A Clemson University student has won $100,000 for an application she developed to help monitor cutting conditions in machine tools.

Valerie Pezzullo, who is receiving her master’s degree in mechanical engineering in May, won first prize in the MTConnect Challenge 2 for “Machining Process Monitoring to Aid in Chatter Identification.”

Valerie Pezzullo holds the $100,000 check she won for winning the the MTConnect Challenge 2 contest.

Valerie Pezzullo holds the $100,000 check she won for winning the the MTConnect Challenge 2 contest.

Her research advisor is Dr. Laine Mears, associate professor of automotive engineering. Pezzullo’s research was done at Clemson University-International Center for Automotive Research.

Her work was selected by those who attended the [MC]2 2014 MTConnect: Connecting Manufacturing Conference in Orlando.

The April contest was sponsored by the National Center for Defense Manufacturing and Machining (NCDMM); the Office of the Secretary of Defense (OSD); Defense-wide Manufacturing Science and Technology (DMS&T); AMT – The Association For Manufacturing Technology and the U.S. Army Benét Labs.

With the MTConnect Challenge 2, participants were tasked with the development of innovative and unique software applications using the MTConnect standard that could be easily adopted by manufacturing enterprises, especially lower tier producers, to enhance their manufacturing capabilities and support the Department of Defense (DoD) supply chain management objectives.

MTConnect is an open, royalty-free set of communications standards intended to foster greater interoperability and information sharing between manufacturing equipment, devices, and software applications.

Pezzullo’s application offers machining process monitoring, facilitates the communication of part-specific information, and includes customization and scalability for different manufacturing facilities and academic research institutions.

By integrating machining process information gathered through MTConnect with information from proprietary data acquisition tools and custom sensors, this application provides a means to monitor cutting conditions to help reduce and prevent chatter and aid in analysis to avoid subsequent unstable operating conditions.

It also improves the input and tracking of part numbers and organizes machining process information in a central location according to the specific part.