OVERVIEW
Design of Experiments (DOE) is an important technique for root cause analysis (RCA) and process improvement. As an example, when potential trouble sources are identified from a cause and effect diagram, DOE can be used to determine which of the factors are likely to be important. DOE can also develop quantitative models of the nature y=f(x) (y is a function of x) where y is often a critical to quality characteristic.
LEARNING OBJECTIVES
Attendees will learn the fundamentals of DOE, some of which carry over into other industrial statistics applications such as acceptance sampling and statistical process control.
Hypothesis testing is the foundation of almost everything we do with industrial statistics.
The null hypothesis, or starting assumption, is that there is no difference between the experiment and the control, a production lot is acceptable, or a process is in control.
The alternate hypothesis is that the experiment differs from the control (is better than the control in an improvement activity), a production lot should be rejected, or a process is out of control and needs adjustment.
AREAS COVERED
Value of DOE in the language of time and money, as shown by comparison of an experiment performed by Frederick Winslow Taylor during the late 19th century, and an even more complicated one performed by a pharmaceutical company that sought FDA approval for a diagnostic test
Hypothesis testing as the foundation of most industrial statistics applications including not only DOE but also statistical process control and acceptance sampling (e.g. ANSI/ASQ Z1.4 and ANSI/ASQ Z1.9)
Interactions, or situations in which the whole is greater or less than the sum of its parts. Interactions cannot be detected by one variable at a time experimentation.
WHO WILL BENEFIT?
Quality Departments
Manufacturing Departments
Engineering Departments
Technicians, Supervisors and Managers
SPEAKER
William A. Levinson, P.E., is the principal of Levinson Productivity Systems, P.C. He is an ASQ Fellow, Certified Quality Engineer, Quality Auditor, Quality Manager, Reliability Engineer, and Six Sigma Black Belt. He is also the author of several books on quality, productivity, and management, of which the most recent is The Expanded and Annotated My Life and Work: Henry Ford’s Universal Code for World-Class Success.
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