ME 340 Dynamics of Mechanical Systems (Fall 2016, Spring 2017, Spring 2018, Spring 2020, Spring 2021, Fall 2021, Spring 2022)
ME 453 Data Science in Manufacturing Quality Control (Fall 2018, Fall 2019, Fall 2020, Fall 2022)
Course Overview: Curriculum emphasis on big data analytics together with real-world manufacturing applications plays a vital role in equipping future generations of manufacturing engineers with the skill set they need in the era of digital manufacturing, and further enhancing the competitiveness of U.S. manufacturers. ME 453 is a new manufacturing course developed by Dr. Shao. The goal of this course is to provide students, including upper-level undergraduate and graduate students, with state-of-the-art manufacturing analytics tools with a focus on quality control applications.
The Need: Most current manufacturing courses are more or less outdated, so students are often not ready for the “real-world” industry after finishing the curriculum. As such, the course is designed in a way that students are exposed to challenging real-world manufacturing problems. Students will form “Quality Control Groups” and be asked to solve a series of problems collaboratively using techniques taught in class. In order to enhance students’ capabilities of critical thinking and teamwork, the problems will be designed as open-ended. Students will also have an opportunity to operate an ultrasonic metal welder in the Automation and Digital Manufacturing Lab, and go through a complete problem solving procedure.
Uniqueness of the Course:
- Real-world data collected from manufacturing factories or labs will be used for lectures, homework, and projects. Those data will be selected from the instructor’s past and current research projects.
- For the final project, students will work collaboratively to solve quality problems oriented from various applications, such as welding, machining, graphene synthesis, and semi-conductor manufacturing.
- A mock industry review will be adopted for the final project grading. The instructor will invite his industrial collaborators from Caterpillar, John Deere, Optimal Inc., etc. to serve as judges.
For more information, please see the course syllabus and flyer. Please contact us (chshao@illinois.edu) if you would like to learn more about this course!