Rdf 2000 reliability data handbook

As the names imply, the parts stress technique requires knowledge of the stress levels on each part to determine its failure rate, while the parts count technique assumes average stress levels as a means of providing an early design estimate of the failure rate. For example, the model for a resistor is as follows:. The approach also assumes an exponential failure distribution and calculates reliability in terms of failures per billion part operating hours, or FITs.

Its empirically based models are in three categories: the Method I parts count approach that applies when there is no field failure data available, the Method II modification to Method I to include lab test data and the Method III variation that includes field failure tracking.

Method I includes a first year modifier to account for infant mortality. Method II includes a Bayes weighting procedure that covers three approaches depending on the level of previous burn-in the part or unit has undergone. Method III includes a Bayes weighting procedure as well but it is based on three different cases depending on how similar the equipment is to that from which the data was collected. For the most widely used Method I case where the burn-in varies, the steady-state failure rate depends on the basic part steady-state failure rate and the quality, electrical stress and temperature factors as follows:.

It provides the ability to update predictions based on test data and addresses factors such as development process robustness. It includes a means to include software reliability but is limited by the fact that it does not yet include models for all commonly used devices.

Quantitative values for the individual factors are determined through an extensive question and answer process intended to benchmark the extent that measures known to enhance reliability are used in design, manufacturing and management processes. The methodology generally ignores the issue of defects escaping from the manufacturing process and assumes that product reliability is strictly governed by the predicted life of the weakest link.

Example models address microcircuit die attach fatigue, bond wire flexure fatigue and die fatigue cracking. The models are very complex and require detailed device geometry information and materials properties. In general, the models are thought to be most useful in the early stages of designing devices e. The IEEE Gold Book provides data concerning equipment reliability used in industrial and commercial power distribution systems.

Reliability data for different types of equipment are provided along with other aspects of reliability analysis for power distribution systems, such as basic concepts of reliability analysis, probability methods, fundamentals of power system reliability evaluation, economic evaluation of reliability, and cost of power outage data. The handbook was updated in ; however, the most recent reliability data reflected in the document is only through NPRD data provides failure rates for a wide variety of items, including mechanical and electromechanical parts and assemblies.

The document provides detailed failure rate data on over 25, parts for numerous part categories grouped by environment and quality level. Because the data does not include time-to-failure, the document is forced to report average failure rates to account for both defects and wearout. Cumulatively, the database represents approximately 2. The environments addressed include the same ones covered by MIL-HDBK; however, data is often very limited for some environments and specific part types.

This handbook, developed by the Naval Surface Warfare Center — Carderock Division provides failure rate models for fundamental classes of mechanical components. Examples of the specific mechanical devices addressed by the document include belts, springs, bearings, seals, brakes, slider-crank mechanisms, and clutches. Failure rate models include factors that are known to impact the reliability of the components. These methods are also supported by our reliability prediction software - RAM Commander.

In RDF the difficult to evaluate environment factor is replaced by equipment mission profiles and thermal cycling. The FIDES methodology is applicable to all domains using electronics: aeronautical, naval, military, production and distribution of electricity, automobile, railway, space, industry, telecommunications, data processing, home automation, household appliances, etc.

The FIDES methodology covers items varying from an elementary electronic component to a module or electronic subassembly with a well-defined function.

However, the coverage is usually sufficient to make representative evaluation of reliability in most cases. The FIDES methodology deals with non-functioning phases as well, during either dormant periods between use, or genuine storage. Siemens SN The data necessary for this calculation is actually a subset of the data for calculation of operating failure rates. This module also allows for non-operating mission phases, thus providing Mission Profile Analysis with Non-operating Prediction.

Part category which provides a rough classification of parts e. Next, the user selects a certain subtype e. If the failure rate for required environment does not appear on the list, the failure rate for some other environment can be used. When the item type is defined, it is possible to view a list of component failure rates for different environments and Quality levels, if corresponding data exist in NPRD Nineteen basic mechanical components have been identified for which reliability prediction equations have been developed.

Most mechanical equipment is composed of some combination of these nineteen components.