Course Description:
ENGRG 7510 Design of Experiments
| Course Number: | ENGRG 7510 |
| Course Name: | Design of Experiments |
| Course Description: | This course on Design of Experiments (DOE) provides experiences in planning, conducting, and analyzing statistically designed experiments. The methods of DOE may be applied to design or improve products and processes. Analysis of variance (ANOVA), test of hypothesis, confidence interval estimation, response surface methods, and other statistical methods are applied in this course to set values for design, process, or control factors so that one or more responses will be optimized, even when noise factors are present in the system. This course is designed to teach the nuts and bolts of DOE as simply as possible. P: MATH 4030 or MATH 6030 or ENGRG 6050, or consent of instructor. |
| Prerequisites: | None |
| Level: | Graduate |
| Credits: | 3 |
| Format: | Online |
| Semesters Offered: |
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| Registration Instructions |
Additional Information
Learning Outcomes
Upon successful completion of this course, you will be able to function competently in applied research involving the design and analysis of experiments.
More specifically, after completing this course, you should be able to implement, formulate, and analyze the resulting data for
- Complete randomized design
- Randomized blocks and related designs
- 2k factorial design
- Factorial design (fixed, random, and mixed effects models)
- Nested design
- Split-Plot design
- Response surface methods
- Regression models
- Use multiple comparison techniques to draw simultaneous inference about parameters
- Use residual analysis to check for violation of the model assumptions
Unit Descriptions
ENGR7510 Design of Experiments (DOE) is divided into five sections:
Lessons 1 - 3 review basic statistical concepts and analysis of variance (ANOVA). Three weeks are devoted to these lessons. In addition, practical aspects of planning engineering experiments, checking model validity, and estimating sample size are discussed. Students will begin to use the software Design-Ease for most of the statistical and graphical analysis.
Lessons 4 - 6 cover the randomized complete block design (RCBD), Latin squares, and factorial designs. Three weeks are devoted to these lessons. Students will also begin a course project. They will either select a case study from the required text DOE Simplified or identify a real-world problem from their own work. The course project may be performed individually or in teams of up to three people. The project consists of planning, designing, conducting, and analyzing an experiment, using appropriate DOX/DOE principles. Two written interim project reports are required, along with a final written project report. The due dates for these items appear in the course outline. The context of the project experiment is limited only by students' imagination. Students may conduct experiments directly connected to their own research or to industrial projects. This is a nice way to get extra mileage from this course.
Lessons 7 & 8 cover fractional factorial designs and confounding present in these designs. Two weeks are devoted to these lessons.. Methods of improving the resolution of the design through blocking and folding over of experiments will be discussed and applied. Substantial progress in the course project must be demonstrated in the second project report.
Lessons 9 & 10 are devoted to advanced topics in the design of experiments: response surface methods and designs, random factors in factorial experiments, mixed models, nested designs, and split-plot designs. These topics will be covered in two weeks.
Lessons 11 - 14 will focus on the Taguchi approach to the design of experiments. Four weeks are devoted to these lessons.. Concepts of orthogonal arrays and linear graphs will be discussed in detail and experiments will be designed using these.
The last week of the course will be devoted to the completion of the course project, project discussions, and project presentation.
Exercises will reinforce basic concepts and provide experience with software for DOE (Design-Ease, MINITAB, Qualitek-4).
Number of Exams
There are 3 exams for this course.
Number of Assignments
There are 10 assignments and 10 discussions for this course.
Number of Projects
There are 4 term projects for this course.
Grading Information
Your course grade will be comprised of 10 discussion questions (15%), two tests (10% each), 13 individual assignments (Homework-25%), a term project (25%) and a final exam (15%).
Assignments % Weight
Two Tests (10% Each) 20%
Homework 25%
Discussion 15%
Term Project 25%
Final Exam 15%
TOTAL 100%
Semester letter grades are assigned on the composite scores as follows:
A 90 to 100 %
B 80 to less than 90 %
C 70 to less than 80 %
D 60 to less than 70 %
F Less than 60%