“It is dedicated to hands-on education and applied research in industrial automation, robotics and smart manufacturing,” says Shokoufeh Mirzaei, Ph.D., professor and IME department chair. “The lab supports undergraduate and graduate coursework, senior capstone projects, and faculty-led research aligned with Industry 4.0 and advanced manufacturing technologies.”

The 2,200-square-foot facility features a fully integrated smart factory, a miniature version of the main system for research and experimentation, a 27-seat classroom setup with a main projection and three peripheral LCD screens, multiple PLC-controlled hardware and software workstations, and flexible space to support additional training in mobile robotics and manufacturing systems.

“The Vy and Timothy Li Automation Lab is a prime example of how philanthropy, faculty initiative and a shared commitment to student success can come together to build something truly transformational,” explains Andrew Ketsdever, Ph.D., dean of the College of Engineering. “This lab is not just a space—it’s a launchpad for innovation and career readiness in the era of Industry 4.0.”

The heart of the lab is an advanced Intelitek Smart Factory system. It includes two PLC-controlled conveyor lines, an automatic storage and retrieval system, five industrial robot arms, CNC milling and turning machines, a vision-based quality control station and a laser engraver with an advanced air filtration system.

Production equipment includes four six-axis Yaskawa GP8 robots, four Epson T3 SCARA pick-and-place robots and one Festo Robotino mobile robot. In addition, there are 10 Siemens PLC-HMI simulators and four Siemens PLC-controlled electromechanical stations. Six Allen-Bradley PLC-controlled electromechanical and electropneumatic stations are equipped with stepper and DC motors and drivers, encoders, switches, lights and pneumatic cylinders.

All components are linked by a continuous-loop conveyor and pallet tracking system, a central management control station, a TCP/IP communication network, and Intelitek’s OpenMES software. The system has been expanded and adapted to address future applied learning needs by adding smart sensors that support real-time protocols like OPC-UA reporting so that various Industry 4.0 research projects can integrate with the system.

“This setup provides students with an immersive, industry-relevant experience in smart manufacturing technologies,” says Mirzaei, who teaches courses related to data analytics, quality control and systems engineering. “Our department is entrenched in understanding industrial processes and efficiency. The automation laboratory enables learning and research [that] will greatly benefit our students.

“While the lab is designed to support a wide range of applications, its core focus is on smart manufacturing, CNC-based automated production, assembly, industrial control and quality control,” explains Mirzaei. “A miniature research station within the lab also allows for experimentation with additional technologies, such as haptic-based robotic grasping and additive manufacturing.”

The lab supports applied research and student projects across several industries, including advanced materials, aerospace, biomedical and logistics.

“The lab is actively being integrated into [our] curriculum to provide students with direct, hands-on experiences,” Mirzaei points out. “Students work with real-world industrial equipment to perform programming, integration and system-level diagnostics.

“They learn to program PLCs, CNCs, robots and sensors, control individual workstations, and then integrate them into a unified system,” notes Mirzaei. “Projects are structured to simulate real-world manufacturing workflows, from robotic assembly to automated inspection, as well as production planning for various parts on the smart factory. [The goal is to equip] students for careers in modern manufacturing and automation.”

The automation lab incorporates core Industry 4.0 tools, including real-time data acquisition with Moneo smart sensors that monitor parameters such as vibration, temperature and motor shaft speed, in addition to IoT communication and cyber-physical systems.

“It also supports analysis and optimization through digital twin modeling,” says Mirzaei. “Students gain first-hand experience with the technologies and infrastructure behind smart factories, developing the skills needed to support the digital transformation of industry.”

The laboratory is also equipped with an automated inspection system that utilizes advanced machine vision.

“Students are tasked with designing and implementing image-processing algorithms to inspect parts for dimensional accuracy, surface defects, proper alignment and pattern matching,” says Mirzaei. “The pass or fail data is transmitted in real-time to the MES system, which subsequently updates the production plan.

“This system facilitates real-time defect detection and integrates AI-driven analytics tools for predictive quality monitoring, such as SPC charts, and continuous process improvement,” adds Mirzaei.