San José State
U N I V E R S I T Y
MSIE
MSIE 202 – Design and Analysis of Experiments
COURSE SYLLABUS AND OUTLINE
Fall 2001 / INSTRUCTOR: Dr. Howard T. FullerTIME: Th 5:30 – 8:20 / OFFICE:
ROOM: SH 410 / OFFICE HOURS: 8:20 – 8:50
FINAL EXAM: TBD, 17:15 – 19:30 / PHONE: (408)-956-6318
THANKSGIVING BREAK: TBD / EMAIL:
Catalog Description
MSIE 202 Design and Analysis of Experiments
Statistical foundations, implementation strategies and practical industrial applications related to the Design and Analysis of Experiments. Methods and practices of using Design Of Experiments (DOE) for developing causal relationships.
Seminar. Three units
Purpose of Course
DOE is tool for establishing objective, data based relationships between process inputs and key process outputs. The structured approach to DOE presented in this course will allow optimal use of time and resources relative to information gained. The rationale for DOE is explained, statistical and experimental concepts are defined. The course teaches the participants the philosophy and methodology of DOE. A major portion of the learning is accomplished by the students using this philosophy and methodology to execute their own designed experiment as a class project. Though hands-on application, they will learn the fundamentals of DOE.
General Course Goals
As a result of actively participating in this course, students will be able to:
1. Explain DOE as a tool for establishing functional relationships
2. Appropriately apply the DOE methodology
3. Know how to effectively interpret and communicate the DOE results.
Textbooks
Montgomery, D., Design and Analysis of Experiments, Wiley, xth edition.
Fuller, H., DOE Course Notes.
Evaluation
1. Weighted Criteria Percentage
Midterm 35
Final Exam 35
Semester Project and Presentation 30
2. Project work, presentations, reading and problem assignments will be assigned to reinforce the concepts covered during the lecture. Due dates will be announced in class. It is your responsibility to keep current and turn in, present and actively participate in class discussions for all relevant assignments.
3. If you are absent the day an assignment is due, you should arrange for one of the following: (a) drop off the assignment in the main office (MSIE) before 4:00 p.m. on the due date, (b) mail the assignment to the instructor at the university (IT MUST BE POST-MARKED ON OR BEFORE THE DUE DATE), (c) send the assignment via e-mail or FAX (IT MUST BE DATE AND TIME STAMPED ON OR BEFORE MIDNIGHT OF THE DUE DATE). Exceptions will be made to this policy only in emergency situations. Please call me as soon as possible.
4. All work completed should be written in proper English. Work that is not done in an acceptable manner will receive no credit. All work must be done using APA format.
5. Grade distribution. The final grade distribution will be as follows: 97-100 A+, 93-96 A, 90-92 A-; 87-89 B+, 83-86 B, 80-82 B-; 77-79 C+, 73-76 C, 70-72 C-; 66-69 D+, 60-65 D; 0-59 F.
Outline of Course Content
Week 1: Overview of DOE, Discussion of Class Project
Week 2: DOE Planning, DOE related tools
Week 3: Descriptive Statistics and Statistical Distributions
Week 4: Statistical Testing; t-test, p-value, Confidence Interval, Practical vs Statistical Significance
Week 5: Statistical Testing: , Paired t-test, F-test, Bartlett’s Test
Week 6: Statistical Testing: ANOVA
Week 7: Two-Level Factorials
Week 8: Midterm (Date: TBD)
Week 9: Two-Level Fractional Factorials
Week 10: Special Topics for Two-Level Factorials: Identifying Wrong Values, Dispersion Effects, Concepts of Robust Experimentation (Taguchi Techniques)
Week 11: Response Surface Methodology: Steepest Ascent
Week 12: Response Surface Methodology: Central Composite, Box-Behnken Designs
Week 13: Special Topics: Evolutionary Operations (EVOP), D-optimal
Week 14: Project Presentations and Final Exam Review
Week 15: Final Exam