Reliability Prediction Methods and Models
Our reliability team is proficient in reliability prediction methods listed below. These methods are also supported by our reliability prediction software - RAM Commander.
MIL-HDBK-217 Part Stress & Part Count
MIL-HDBK-217 Module for Parts Stress reliability prediction of electronic equipment based on MIL-HDBK-217 E, F, F Notice 1, F Notice 2, published by Department of Defense, USA.
MIL-HDBK-217 Parts Count reliability prediction Module based on MIL-HDBK-217 E, F Notice 1, F Notice 2 methods for Parts Count.
217Plus - Based on Handbook of 217PlusTM
Reliability Prediction Models, 26 May 2006 by Reliability Information Analysis Center (RIAC).
BEL - BellCore - Module for reliability prediction based on Bellcore document TR-NWT-000332, (Issue 4, Issue 5, Issue 6).
Telcordia - Telcordia SR332, Issue 1, May 2001
Telcordia Issue 2 - Reliability Prediction Procedure for Electronic Equipment, SR-332, Issue 2, September 2006
CNET RDF 93 Revision 2/95
Module for reliability prediction based on CNET, French reliability prediction method for commercial applications.
UTEC 80810, RDF 2000, IEC 62380
RDF 2000 (UTEC 80810) is a new version of the French reliability prediction standard that covers most of the same components as MIL-HDBK-217. In RDF 2000 the difficult to evaluate environment factor is replaced by equipment mission profiles and thermal cycling. RDF2000 provides complex models that can handle permanent working, on/off cycling and dormant applications.
IEC 62380 (RDF 2003)
Updated version of RDF 2000 UTEC 80810 method – French Telecom reliability prediction Standard. It includes most of the same components as MIL-HDBK-217. Since it is difficult to evaluate the environmental factor, RDF 2000/2003 uses equipment mission profiles and thermal cycling for evaluation. RDF2000/2003 provides complex models that can handle permanent working, on/off cycling and dormant applications. As this standard becomes more widely used, it could become the international successor to the US MIL-HDBK-217.
FIDES Guide 2009
This method replaces the FIDES Guide 2004 issue A (also published by the UTE under reference UTEC 80811). 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. Coverage of item families by FIDES is not absolutely exhaustive. However, the coverage is usually sufficient to make representative evaluation of reliability in most cases.
• Failures derived from development or manufacturing errors.
• Overstresses (electrical, mechanical, thermal) related to the application and not listed as such by the user.
The FIDES methodology deals with non-functioning phases as well, during either dormant periods between use, or genuine storage.
BRT - British Telecom -British Telecom Module for reliability prediction based on British Telecom document HRD-4 or HRD-5.
GJB299 -Chinese reliability standard for both Part Stress and Part Count.
Siemens SN29500.1 - Siemens reliability standard
Siemens SN 29500-2005-1 - Siemens reliability standard updated version
RADC-TR-85-91 Non-operating Reliability Prediction
Module for calculating non-operating failure rates based on RADC TR-85-91. The data necessary for this calculation is actually a subset of the data for calculation of operating failure rates. Thus, no additional data entry is required to run RADC-TR-85-91.
This module also allows for non-operating mission phases, thus providing Mission Profile Analysis with Non-operating Prediction.
NPRD-95 Non-electronic Parts Reliability Data
NPRD-95 module contains a library of failure rates for a large number of non-electronic components under various environments. The source of this data is the document NPRD-95, "Non-electronic Parts Reliability Data", released by RAC.
Part category which provides a rough classification of parts (e.g., actuators, batteries, pumps, etc.) should be selected first for each device. Next, the user selects a certain subtype (e.g., for batteries - Carbon Zinc, Lithium, etc.).
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-95.
NSWC-98 Handbook of Reliability Prediction Procedures for Mechanical Equipment
This handbook by the US NAVY presents an approach for determining the reliability characteristics of mechanical equipment. The design evaluation program initiated by the Carderock Division of the Naval Surface Warfare Center includes a methodology for evaluating a design for R&M that considers the material properties, operating environment and critical failure modes at the component level. 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. A designer can utilize the equations to determine individual component reliability and then combine the results in accordance with the system reliability diagram to determine total system reliability in its operating environment.
Stress/Strength Analysis - Structural/Mechanical Analysis of Components and Systems
Stress/Strength analysis method determines the probability of a failure based on the probability of stress exceeding strength.
Calculation of Failure Probability (Unreliability) based on:
• Distributions of Stress and Strength
• Variation information between Stress and Strength (Factor of Safety n and Variations)
ALD Reliability Prediction Software module
Reliability Analysis Software module
Stress/Strength prediction module
Reliability Block Diagram Tool
Download the latest version of RAM Commander V8.7 (2019)