Course Information
- Instructor: Dr. John S. Kang
- Prerequisite: ME 202, ME 314, ME 330
- The students are required to bring a laptop to all classes to practice coding examples.
- Prerequisites: ME 202, ME 314, ME 330
Course Overview
Just as the invention of the steam engine transformed society in the late 18th century, the integration of intelligence into manufacturing has become a key driver of Industry 4.0. This course introduces the fundamental elements of smart manufacturing, highlighting the role of emerging technologies such as sensors, machine vision, and data analytics, including machine learning, in reshaping modern manufacturing engineering. Concepts are reinforced through in-class machine learning exercises and case-based applications, enabling students to gain both theoretical understanding and practical experience.
Student Learning Outcomes
- Explain the concept of smart manufacturing within the broader context of the industrial revolutions.
- Compare and evaluate core technologies, such as sensors, data analytics, and control systems, that underpin smart manufacturing.
- Design appropriate sensor systems tailored to smart manufacturing applications.
- Apply data analytics, including machine learning techniques, to sensor data for smart manufacturing applications.
- Conduct comprehensive literature reviews on recent smart manufacturing technologies.
- Develop and present integrated solutions that combine sensors and machine learning for engineering applications.