PRINTED WIRING ASSEMBLIES : RELIABILITY STRESS SCREENING
Page 1 Scope . . . . . . . . . . . . . . . . . . . . . . . . 2 2 Field of application . . . . . . . . . . . . . . . . . . . 2 3 Reference . . . . . . . . . . . . . . . . . . . . . . . 2 4 Definitions . . . . . . . . . . . . . . . . . . . . . . . . 2 5 Sampling . . . . . . . . . . . . . . . . . . . . . . . 3 5.1 Sample preparation . . . . . . . . . . . . . . . . . 3 5.2 RSS time planning . . . . . . . . . . . . . . . . . 4 5.3 Reduced RSS process determination . . . . . . . 4 6 Method of RSS . . . . . . . . . . . . . . . . . . . . 4 6.1 Principle . . . . . . . . . . . . . . . . . . . . . . . 4 6.1.1 Initial RSS test . . . . . . . . . . . . . . . . . 4 6.1.2 Optimum RSS process duration . . . . . . . 4 6.1.3 Function test . . . . . . . . . . . . . . . . . . 4 6.1.4 Pass/failure criteria . . . . . . . . . . . . . . 4 6.1.5 Failure analysis . . . . . . . . . . . . . . . . 5 6.1.6 Selection of stress types and stress levels . . . 5 6.2 Applicable stress types . . . . . . . . . . . . . . . 5 6.2.1 Constant high temperature . . . . . . . . . . 5 6.2.1.1 Passive “bake” process . . . . . . . . 5 6.2.1.2 “Bake” process with applied voltage . . . 6 6.2.1.3 “Bake” process with power dissipation . . 6 6.2.2 Low/high temperature cycling . . . . . . . . . 6 6.2.2.1 Passive temperature cycling . . . . . 6 6.2.2.2 Temperature cycling with power dissipation . . . . . . . . . . . . . . . . 6 6.2.3 Vibration and other mechanical stress . . . . 7 6.2.3.1 Fixed frequency sinusoidal vibration . . . 7 6.2.3.2 Swept frequency sinusoidal vibration . . 8 6.2.3.3 Random vibration . . . . . . . . . . . 8 6.2.3.4 Bump . . . . . . . . . . . . . . . . . 8 6.2.3.5 Other mechanical stresses . . . . . . 8 6.2.4 Combination of temperature cycling and random vibration . . . . . . . . . . . . . . . . . . . . 8 6.2.5 Humidity . . . . . . . . . . . . . . . . . . . . 9 6.2.5.1 Constant high humidity and temperature . . . . . . 9 6.2.5.2 High humidity and temperature cycling . . . . . . 9 6.2.6 Operational stress . . . . . . . . . . . . . . . 9 6.2.6.1 Constant operational stress . . . . . . 9 UDC 621.38
Field failures of electronic systems
Results of a research project recently concluded at the Danish Engineering Academy are presented. The scope of the research was to investigate the field-failure pattern of electronic systems of some complexity. The project included a close survey of 10000 to 15000 electronic systems in use in Denmark. A physically-explainable model is demonstrated where the device lifetimes are linked directly to the system failure pattern, without any restrictions on the device-lifetime distributions. This permits real-life components in the model. When the system failure data are known the model can be applied as an analysis tool, which makes it well suited for electronic systems; the reverse application is to use the model for improved reliability predictions based on realistic information about device-distributions.<<ETX>>
Prediction of a representative point for rail temperature measurement by considering longitudinal deformation
Monitoring rail temperature is very important for determining the safe running speed of trains and to prevent buckling. In general, the maximum variation of the internal rail temperature can be >7 ℃ depending on the point of measurement. However, there is as yet no sufficient information about how to predict the measurement point to represent the thermal deformation due to temperature distribution. In this study, the authors report a new point, called the representative measurement point, at which the rail temperature can be measured. This point considers the average deformation of the rail through structural analysis by adopting experimental and actual rail temperature data. The authors designed and installed a measurement system similar to an actual rail environment. Using the system, various data were acquired (internal/surface rail temperature and weather data) for 10 months. On the basis of these data, an analysis was done to calculate the average deformation point through thermal analysis. Finally, the representative measurement point was proposed as the position at which the average deformation point converges regardless of weather or seasons. The authors believe that the method described herein is advantageous in that it could be used in a high-accuracy temperature-monitoring system and for predicting thermal deformation and buckling.