Telcordia software to calculate the reliability prediction of electronic equipment based on the Telcordia (Bellcore) TR and SR standards. Free trial. Telcordia Telecom Information SuperStore – Reliability Prediction Procedure for The following documents were fully or partly replaced by SR TR Bellcore TR – Download as PDF File .pdf), Text File .txt) or read online.

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Bellcore/Telcordia Predictions

Electronic devices with aluminum or aluminum alloy with small percentages of copper and silicon metallization are subject to corrosion failures and therefore can be described bellcode the following model [11]:. Issue 4 of SR provides all the tools needed for predicting device and unit hardware reliability, and contains important revisions since the document was last issued.

The Telcordia standard also documents a recommended method for predicting serial system hardware reliability. The following documents were fully or partly replaced by SR Screen shots click to enlarge Grid view Dialog view Chart view. Tables needed to facilitate the calculation be,lcore reliability predictions.

Tr-32 based on field data The Telcordia standard also documents a recommended method for predicting serial system hardware reliability. This leads to the concept of reliability prediction.

Notice 1 and Notice 2 Revised generic device failure rates in Section 8, based mainly on new data for many components. Using this equation, the parameters B and C calculated by ALTA can bellcode be transformed to the parameters described above for the Arrhenius relationship.

The MIL-HDBK predictive bellcode consists of two parts; one is known as the parts count method and the other is called the part stress method [1]. Accurate prediction of the reliability of electronic products requires knowledge of the components, the design, the manufacturing process and the expected operating conditions.

Three factors are usually considered for testing: Therefore, the prediction is usually more accurate, given that enough samples are used in the testing. The most common failure mode is “conductor open.

This lends the procedure and the predictions derived from it a high level of credibility free from the bias of any individual supplier or service provider. Figure 5 shows the reliability plot and the estimated B10 life at the usage temperature level. With this method, a test is conducted on a sufficiently large sample of units operating under normal usage conditions.


The advantages and disadvantages of empirical methods have been discussed a lot in the past three decades. For example, for the Weibull distribution, the life characteristic is the scale parameter gr-332 and for the lognormal distribution, it is the log mean. On the bellcorw hand, with the life testing method, since the failure data from your own particular products are obtained, the prediction results usually are more accurate than those from a general standard or model.

The Black model employs external heating and increased current density and is given by:. In using the above models, the model parameters can be determined from the design specifications or operating conditions. However, if you think your products do not exhibit a constant failure bellcoge and therefore cannot be described belocore an exponential distribution, the life characteristic usually will not be the MTBF.

This valuable feature comes in especially handy when it is necessary to transfer data from one project or library to another. These powerful facilities transfer as much of the available information as possible, saving you valuable time and effort.

The usage temperature level is Kelvin. The standard provides the generic failure rates and three part stress factors: Recommended methods for predicting device and unit hardware reliability.

It contains instructions for suppliers to follow when providing predictions of their device, unit, or serial system reliability. In today’s competitive electronic products market, having higher reliability than competitors is one of the key factors for success.

Generally, chemical reactions can be accelerated by increasing the system temperature.

Bellcore/Telcordia Reliability Prediction in Lambda Predict

In Method III, the predicted failure rate is a weighted average of the generic steady-state failure rate and the field failure rate. For this example, the life of an electronic component is considered to be affected by temperature.


Time plot and calculated B10 life for the analysis. The empirical or standards based methods can be used in the design stage to quickly obtain a rough estimation of product reliability. Notice 1 in and Notice 2 in Time plot and the calculated B10 life for the analysis. Issue 4 of SR contains: It can also be used directly by telecommunications service providers for product reliability evaluation.

These predictions provide necessary input to system-level reliability models for predicting expected downtime per year and system availability. However, in this section of the article, we are using the term life testing method to refer specifically to a third type of approach for predicting the reliability of electronic products.

Bellcore/Telcordia Reliability Prediction in Lambda Predict

Bellcore capacitor failure rate example. Because of dissatisfaction with military handbook methods for their commercial products, Bellcore designed its own reliability bwllcore standard for commercial telecommunication products. Once the prototype of a product is available, lab tests can be utilized to obtain more accurate reliability predictions. This empirically hr-332 model is known as the Arrhenius equation. First, we will discuss empirical prediction methods, which are based on the experiences of engineers and on historical data.

As an example, suppose that an IC board is tested in the lab and the failure data are recorded. Clarification and guidance on items raised by forum participants and by bllcore asked questions from users.

This procedure also documents a recommended bellckre for predicting serial system hardware reliability. Time plot and calculated B10 life. The models allow reliability prediction to be performed using three methods for predicting product reliability: Historically, this term has been used to denote the process of applying mathematical models and component data for the purpose of estimating the field reliability of a system before failure data are available for the system.