Determining the Connection Between Test and Field Reliability

In last month's HotWire, we discussed an application of categorical variables in accelerated life testing and life-stress analysis. In this issue, we provide another application of categorical variables for comparing test data and field data.

One of the most difficult activities for a reliability engineer is making a quantifiable connection between reliability results from in-house testing and the reliability experienced with items in the field. Often, tests will be performed on products in development in order to make an estimate of the reliability in the field. The results of these tests, however, may not match the actual field performance once the product has been released. In this article, we look at a way of using the proportional hazards model to help quantify an acceleration factor that can link lab and field reliability performance.

Treating Common Cause Failures in Fault Trees

Common cause failure analysis is important in reliability and safety studies, as common cause failures often dominate random hardware failures. Systems affected by common cause failures are systems in which two or more events have the potential of occurring due to the same cause. Some typical common causes include impact, vibration, pressure, grit, stress and temperature. ReliaSoft provides an innovative approach to handle common cause failures. Failures that cause different events to happen can be modeled with mirror blocks in BlockSim.