Design of Experiments with MINITAB Course
Note: This course can be modified in duration, format, and content to satisfy a customer’s specific training requirements. The details below reflect the most common and successful design of the course.
Course Description: This course begins with a review of the prerequisite material including graphical presentation methods, measures of location and variation, and the hypothesis tests and confidence intervals necessary to analyze and interpret designed experiments. Students will learn to design, analyze, and interpret experiments to study how a process output variable (POV) depends on one or more process input variables (PIV) using analysis of variance (ANOVA) and regression techniques. Students will learn to use both graphical and quantitative methods to confirm that the assumptions of the analysis methods are satisfied and appropriate remedial actions when they are not. The specific experiment designs to be covered are: the completely randomized design, the randomized block design, general factorial designs, two-level factorial designs, fractional factorial designs, Plackett-Burman designs, central composite designs, and Box-Behnken designs. Students will use the MINITAB statistical software package. MINITAB and DOE skills will be reinforced with substantial homework assignments. Students will also be required to participate in lab exercises and to report the results of their experiments in both oral and written form.
Who Should Take This Course: This course is intended for process improvement specialists who work in product or process engineering, manufacturing, research, service industry, and business administration operations.
Prerequisite: Students must have completed an applied statistics course or be able to demonstrate proficiency in basic statistical methods.
Textbook: Paul Mathews, Design of Experiments with MINITAB. See the link to the textbook for details of the book and for supporting course materials including class presentation notes, homework problems, and classroom exercises and labs documents.
Contact Hours: 40 hours
Course Format: The preferred course format is to present the material in ten four-hour sessions with one session per week, in a two-weeks-on, one-week-off cadence. This gives students time to read and study the methods of the week, to complete homework assignments, to consider personal applications of the methods, and to practice solving problems.
Homework: Ten assignments requiring about 2-6 hours each (3 hours nominal) will be given. The customer may decide if students are required to do the homework although students post-course DOE skills are strongly and positively correlated to the amount of homework that they do.
Evaluation: Pre- and post-course quizzes will be used to document what students learned during the course.