ESI4221 Industrial Statistics / Quality Control

Hui Yang


Textbook: Douglas C. Montgomery, Introduction to Statistical Quality Control, 6th Edition, 2008, John Wiley & Sons, Inc



K.S. Krishnamoorthi and V. Ram Krishnamoorthi, A First Course in Quality Engineering, 2nd Edition, 2011, CRC Press

Douglas C. Montgomery and George C. Runger, Applied Statistics and Probability for Engineers, 5th Edition, 2010, John Wiley & Sons, Inc., New York.


Course Objectives:
This course will present the theory and methods of quality monitoring including process capability, control charts, acceptance sampling, quality engineering, and quality design. The course objectives include:


To understand the basic concepts of quality monitoring.
To understand the statistical underpinnings of quality monitoring.
To learn various available statistical tools of quality monitoring.
To learn the statistical and economical design issues associated with the monitoring tools.
To demonstrate the ability to design and implement these tools through laboratory experiments.



Introduction to Statistical Quality Control (Deming, Six Sigma, DMAIC)


Quality Concepts and Statistical Analysis Software (Excel and Matlab)


Modeling Process Quality (statistical measures, discrete distributions, continuous distribution, probability plotting)


Inferences about Process Quality (Hypothesis testing, statistical estimation and linear regression)


Methods and Philosophy of SPC


Control Chart for Variables (x-bar and R charts, x-bar and S charts)

  Control Charts for Attributes (p chart, np chart, c chart)
  Process and Measurement System Capability Analysis
  CUSUM and EWMA Control Charts
  Laboratory and Problem Sessions


Grading Policy


Exam 1 35%
Exam 2 35%
Quiz/homework 30% (Quizzes will be announced in class, generally, a week in advance)
Final Exam 35%

The top two scores from the three exams will be added to and the total quiz/homework score to obtain the total grade for the course (out of a total of 100 pts). Exam dates will be announced as the course progresses. Final grade will be determined based on the student performance in different evaluation elements as shown above. No make-up exams unless previous arrangements have been made. Students will be expected to attend class and prepare assignments. Habitual failure to do so will result in a reduced grade. An incomplete grade will only be given when a student misses a portion of the semester because of illness or accident. Cheating on examinations, plagiarism and other forms of academic dishonesty are serious offenses and may subject the student to penalties ranging from failing grades to dismissal.

Grading scale will be used: A: 90+; B: 80+; C: 70+; D: 60+, F: <60 (College of Engineering Rule: Only grades of C or better will be accepted in all Math, Science, and Engineering courses).


Excel Demos of Statistical Control Charts


Control charts for variables: (Xbar and R charts, Xbar and MR charts)
Control charts for attributes: (p chart, p chart-variable sample size, np chart, c chart)

CUSUM and EWMA Control Charts


Examples of Manufacturing Processes


Battery Manufacturing Quality Control (
High Performance Milling NC Programming (
Toyota Camry Hybrid Factory Robots (




EXCEL and MATLAB will be used for some homework assignments in this class. It is available in College of Engineering computer laboratories, or obtain the student version for use at home.


Matlab Tutorial