The goal of this course is to familiarize the student with various philosophies and definitions of quality. The course teaches the principle components of a quality system, basic approaches to designing, implementing and managing a quality system, on-line statistical process control and its relationship to capability assessment and improvement, basics of acceptance sampling both from an analytical and an applications perspective, how to measure component reliability and how to model the reliability structure of a complex system as a function of the constituent component reliabilities. The course develops an introductory knowledge of experimental design with particular emphasis on tools such as one-way and two-way ANOVA and factorial design, and impart an understanding of the relevance of these tools in the context of off-line quality control. Also, it introduces the basics of the Taguchi method with a particular emphasis on the continuous loss function and robust design.
Upon successful completion of this course, a student will be able to
1. Describe the total quality management philosophy. (j, B2)
2. Select and use appropriate online process control tools to monitor the evolution of a production process with respect to an attribute or variable type quality characteristic. (b2, B4)
3. Select an appropriate acceptance sampling process to ensure desired levels of customer and producer protection in the shipment of finished lots.(e, B3)
4. Model system reliability and other relevant parameters such as mean time between failures as a function of component reliabilities. (e, B3)
5.Use an appropriate experimental design scheme to determine the control factors that affect quality, considering the interactions between control and noise factors.
Montgomery, C. D., (2009), Introduction to Statistical Quality Control (6th edition), John Wiley & Sons Inc.
| Workload | Hrs |
|---|---|
| Lectures | 42 |
| Course Readings | 26 |
| Exams/Quizzes | 45 |
| Case Study Analysis | 20 |
| Homework | 35 |