Industrial Internet-of-Things (IIoT) is becoming integral parts of manufacturing environments to enable more efficient operation. However, these IIoT devices and their corresponding cyber-infrastructures are often static, slow, and expensive.
In The Grainger College of Engineering, an interdisciplinary team – consisting of MechSE Professor Chenhui Shao, Computer Science Professor Klara Nahrstedt, and graduate students from MechSE and CS Beitong Tian, Kuan-Chieh Lu, Ahmadreza Eslaminia, and Yaohui Wang – worked together on a system, called WeldMon that made IIoT much more affordable, fast, and adaptable.
Furthermore, WeldMon was validated on Ultrasonic Welding Machines, and it was shown that WeldMon improved the future of the machine’s condition monitoring. The team shared the results of WeldMon at the IEEE Ubiquitous Computing. Electronics & Mobile Communication Conference, where their paper “WeldMon: A Cost-effective Ultrasonic Welding Machine Condition Monitoring” won the Best Student Paper Award.
Tian, lead PhD graduate student on this paper, advised by Nahrstedt, motivated his team through experience he gained from work on another project.
“I, together with my collaborators at the Holonyak Micro & Nano-Technology Laboratory and Materials Research Laboratory, developed a cost-effective sensing system called MAINTLET to monitor pump conditions in cleanrooms,” Tian said. “When I learned about a group of researchers in Mechanical Science and Engineering using a high-cost system to detect defects and abnormal machine conditions in ultrasonic welding machines, it naturally sparked my curiosity. I wondered if the low-cost MAINTLET could achieve the same results for ultrasonic welding machines.”
When asked how the topic of ultrasonic welding would affect the average person, Lu, a PhD candidate in Shao's research group, gave his perspective.
“Ultrasonic metal welding is vital in manufacturing industries like electric vehicles. This technology plays a crucial role in ensuring the reliability and efficiency of key components, ultimately influencing the quality and safety of the vehicles that people use daily,” Lu said.
Lu also shared his thoughts on why Machine Condition Monitoring Systems (MCMS) are important.
“MCMS are technologies designed to assess and analyze the health and performance of machinery in a real-time manner,” he said. “These systems use a combination of sensors, data acquisition methods, and data analysis algorithms to monitor various parameters such as vibration, temperature, pressure, and more. The primary goal is to detect and diagnose potential issues in machinery before they lead to costly failures.”
Tian thanked the faculty and his peers for collaborating with him on the WeldMon system and paper.
“I received valuable guidance and support from professor Nahrstedt, who is my advisor. Additionally, Ahmadreza and Kuan-Chieh, along with their advisor – Professor Shao – played crucial roles by assisting in data collection, analyzing results, and contributing to the completion of the mechanical engineering-related system issues and the inclusion of corresponding results in the paper," Tian said.