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Dec 26, 2024
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IE 348 - Quality Assurance (SPC)3 lecture hours 0 lab hours 3 credits Course Description Improved quality has been identified as one of the most critical issues facing business today, essential to assuring competitiveness in a global economy. While emphasis is placed upon the techniques of statistical process control and acceptance sampling, the course also details other graphical tools of quality analysis, explicitly connecting quality to productivity and costs. The course is intended to present quality concepts, tools and techniques in sufficient breadth so as to be applicable to both manufacturing and the service sector. (prereq: MA 262 and IE 2030 ) Course Learning Outcomes Upon successful completion of this course, the student will be able to:
- Understand and describe the components of quality
- Understand the roles of quality in organizations
- Discuss the importance of quality improvement as a strategic management issue
- List fundamental concepts and techniques advanced by Deming, Juran, Fiegenbaum, and Crosby
- Successfully characterize and evaluate process capability
- Specify, create, implement, and interpret fundamental variables and attributes control charts
- Utilize graphical methods for efficient data analysis and problem solving
- Develop acceptance sampling plan OC curves
- Specify and interpret basic acceptance sampling systems such as ANSI/ASQC Z1.4
- Design appropriate quality control systems
- Understand basics of design of experiments and how to design, implement and analyze the results
- Apply QA techniques to both manufacturing and service sectors
- Improve communications skills
- Understand the importance of and be able to implement a Measurement System Analysis
Prerequisites by Topic
- Good understanding of statistical distributions, variability, and using software to do hypothesis testing, analysis of variance, and conduct and interpret other statistical tests
Course Topics
- What is quality?
- How is quality defined
- Quality improvement
- The DMAIC process
- Methods and philosophy of SPC
- Control charts for variables
- Control charts for attributes
- System capability analysis
- Measurement System Analysis
- Acceptance sampling
Coordinator Dr. Doug Grabenstetter
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