Fall 2020 Teaching Schedule
- TECH 200, Tue & Thu, 4:30-5:45 p.m. (Online class meets via Zoom)
- TECH 230, Mon & Wed, 4:30-5:45 p.m. (Online class meets via Zoom)
Summer 2020 Teaching Schedule
- TECH 230, Tue & Thu, 5:00-7:00 p.m., Online Class.
Spring 2020 Teaching Schedule
- TECH 233, Tue & Thu, 6:00-7:15 p.m., IS 108.
- TECH 031, Tue & Thu, 4:30-5:45 p.m., ENG 407.
- Six Sigma and Continuous Improvement Systems Management (TECH 230): This course focuses on the definition and applications of Six-Sigma quality systems for design production and business processes. The main topics include statistical methods in quality control and assurance, implementation strategies, and practical industrial applications for achieving continuous quality improvement, defect reduction, and project planning and management methods to achieve universal participation in process improvement.
- Design and Analysis of Experiments (TECH 233): This course focuses on analysis of experimental design strategies for process and design improvement with industrial applications. Various DoE methods including single factor, multi-factor, and optimization designs are among the main topics. Statistical model building and evaluation is conducted for experimental analysis using t-tests, ANOVA, Chi-square, linear and multiple regression techniques.
- Research Methods for Engineering and Technology (TECH 200): This course covers current research methods applied to problems in engineering, technology, and other technical fields. The topics include details of research process, types of research methods and applications, mixed methods design, and qualitative vs quantitative methods in engineering research. Students are expected to write a mini-thesis as a final project for the course. TECH 200 serves as the GWAR (Graduation Writing Assessment Requirement) for MSQA students.
- Quality Assurance and Control (TECH 31): This course covers introduction to concepts and statistical methods that companies use to manage and improve quality. Topics include sampling inspection, statistical process control, quality function deployment, cost of quality, basics of design of experiment and Taguchi's method for designing in quality. Students are expected to complete a final project focusing on data analytics for quality improvement.