Mathews Malnar and Bailey, Inc. Quality engineering, applied statistical consulting, and training services for R&D, product, process, and manufacturing engineering organizations.

Introduction to Design of Experiments for Managers

Course Description: This course:

• Introduces Design of Experiments (DOE) methods to technical managers.
• Describes how DOE finds the best answers to design and process problems in the fastest and most economical way.
• Addresses the management of the people who will be performing designed experiments.

A review of the DOE process will be performed including: initial process characterization; identification of design variables; preliminary testing; selection of variable levels; selection of an experiment design; sample size determination; experiment planning; experiment execution; numerical data analysis and interpretation; and experiment reporting.

A brief outline of the experiment designs available for treating quantitative and qualitative variables will be presented including designs for screening many variables and designs for building complex models. Included are: designs for one, two, and multiway classifications, factorial designs, fractional factorial designs, Box-Behnken designs, and central composite designs. The highly fractionated factorial designs of Plackett/Burman and Taguchi will also be considered. The use of an experiment design catalog and analysis macros from Minitab will be discussed.

A simple three variable experiment (paper helicopters) will be performed in class to demonstrate all of the steps of the DOE process. The data will be analyzed using Minitab and then used to specify an improved design. The limitations of the model and the implications of manufacturing process variability will be discussed.

After the DOE demonstration there will be a discussion of the resources necessary to support DOE activity:

• Preliminary testing
• Measurement systems requirements
• Staff who must be involved in planning
• Staff who must be involved in execution
• Staff time requirements
• Access to the equipment/process
• Software requirements

There will be a closing discussion of the training that is required to develop in-house experts to design, execute, analyze, and interpret designed experiments.

Prerequisite: Persons attending this class should have basic algebra skills and be familiar with the basic language and notations of quality engineering.

Contact Hours: Seven (7)

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