Steve has agreed to add a fourth session - focused on Accelerated Life Testing (ALT) by popular demand. Note: new registration link to right.
May 2, 11:00 AM - 12:20 PM EDT
This is a three one-hour 20 minute lecture series on predicting product reliability.
This Webinar is held every weekday, from:
Apr 9, 10, 11, 2012 11:00 AM - 12:20 PM EDT
Title
Predicting Product Life Using Reliability Analysis Methods
Abstract
Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition. Poor reliability can doom a product and jeopardize the reputation of a brand or company. Inadequate reliability also presents financial risks from warranty, product recalls, and potential litigation. When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met. This 4-Hour course provides an overview of quantitative methods for predicting product reliability from data gathered from physical testing or from field data.
REGISTER at
Learning Objectives
1. Develop awareness of Reliability concepts, methods, and tools for predicting product reliability performance
2. Learn best practices in the modeling of time-to-failure data for prediction
3. Apply methods for estimating component, subsystem, and system reliability
4. Understand aspects of Reliability test planning for Reliability estimation and/or demonstration
5. Awareness of Accelerated Life Testing
6. Apply Reliability methods for predicting warranty
Biography
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 estimate and reduce warranty.
Credentials and Honors
M.A., Applied Statistics, University of Michigan, 2002
M.B.A, Katz Graduate School of Business, University of Pittsburgh, 1992
B.S., Mechanical Engineering, University of Michigan, 1986
Summa Cum Laude, University of Michigan, 1986
Tau Beta Pi - National Engineering Honor Society, 1986
Associates Fellowship and Highest Honors, University of Pittsburgh 1992
Six Sigma Blackbelt Certification, Ford Motor Company 2001
Ford Education Fellowship, 2001