ABSTRACT
The main causes of initial failures are quality defects such as workmanship error or mal-manufacturing etc. These earlier failures are unacceptable from a viewpoint of customer satisfaction and result in change of their royalty to the company. Therefore, stress screening is usually used to avoid infant mortalities. Burn-in, ESS (Environmental Stress Screening), HASS (Highly Accelerated Stress Screening) are the most representative methods that can eliminate the defects. Although, appropriate specifications, adequate design tolerance and stress analysis for sufficient component derating could decrease the initial failure, it is impossible to cover all possible interactions between components in operation. ALT (Accelerated Life Test) and HALT (Highly Accelerated Life Test) are used to reduce the level of failure rate during a normal operating period. HALT, quite different from standard life testing, design verification testing and end-of-production testing, are becoming recognized as a powerful tool to improve product reliability, reducing warranty costs and increasing customer satisfaction. HALT has been widely used in industry to find out the weak point in a product in a short time (Hobbs, 2000). Although HALT is a powerful tool to find out the latent defects that can be eliminated or reduced prior to the life tests at the
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development stage, however, it is difficult to estimate the lifetime of the product. Therefore, an ALT is conducted for the purpose of estimating the lifetime of the product as soon as possible in an economical way. An ALT employs higher-than-usual levels of a stress to quickly obtain reliability-related quantities (e.g., the qth quantile of the lifetime distribution). In the case of printed circuit board assembly, parts stress analysis (derating) is a basic tool of assuring that stresses, either environmental or operational, are applied below rated values to enhance reliability by decreasing failure rates. It essentially prevents small changes in operating characteristics from creating large increases in failure rate (Reliability toolkit, 2001).
