Course No: MECH.5750-031; SIS Class Nbr: 8159; SIS Term: 2630
Course Status: Open
Concepts of Robust Design and statistical Design Of Experiments (DOE) as applied to the design and manufacturing of new high technology products. Classical and current methodologies of DOE including Full Factorial, Fractional Factorial, Taguchi, Central Composite and Yates Algorithms. The course will also provide for different methods for experimental design and analysis, including average and variability analysis. Commercial software packages and case studies using industrial experiments will be used to illustrate the material.
Prerequisites, Notes & Instructor
- Prerequisites: Students with a CSCE career need permission to take Graduate Level Courses.
- Special Notes:
- Section Notes:
- Credits: 3;
- Instructor: Sammy Shina
When Offered & Tuition
- Online Course
- Spring 2017: Jan 17 to Apr 29
- Chat Hours: Mon 9:00-9:55pm*
- Course Level: Graduate
- Tuition: $1725
- Note: There is a $30 per semester, nonrefundable registration fee for credit courses.
*Chat Hours provide an opportunity for the instructor and students to communicate
in "real time". It is an informative and interactive session where course related questions, answers,
and discussions take place. While student attendance during chat hours is not required, it is highly recommended.
Weekly chat sessions are archived for students who are not able to participate in the live chat sessions at the
Related Programs: M.S. in Engineering Management, M.S. in Engineering Management
Every effort has been made to ensure the accuracy of the information presented in this catalog. However, the Division of Online & Continuing Education reserves the right to implement new rules and regulations and to make changes of any nature to its program, calendar, procedures, standards, degree requirements, academic schedules (including, without limitations, changes in course content and class schedules), locations, tuition and fees. Whenever possible, appropriate notice of such changes will be given before they become effective.