MTBF prediction

Reliability prediction methodology provides the basis for reliability evaluation and analysis. By allowing you to assess the reliability of your design prior to production, reliability predictions enable you to build products with confidence. Reliability prediction techniques encompass a broad range of standards and statistical models. By incorporating all globally accepted standards, Reliateck uses Relex Reliability Prediction software which offers the most comprehensive prediction package available. Known as the standard in a broad range of industries, with Relex Reliability Prediction you can be assured you are using the trusted brand name in prediction analytics. Reliateck will provide training and offers Mean Time Between Failure (MTBF) reliability predictions analysis product that addresses needs of most customers. Upon receiving your product Bill of Material (BOM), Percept will use advanced reliability software modeling, along with real world data and our expertise, to predict a MTBF for your product. The service includes a comprehensive report & and consultation from one of our reliability experts.

Mean time between failure (MTBF) predictions has many applications including substantiating a design requirement, identifying reliability drivers, making competitive product evaluations, selecting warranty periods, advertising and marketing. Percept can help you calculate your MTBF.

Prediction using MIL-HDBK-217 or Telcordia® provides a front-end look at mean time between failure. The model can predict MTBF using as little as the part type and count information. As the design progresses it can be updated to include thermal and piece part circuit stress analysis information. MIL-HDBK-217 is useful for both military and commercial electronics. Telcordia prediction models address commercial electronics only. It has the ability to consider the results of burn-in test, assembly and top assembly test, acceptance test, and field performance data. Hence, it can calculate pre-production, production and operational MTBF.