use."
Liao, who received the Ralph E. Powe Junior Faculty Award this spring, is one of a number of faculty in the College of Engineering hired for their research expertise in advanced manufacturing – an umbrella term for the use of new and innovative technologies to improve manufacturing processes and ultimately make better products.
Enhancing lightweight metals through manufacturing
Liao also brings experience in a growing area of expertise at the University: applications of lightweight metals. Together with Bin Li, an assistant professor of materials science and engineering, Liao is working on designing manufacturing processes that enhance the quality of lightweight metals.
Lightweight materials, such as magnesium alloys, have potential applications in the automotive and aerospace industries, where lighter materials translate into improved fuel efficiency and overall cheaper, greener products. But using these new materials in consumer-oriented products requires first understanding and then improving qualities such as strength, ductility and durability.
Bin Li has recently received two NSF-funded grants for work in advanced manufacturing.
For the past several years, Li has been working on better understanding the microstructure of magnesium alloys.
“Currently magnesium alloys are not used so extensively because technical barriers are still very high,” said Li, who in July received a National Science Foundation grant, his second in a year, to study twinning-induced plasticity in magnesium alloys. “This material is really complicated, so fundamentally we still don’t understand it very well.”
Liao, an expert in laser-based manufacturing processes, relies on Li’s expertise in materials characterization to design manufacturing processes that can enhance these properties.
“We’re trying to use advanced manufacturing techniques to improve the material’s properties,” Li said. “You can use the laser technique to change the microstructure of the materials, and the microstructure determines the properties, so if you know how to control the microstructure you can achieve the goals you want from the materials perspective.”
Computational methods can optimize manufacturing process design
According to a 2016 report by the White House, it takes anywhere from 10 to 20 years to get from the discovery of a new material and the ability to produce it in a laboratory to understanding it well enough to develop processes for use in commercial manufacturing. But, the report suggests, recent advances in modeling and computation can accelerate that timeline.
Li draws heavily on simulation and modeling in his research, a field known as computational materials science. He develops physics-based models of materials to project what kind of microstructure a particular manipulation might produce.
Li's modeling techniques can move from the electron and atomic scale up to the macroscale, enabling him to better understand how one particular component in a complex machine might perform over time. Using these modeling techniques, engineers can make precise predictions about when and how a particular component in a complex machine such as a car might fail.
"By integrating all these computational methods, we can optimize the design of the car component, even the whole car," Li said. "We use computational material science to solve engineering problems."
Nevada's economic diversification plan relies on advanced manufacturing as a key way to improve the state's economy, particularly in Northern Nevada. In response to employer demand, Li and Liao are integrating advanced manufacturing into their courses. The pair are also collaborating with other researchers on developing a minor in manufacturing. Both Liao and Li believe their students recognize the potential of manufacturing experience for their careers.
"In my class, students feel that manufacturing should be one of the major components for mechanical engineering students," Liao said. "They know it is important, otherwise they wouldn't take the class."
Driving progress in advanced manufacturing
Professor, Mechanical Engineering
Jiang studies how materials can better withstand external loads in engineering structures. Funded by the Department of Energy and the National Science Foundation, he has spent the past five years working on how lightweight magnesium alloys hold up under various cyclic loading conditions by microscopically examining the crystal structure and deformation under loading. Jiang’s study will provide insight into the quantitative relationship between the applied load and the material deformation, the dependence of the deformation behavior on the crystal orientations, and the relationship between the material performance and the microstructures inside the material.
Results from Jiang’s work on lightweight materials have been disseminated in high-impact journals such as Nature Communications, Acta Materialia and International Journal of Plasticity.
Assistant Professor, Computer Science and Engineering
La‘s expertise lies in developing human-robot interaction models and algorithms that can be used to create high-efficiency advanced manufacturing processes. His current research focuses on designing robotic systems for infrastructure inspection, including the use of drones and ground-based robots to safely and efficiently inspect bridges, as well as the development of novel algorithms and 3-D visualization techniques to improve the use of ground-penetrating radar for inspection and sensing.
“Due to its highly interdisciplinary nature, addressing the challenges of advanced manufacturing requires an interdisciplinary approach and specialized equipment,” La said. “We plan to combine advanced robotics, controls and automation technologies to provide Nevada engineering students with a unique, globally competitive perspective on advanced manufacturing.”