Scientists, Design Engineers, and Manufacturing/Process Engineers must develop product and process specifications that ensure that products delivered to customers perform their intended functions over time. If specifications are too wide, the risks of inadequate product performance and product failures increase. If specifications are too tight, the costs to ensure conformance increase. Scientific and engineering theory, knowledge, and principles play an important role in developing specifications, but usually this must be combined with testing and data analysis to verify appropriate specifications.
This webinar by industry expert Steven Wachs, covers useful and important statistical methods that assist scientists and engineers in the development of appropriate product and process specifications.
Steven will start the webinar with a basic review of what specifications are and why they are important along with the risks of inappropriate specifications. He will discuss several methods to characterize existing product or process data that help determine whether proposed specifications are feasible or perhaps unnecessarily liberal. The typically confusing terms of coverage probability and confidence levels will also be reviewed in some detail. Steven will also discuss, the use of predictive models in developing specifications of inputs to ensure adequate responses.
Finally, the use of Monte Carlo Simulation will be briefly discussed as a way to further optimize specifications to achieve optimal outcomes.
Often, product specifications are established based on historical precedent or are changed in response to a problem that arises. However, methods exist to ensure that product specifications are appropriate to ensure products perform their intended function over time. This webinar delves into various statistical methods that are useful for defining or confirming that product and/or process specifications are appropriate
The information gained in the webinar will allow you improve your ability to develop appropriate and defensible specifications. This manages the risks of overly liberal specifications and the costs associated with overly conservative specifications.
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control. Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as to estimate and reduce warranty. In addition to providing consulting services, Steve regularly conducts workshops in industrial statistical methods for companies worldwide.