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Apr 17, 2024
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IE 613 - Quality Engineering3 lecture hours 0 lab hours 3 credits
Course Description
This course focuses on engineering techniques specifically designed to result in high-quality products and processes. Experimental design focuses on the selection of factors (parameters) which result in an optimal output. Taguchi methods, which lead to minimum-variance results, are also included. Quality function deployment (QFD) brings the needs of the customer into the engineering design process. Numerous examples and applications are provided to show the applicability of these techniques to a wide variety of products and services. (prereq: none)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Recognize applications of experimental design techniques
- Plan and conduct a designed experiment
- Analyze experimental data, draw conclusions, and make recommendations regarding process, design, and quality improvements
- Understand and be able to explain the differences between, and the pros and cons of, traditional experimental design methods and Taguchi methods
- Present and discuss analysis procedures, results, and implementation in a professional forum
Prerequisites by Topic
- Probability and statistics
Course Topics
- Intro to quality engineering: the engineering design process, role of experimentation, robust design, experiments with a single factor/ANOVA (3 hours)
- Minitab demonstration, randomized complete block design (3 hours)
- Quality function deployment, factorial designs: two-factor designs, general factorial designs (3 hours)
- 2K factorial designs (3 hours)
- Blocking and confounding in the design (3 hours)
- Fractional factorial designs (3 hours)
- Fitting regression models (3 hours)
- Response surface methods (3 hours)
- Taguchi methods (3 hours)
- Robust parameter design and process robustness studies (3 hours)
Coordinator
Dr. Subha Kumpaty
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