Presented by Prof. Joseph B. Bernstein
All reliability professionals are required to report reliability in simple-to-understand yet meaningful metrics. Typically, Mean Time To Fail (MTTF) or Defective Parts Per Million (DPPM) is used by many industrial practitioners as a way to communicate the calculated reliability of a product, device or system. Most metrics for reliability assume a constant hazard rate or constant failure rate statistical approach. This is mathematically described as a time invariant Poisson process. This is exactly the “exponential” reliability model as is well known by most industries and is the working assumption when using MTTF or other such metrics.
In reality, everyone knows that some equipment have wearout or fatigue mechanisms that accumulate over time and makes the likelihood of an older product inherently more susceptible to failure than a new piece of equipment. Similarly, companies are constantly working on reliability growth and improvement with each generation making the decision to upgrade implicitly a decision to improve long-term reliability. Also, defects are often seen during product introduction and decreasing failure rates are observed.
This 2-hour tutorial, which costs $200, will focus on the mathematical basis for exponential reliability models and how they are justified by physics of failure and basic assumptions of thermodynamics. The physics and statistics are then extended to justify using the Weibull distribution to describe more accurately the failure distribution in the field. However, this information is often lost in communication since MTTF is not appropriate once the Poisson model is no longer used. Furthermore, Weibull describes both decreasing as well as increasing failure rates and the information contained therein is lost when converted to a single MTTF parameter.
This tutorial will develop the understanding needed in order to decide when it is appropriate and when it is not appropriate to use Weibull statistics as opposed to Poisson statistics. Participants will learn the tools to develop their own insight as to when the MTTF statistic is meaningful and can be used for making proper reliability decisions. Through some simple mathematical formalisms and basic understanding for thermodynamics, participants of this webinar will learn for themselves how Weibull is often a useful measure for describing reliability and how it is often inappropriately used. Our goal will be to clarify any confusion that exists as to the proper way to report reliability using single statistical metrics or when more sophisticated metrics are required.