The advanced manufacturing research area focuses on manufacturing processes and systems, additive manufacturing, logistics and supply chain, quality, reliability and maintenance.
Uncovering the Art of Printing Extremely Hard Steels Flawlessly
For millennia, scientists have been meticulously tweaking the ingredients of steel to enhance its properties. As a result, several variants of steel exist today; but one type, called martensitic steel, stands out from its steel cousins as stronger and more cost-effective to produce. Researchers from the department and Texas A&M, in collaboration with scientists from the U.S. Air Force Research Laboratory, developed guidelines that allow 3D printing of martensitic steels into very sturdy, defect-free objects of nearly any shape.
To have diverse applications, low-alloy martensitic steels need to be assembled into objects of different shapes and sizes. This is accomplished through additive manufacturing. Complex items can be built layer by layer by heating and melting a single layer of metal powder along a pattern with a sharp laser beam. Each of these layers is joined and stacked to create the final 3D-printed object. However, 3D printing martensitic steels using lasers can introduce unintended defects in the form of pores within the material.
The research team chose an existing mathematical model inspired from welding to predict how a single layer of martensitic steel powder would melt for different settings for laser speed and power. By comparing the type and number of defects they observed in a single track of melted powder with the model’s predictions, they were able to change their existing framework slightly so that subsequent predictions improved.
Their framework can correctly forecast if a new, untested set of laser settings will lead to defects in the martensitic steel. The guidelines are general enough that the same 3D printing pipeline can be used to build intricate objects from other metals and alloys.
Featured Students
Ashif Iquebal graduated in summer 2020 and began working as an assistant professor at Arizona State University. His dissertation is titled “Graph Analytics for Smart Manufacturing.” In November 2018, he was named the winner of the best student poster award at the INFORMS annual meeting.
Zimo Wang graduated in summer 2020 and began working as an assistant professor at The State University of New York-Binghamton. His dissertation is titled “Smart Sensing in Advanced Manufacturing Processes: Statistical Modeling and Implementations for Quality Assurance and Automation.” He had the best student paper at the quality control and reliability engineering session at the IISE conference.