Laboratory Course - Microelectronics Fabrication Curriculum
    Syllabus
    Required textbook:
    Applied Statistics and Probability for Engineers, 3rd edition, 2003,by D. C. Montgomery and G. C. Runger, John Wiley and Sons, with eText CD
    Other (not required) reading material:
    Statistical Methods for Industrial Process Control
    Handbook of Experimental Methods for Process Improvement both by David Drain, Chapman and Hall, 1997
    IEE 598 DOE/SPC for Semiconductor Processing

    Week

    Lecture

    Lecture Topics

      1

    Chapter 1
    Chapter 2

    • Course overview/review of syllabus/student information, role of statistics in engineering (1-1 through 1-4)
    • Introduction to probability and random variables (rv’s) (2-1 through 2-8)

      2

    Chapter 3
    Chapter 4

    • Probability, probability density functions of discrete rv’s, and the binomial distribution (3-1, 3-2, 3-4, 3-6, 3-9)
    • Probability plots, probability mass functions of continuous rv’s, and the normal distribution (4-1, 4-2, 4-4, 4-6, 4-7)

    3

    Chapter 6

    • Correlation and independence, random sampling, and the central limit theorem (CLT) (6-1 to 6-7)

     4

    Chapter 8 Chapter 9

    • Statistical intervals for a single sample, point estimation, confidence intervals for means and variances (8-1 to 8-4), semiconductor examples
    • Tests of hypotheses for a single sample, t tests for means, and tests for variance (9-1 to 9-4)

    5

      Chapter 10
    Midterm
    • Inference for a difference in two means with known and unknown variances, variances of two normal populations, and review summary table for two-sample inference procedures, paired t-test (10-1 through 10-5)
    • Midterm Exam

    6

    Chapter 13
    • Introduction to designed experiments and analysis of variance (ANOVA) for a single factor (13-1, 13-2)

    7

    Chapter 13
    • Randomized block designs (13-4), role in semiconductor processing

    8

    Chapter 14

    • Multiple-factor designed experiments (DOE) (14-1 through 14-5)
    • 2k designs for factors (14-7) and examples for semiconductor processing

    9

    Chapter 14
    • Single replicate of a 2k design (14-7)
    • Blocking of a 2 k design (14-8)

    10

    Chapter 14
    • Fractional replication of a 2k design (14-9)
    • Addition of center points to a 2k design (14-7 supplemental)

    11

     

     

    • Examples for semiconductor processing
    • Midterm Exam

    12

    Chapter 16
    • Introduction to statistical process control (SPC) (16-1 to 16-4)
    • Control charting, and the control chart and special concerns for semiconductor manufacturing (16-5)

    13

    Chapter 16
    • Rational subgroups, control charts for individuals (16-6)
    • Process capability (16-7)

    14

    Chapter 16
    • Introduction to attribute data
    • Attribute control charts (16-8)

    15

    Chapter 16
    • Control chart performance and special topics (16-9)

     

     

    • Final Exam
    Course Syllabus: IEE 598 Design of Experiments/ Statistical Process Control for Semiconductor Processing

    Instructor: George C. Runger,

    Required textbook:
    Applied Statistics and Probability for Engineers, 3rd edition, 2003,by D. C. Montgomery and G. C. Runger, John Wiley and Sons, with eText CD
    Other (not required) reading material:
    Statistical Methods for Industrial Process Control
    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.