Handbook of Experimental Methods for Process Improvement both by David Drain, Chapman and Hall, 1997
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Week |
Lecture |
Lecture Topics |
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1 |
Chapter 1 |
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2 |
Chapter 3 |
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3 |
Chapter 6 |
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4 |
Chapter 8 Chapter 9 |
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5 |
Chapter 10 |
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6 |
Chapter 13 |
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7 |
Chapter 13 |
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8 |
Chapter 14 |
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9 |
Chapter 14 |
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10 |
Chapter 14 |
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11 |
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12 |
Chapter 16 |
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13 |
Chapter 16 |
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14 |
Chapter 16 |
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15 |
Chapter 16 |
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Instructor: George C. Runger,
Handbook of Experimental Methods for Process Improvement both by David Drain, Chapman and Hall, 1997
About the course:
- A course in statistical process control and improvements through designed experiments that focuses on semiconductor processing
- Intended for engineers, and physical/chemical scientists, and deals with the types of control charts and experiments that are frequently run in industrial settings
- A basic working knowledge of introductory statistical methods would be useful background, but introductory material will be covered at the start of the course
- The introductory material that will be covered at the start of the course includes
the following:
- Compute and interpret the sample mean and standard deviation
- Use the normal distribution
- Test a hypothesis (the t-test, for example)
- Construct and interpret a confidence interval
Course objective:
- Interpret data summaries
- Compute basic probabilities for risk assessment
- Reason statistically from a sample to a process
- Plan, design, conduct, and analyze experiments efficiently and effectively
- Assess process control and capability and to develop and use basic control charts
- Adjust analyses for important characteristics of semiconductor data
Opportunities to use the principles taught in the course arise in all phases of engineering work, including new product design and development, process development, and manufacturing process improvement. Methods will be customized to semiconductor manufacturing and examples will be drawn from this field. Some important modifications to standard methods are needed for semiconductor processes.
All experiments conducted by engineers and scientists are designed experiments; some of them are poorly designed, and others are well designed. The well-designed ones allow you to obtain the desired results faster, easier, and with fewer resources. That’s what you will learn how to do in this course. A well-designed experiment can lead to reduced development lead-time for new processes and products, improved manufacturing process performance, and products that have superior function and reliability.
Computer software: Computer software to implement the methods presented will be illustrated, and you will have opportunities to use it for homework assignments and project. Campus labs provide Minitab, but any one of several commercial packages can be used and the relationships between these and Minitab should be easy to follow.
Grading: Your grade in the course will be determined by two mid-term exams (50%), a final exam (25%) and homework projects (25%). Additional homework exercises will be assigned, with solutions, but these will not be scored.
Homework and Projects: Important!! You should work as many exercises from the book as you feel are necessary to become familiar with the material. These will not be turned in, but selected solutions will be provided. Small projects will be assigned approximately every two weeks that will be more comprehensive applications of the material. These will be turned in and they will sometimes require you to collect and analyze data present to the class. No proprietary information should be used. Additional details will be provided.