Penn State receives sensors to enhance student education

Penn State receives sensors to enhance student education
Sensors from KCF Technologies will enable students in the industrial engineering department at Penn State to analyze machine data to prevent productivity losses. (Miranda Buckheit, Penn State)

Students in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering (IME) at Penn State will learn how wireless sensors and cloud computing can impact the manufacturing field, thanks to sensors donated from KCF Technologies.

KCF Technologies, of State College, Pennsylvania, donated several SmartDiagnostics wireless vibration sensors to the department. The sensors are attached to various equipment found in the Factory for Advanced Manufacturing Education (FAME) Lab.

The sensors in the FAME Lab will enable students to use sensor-collected data to learn how to analyze a machine's health and when to repair the machines before they break down, ultimately leading to a decrease in economic loss. 

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The sensors will also enhance the course work of IE 470: Manufacturing Systems Design and Analysis. IE 470 is an undergraduate class taught by Vittal Prabhu, professor of industrial engineering and Charles and Enid Schneider Faculty Chair of the Penn State Service Enterprise Engineering Initiative. The course helps students understand modern manufacturing systems by exposing them to technology, design and analysis methodologies, robotics, automation and techniques for improving productivity in manufacturing.

"It's important that we are teaching the students how to analyze this kind of information because I think it's the future of industrial engineering," Prabhu said in a statement. "It's going to make them more desirable in the job market because they are ready for these changes."

The wireless vibration sensors transmit data in real-time to a cloud-based data storage and visualization platform where students can log in to view the data from any operating system and without downloading any software. The visualization platform provides historical trend views where students can track and understand changes in sensor data over time and correlate the information with the machine’s health. No specialized training is required to use the system.

The sensors are mounted on several of the ABB robotic arms and a HAAS CNC machining center to continuously measure the vibration of machines. If the vibration signatures of the machine appear to be unusual, the cloud platform system has capabilities to provide predictive information with configured "warning" and "alarm" notifications, which means that the machine is due for maintenance.

The sensor can be easily mounted to any metallic surface via its magnetic base to measure vibration and temperature. It consistently transmits the real-time data to a gateway or a hub, similar to a receiver box, which then pushes all the received data to the cloud platform over the Internet.

Additionally, the sensors will be used in Rakshith Badarinath's research on polymer additive manufacturing using ABB robots. Polymers have long been used in 3D printing due to the material’s ability to soften and flow when heated but become hardened when cooled.

"This is the age of connectedness, and the wireless sensors like those of KCF are easier to set up and make data acquisition much easier in research," Badarinath said. "I am able to use these sensors to monitor vibrations in the ABB robots and how much these vibrations affect quality of the printing process. This enables us to closely monitor and control the resulting product quality.”

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