Effective Reliability Data Analysis (Session 9C) $150.00
Papers in this session will tell you how to read and use field data correctly, and show you some brilliant ways to estimate reliability from testing results.

Moderator
James M. Loman, Ph.D., Space Systems Loral

Reliability Estimation One-Shot Systems with Zero Component Failures (Paper 9C1)
Huairui Guo, Ph.D., Sharon Honecker, Adamantios Mettas, and Doug Ogden, ReliaSoft Corporation
This paper proposes a method to estimate reliability for one-shot systems from subsystem test data when there are no observed failures in the subsystem tests. This method also can be applied to the general cases when failures are observed.
Estimating Field Failure Rate from the Results of HALT (Paper 9C2)
Harry McLean, Advanced Energy and Mike Silverman, Ops A La Carte
How many of us have wanted to use the HALT data to estimate Annualized Failure Rate (AFR)? The common response is that "it cannot be done." In fact, it is possible but what is needed is a good model and good data to back the model. This paper describes a model that we developed based on HALT experience combined with field data.
Incorporating Product Retirement in Field Performance Reliability Analysis (Paper 9C3)
Ke Zhao, Duane Steffey, Ph.D., and John Loud, Exponent, Inc.
Modern consumer electronic products retire at much faster rates than previous generations of products. Neglecting to account for the shortened age of early retired units can lead to inaccurate characterization of the time-to-failure distribution. We present several case studies in which reliability estimates vary significantly, depending on whether retirement is addressed in the analysis, thus demonstrating the practical value of accounting for the product retirement of surviving units.
Field Failure Rate, more than you may think (Paper 9C4)
James A. McLinn, Rel-Tech Group
Ramp up, commercialization or roll-out are all common terms for one stage of a project when it goes from a low level production rate to a high rate. During this time, it is common for new problems to arise and the time to failure remain unknown. When shipping systems without operating time clocks or serialization, only the quantities shipped and quantities replaced are known. This paper will show some common errors with these model attempts that can be avoided.