INFORMATION SENSING AND ANALYSIS FOR MANUFACTURING PROCESSES
Focuses on the sensing and multivariate data modeling and analysis techniques for monitoring, diagnosis, and quality improvement of manufacturing processes. The techniques introduced can find wide applications in health care, financial engineering, service industry applications, human factors, etc.
Prerequisites & course information
Requisites: I SY E/M E 512 , graduate/professional standing, or member of Engineering Guest Students Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Spring 2025 Learning Outcomes: 1. Perform data analysis and propose quality improvement plans Audience: Both Grad & Undergrad 2. Develop, implement, and interpret advanced control charts for monitoring continuous and discrete quality characteristics and multivariate systems Audience: Both Grad & Undergrad 3. Implement appropriate data reduction and data processing methods in statistical process control Audience: Both Grad & Undergrad 4. Apply methods and tools to a real problem-solving experience via a course project Audience: Graduate Learning Outcomes: 1. Perform data analysis and propose quality improvement plans Audience: Both Grad & Undergrad 2. Develop, implement, and interpret advanced control charts for monitoring continuous and discrete quality characteristics and multivariate systems Audience: Both Grad & Undergrad 3. Implement appropriate data reduction and data processing methods in statistical process control Audience: Both Grad & Undergrad 4. Apply methods and tools to a real problem-solving experience via a course project Audience: Graduate
Sources
- Course catalogue ↗2026-2027