Reliability Prediction Models

Note: This is the second part of a three-part article. Part 1 identified the major factors in reliability prediction models that contribute to predicting component failure. This article, Part 2, describes the most widely accepted reliability prediction standards applied in current projects. Part 3 will provide guidelines for making a sound judgment when deciding which standard to apply to a particular analysis.

Part 2 of 3


Reliability prediction model preferences vary greatly by industry and geographic location. In addition, the various models have unique characteristics that may or may not make that particular standard a better fit for your application. These characteristics include field or test data, confidence intervals and process grades, among others.

The following paragraphs explore the most popular reliability standards, including MIL-HDBK-217, Telcordia, 217Plus, NPRD/EPRD, and some lesser used models such as NSWC-98/LE1, PRISM, IEC62380, SN29500, HRD5, and GJB/z 299B.

Most Popular Reliabiltiy Prediction Standards


The earliest standard to appear was MIL-HDBK-217, Military Reliability Prediction of Electronic Equipment, developed by the United States Department of Defense (DOD) for their suppliers of military equipment. Because of its age, and due to the fact that it was developed from a customer’s point of view, MIL-HDBK-217 typically yields pessimistic results (i.e. higher predicted failure rate). There are several approaches to overcome its pessimistic results, the most recent of which is the ANSI/VITA 51.1-2008 publication. Accepted and known worldwide, it is used by commercial companies and the defense industry. MIL-HDBK-217 models support the ability to perform parts count and parts stress predictions.


The Telcordia standard, Reliability Prediction Procedure for Electronic Equipment (Technical Reference SR-322) was initially developed by AT&T Bell Lab, who modified MIL-HDBK-217 to better reflect failure rates that they were experiencing in the field. Like MIL-HDBK-217, these models include the ability to perform parts count or parts stress prediction. Telcordia also supports various calculation methods that allow the user to refine their predicted failure rate based on burn-in, laboratory, and/or field data. In addition, Telcordia supports user-definable confidence levels and calculation of a mean failure rate and standard deviation for each part. The most current version is Telcordia Issue 3, released in 2011.


217Plus Process Grades Handbook of 217Plus Reliability Prediction Models is the basis for the 217Plus standard. It was published in 2006 by the Reliability Information Analysis Center (RiAC), a DoD Information Analysis Center. The successor to the PRISM standard, 217Plus supports all the major component categories found in MIL-HDBK-217. And like MIL-HDBK-217, 217Plus supports both parts count and parts stress predictions. This standard allows the user to incorporate experiences from similar equipment utilizing Bayesian analysis, and also accounts for “soft factors” related to the level of maturity of the supplier/manufacturer through the use of Process Grade factors.


While NPRD and EPRD Libraries are not technically calculation models, they supply failure rates for thousands of parts.

These databooks are electronic databases of failure rates published by the RIAC (Reliability Information Analysis Center). While reliability prediction standards like MIL-HDBK-217 contain mathematical models that are derived from empirical field failure data, these databooks contain historically observed field failure rates for commercial quality components and other part types not addressed by MIL-HDBK-217 that you can use for unsupported part types. NPRD 2011 contains failure rates for more than 80,000 types of components.

Other Reliability Prediction Standards

FIDES 2009

The FIDES models are based on the following publications published by the FIDES Group: FIDES Guide 2004 Issue A, Reliability Methodology for Electronic Systems and FIDES Guide 2009, Reliability Methodology for Electronic Systems. The base failure rates calculated by a FIDES model are always adjusted by π (Pi) factors for process grades, application factors, and ruggedized factors to take non-component variables into account. The FIDES 2009 model can also adjust base failure rates by π factors for lead free factors. The FIDES 2009 model supports families count, parts count, and parts stress, predictions.


The PRISM model was released in March 2000. It deviates from traditional reliability prediction methodologies by allowing you to factor in component, assembly, and system test data. It also addresses system level design and manufacturing processes to refine the system prediction. The original PRISM model included only six models (resistors, capacitors, diodes, transistors, microcircuits and thyristors). In addition, component and system assessment models address not only operational aspects but also non-operational and/or dormant aspects of a part or system. PRISM has since been superseded by 217Plus.

IEC TR 62380

The IEC TR 62380 model is based on Reliability Data Handbook - Universal Model for Reliability Prediction of Electronic Components, PCBs, and Equipment, published by the International Electrotechnical Commission (IEC). This standard has a complexity similar to Telcordia, but has its own dedicated component categories, and therefore is not compatible with the other standards. IEC TR 62380 uses cycling profiles and their applicable phases as a basis for failure rate calculations, and considers the effects of thermal cycling on the component failure rate.

Siemens SN 29500 v1

The Siemens SN 29500 model is based on IEC 61709, Electronic Components - Reliability - Reference Conditions for Failure Rates and Stress Models for Conversion. It provides frequently updated failure rate data at reference conditions as well as parts count and parts stress predictions. The reference conditions adopted by this model are typical for the majority of applications of components in systems. If operating conditions differ significantly from reference conditions, this model supports converting the failure rate data at the reference conditions to actual operating conditions.


The Handbook of Reliability Prediction Procedures for Mechanical Equipment, developed by the Naval Surface Warfare Center, contains reliability models for mechanical devices such as springs, bearings, seals, motors, brakes, etc. The most recent version of this standard was released in September 1998.


The Handbook of Reliability Data, published by British Telecom of the United Kingdom, is based on the former RDF2000 standard, CNET 93. The most recent version was released in 1994.

GJB/z 299B

The 299 models are based on the GJB/z 299B and GJB/z 299C publications of the Chinese standard, Reliability Prediction Model for Electronic Equipment. These models are similar to MIL-HDBK-217 models, supporting the ability to perform both parts count and parts stress predictions. In addition to supporting more parts than the 299B model, the 299C model provides alternate parts count and parts stress predictions for components from foreign manufacturers.

Windchill Prediction can use any of the standards described in this article to assess the reliability of your system design. Its superior integration enables you to mix calculation models within a single project, allowing you to select the model most appropriate to each part or component in your design. With Windchill Prediction, the additional analysis capabilities available in one model can typically be applied to any model you use. For example, Telcordia calculation methods for taking field and test data into account in the prediction can also be used with MIL-HDBK-217. Part 3 of this three-part article provides guidelines for making a sound judgment when deciding which reliability prediction standard to apply to a particular analysis. Additional information about Windchill Prediction, supported models, and predictive modeling in general can be found by visiting our Windchill Prediction product page.