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Standards Based Reliability Prediction: Applicability and Usage to Augment RBDs
Part II: The Standards for Reliability Prediction
Note: This is the second part of a three-part series about standards based reliability prediction and ReliaSoft's newly introduced Lambda Predict software package. Part I introduced standards based reliability prediction and discussed when it is appropriate to use and when it should be avoided. This part discusses the different major reliability prediction standards. Part III will give an example of how standards based reliability prediction and Lambda Predict can be used to complete a Reliability Block Diagram (RBD) when data is not available.
Reliability prediction plays a major role in many reliability programs across government and industry. Standards based reliability prediction relies on defining failure rates for the components of a system based on predefined standards, depending on the types of components, the use environment, the way the components are connected and the reliability prediction standard. These component failure rates are then used to obtain an overall system failure rate.
Over the past few decades, several standards have been introduced by various governments and industry organizations to assist in conducting this type of analysis. The standards define models for different component types based on test data. The models assume a constant failure rate (i.e. no wearout or early failures problem), which generally describes the useful life of a component where failures are considered random events. The following is an overview of the common standards that are available in Lambda Predict as different modules. Note that Lambda Predict provides redundancy calculation in addition to each of these standards.
MIL-217 Standard
The MIL-217 standard is a reliability prediction program based on the
internationally recognized method of calculating electronic equipment
reliability given in MIL-HDBK-217 (published by the US Department of
Defense). This standard uses a series of models for various categories of
electronic, electrical and electro-mechanical components to predict failure
rates that are affected by environmental conditions, quality levels, stress
conditions and various other parameters. These models are fully detailed
within MIL-HDBK-217.
This standard supports two methods of reliability prediction as described in MIL-HDBK-217F: Parts Count and Part Stress Analysis.
Parts Count Method
Parts Count generally requires information such as part quantities, quality
levels and the application environment. Because it requires less information
than Part Stress Analysis, it is most applicable early in the design phase
and proposal formulation. Parts Count prediction defines the overall
equipment failure rate as:
where:
| n | = Number of part categories |
| Ni | = Quantity of ith part |
 |
= Failure rate of ith part |
 |
= Quality Factor of ith part |
If the equipment consists of parts operating in more than one environment, then this equation is applied to each portion of the equipment that is operating in a distinct environment. The sum of the failure rates of all environments represents the overall equipment failure rate.
Part Stress Analysis Method
Part Stress Analysis requires more detailed information and is usually
applicable later in the design phase. The Part Stress Analysis method will
usually result in a lower failure rate or higher system reliability (a less
conservative result) than the Parts Count method would produce.
For this type of analysis, the models are much more detailed and varied across part types. For example, the model for microcircuits, memories is:
where:
| C1 | = Die Complexity Failure Rate |
 |
= Temperature Factor |
| C2 | = Package Failure Rate |
 |
= Environment Factor |
 |
= EEPROM Read/Write Cycling Induced Failure Rate |
 |
= Quality Factor |
 |
= Learning Factor |
Bellcore (Telcordia) Standard
The Bellcore standard predicts the reliability of electronic equipment based
on the Bellcore (Telcordia) standards TR-332 Issue 6 and SR-332 Issue 1
(published by AT&T Bell Labs). This type of prediction has only one focus:
electronic equipment. It can provide predictions at the component level,
system level or project level for COTS (Commercial Off-The-Shelf) parts.
Bellcore utilizes three methods for predicting product reliability:
Method I: Parts Count
Method II: Combines Method I predictions with laboratory data
Method III: Predictions based on field data
NSWC Standard
This is a mechanical standard that uses a series of models for various
categories of mechanical components to predict failure rates that are
affected by temperature, stresses, flow rates and various other parameters.
These models are fully detailed in the Naval Surface Warfare Center Handbook
of Reliability Prediction Procedures for Mechanical Equipment, NSWC-98/LE1
(published by the US Navy).
Due to the wide range of failure rates that occur in apparently similar components, the NSWC Mechanical Prediction module does not rely on failure rate data alone. It also accounts for material properties, operating environment and critical failure modes at the component level.
The categories of mechanical equipment covered by this standard are:
Electric Motors
Compressors
Actuators
Gears and Splines
Pumps
Slider-Crank Mechanisms
Mechanical Couplings
Brakes and Clutches
Threaded Fasteners
Springs
Valve Assemblies
Seals and Gaskets
Solenoids
Bearings
Filters
RDF 2000 Standard
The IEC 62380 TR Edition 1 (formerly known as UTE C 80-810) standard is
another widely used reliability prediction program. It is based on the
French Telecommunications standard RDF 2000.
The IEC 62380 TR Edition 1 reliability calculation guide for electronic components and optical cards offers a significant step forward in reliability prediction when compared to some of the older reliability standards. Calculation models take into account directly the influence of the environment. The thermal cycling seen by cards and mission profiles undergone by the equipment replace the environment factor, which can be difficult to evaluate. These models can handle continuous working, on/off cycles and dormant applications. Failures related to component soldering are included in the component failure rate.
The IEC 62380 (RDF 2000) Prediction Module provides:
Failure Rate calculation at
component, block and system level
Unavailability calculation at system level
Repairable system calculation
Component and Block Pi Factors
China 299B Standard
The China 299B standard is a reliability prediction program based on the
internationally recognized method of calculating electronic equipment
reliability given in the Chinese Military Standard GJB/z 299B 299B. This
standard uses a series of models for various categories of electronic,
electrical and electro-mechanical components to predict failure rates that
are affected by environmental conditions, quality levels, stress conditions
and various other parameters.
The 299B standard contains two methods of reliability prediction: Parts Count Analysis and Part Stress Analysis.
The 299B Prediction Module provides:
Failure Rate calculation at
component, block and system level
Unavailability calculation at system level
Repairable system calculation
Part Stress and Parts Count analysis
Component and Block Pi Factors