Reliability Data Collection and Analysis Resources


The purpose of this course is to provide illustrative examples of the more common mathematical calculations and statistical techniques utilized by reliability engineers in the practical performance of their daily activities.
Course Dates: Tuesday, Nov. 15 – Thursday, Nov. 17, 2022.
Course Location: DoubleTree Suites by Hilton Orlando – Disney Springs.
Registration Deadline: Oct. 14, 2022. Save your seat for Quantitative Reliability Analyses – Practical Approaches!
View the other course option, Software Failure Modes Effects Analysis, offered the same date and time. 



Nonelectronic Parts Reliability Data – NPRD-2016 

The 2016 Edition of the Nonelectronic Parts Reliability Data publication (NPRD-2016) presents field failure rate data on a wide variety of electrical assemblies and electromechanical/mechanical parts and assemblies. Compared to its predecessor NPRD-2011 publication, NPRD-2016 adds 138,000 new parts and over 370 billion part hours, representing approximately a 400% increase in content. The expanded part types and data in NPRD-2016 cover ground, airborne and naval environments.
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Electronic Parts Reliability Data – EPRD-2014

The Electronic Parts Reliability Data (EPRD) publication contains field failure rate data for commercial and military electronic components for use in reliability analyses. Component types include integrated circuits, discrete semiconductors (diodes, transistors, optoelectronic devices), resistors, capacitors, and inductors/transformers.
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Failure Mode / Mechanism Distributions – FMD-2016 

This databook contains field failure mode and mechanism distribution data on a variety of electrical, mechanical, and electromechanical parts and assemblies. This data can be used to assist in the performance of reliability analyses and assessments such as Failure Modes, Effects and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA).
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Reliability Online Automated Databook System (ROADS)

The Reliability Online Automated Databook System (ROADS) is a subscription that provides customized access to all the Quanterion Databooks: Nonelectronic Parts Reliability Data (NPRD), Electronic Parts Reliability Data (EPRD) and/or Failure Modes / Mechanisms Distribution (FMD). Learn more.



Tools and Resources

System Reliability Toolkit-V

This fifth toolkit in the popular series developed by Quanterion reflects the updated focus in RMQSI. Several of the same Quanterion staff members have been involved in all five titles in the series. Over 30 new topics have been added, and several others updated, with a minimum removal of topics from the “System Reliability Toolkit.” In addition, Appendices have been added stressing the practical application of the document’s practices throughout a program’s life. Learn more.


Warranty CalculatorWarranty Calculator

The Warranty Calculator planning and analysis tool provides automated calculations and comparisons for ten different warranty types in common use. The tool also includes data, information and references that provide further guidance for over 30 additional warranty types. Learn more.


Reliability Toolkit: Commercial Practices Edition

The “Reliability Toolkit: Commercial Practices Edition” helps both the commercial and military sectors deal with developing and manufacturing reliable products in today’s competitive markets. Over 80 topics, representing every aspect of a product’s reliability over its life cycle, have been well received by thousands of Toolkit users to date. Learn more.

NOTE: The “Reliability Toolkit: Commercial Practices Edition” was published in 1995. It has been updated twice since publication with the latest version, “System Reliability Toolkit-V”.


Practical Applications of the RIAC System Reliability ToolkitPractical Applications of the RIAC System Reliability Toolkit

The purpose of this publication is to provide illustrative examples of the more common mathematical calculations and statistical techniques utilized by reliability engineers in the practical performance of their daily activities. It is intended to be used as a companion to the RIAC “System Reliability Toolkit,” as the foundations of all of the techniques illustrated in this publication are discussed. Learn more.



Reliability Modeling - The RIAC Guide to Reliability Prediction, Assessment and EstimationReliability Modeling – The RIAC Guide to Reliability Prediction, Assessment and Estimation

The purpose of this publication is to provide guidance on modeling techniques that can be used to quantify the reliability of a product or system. There are many ways in which this can be accomplished, depending on the product or system and the type of information that is available, or practical to obtain. It reviews the possible approaches, summarizes their advantages and disadvantages, and provides guidance on selecting a methodology based on the specific goals and constraints of the analyst. Learn more.


Mechanical Analysis and Other Specialized Techniques for Enhancing Reliability (MASTER)

Mechanical Analysis and Other Specialized Techniques for Enhancing Reliability (MASTER)

This document is specifically targeted to address the competing approaches to part reliability predictions, including statistical analysis of relevant failure data, physics of failure modeling, empirical failure models and data, and other less common but acceptable methods. Learn more.




Weibull Analysis

Weibull Analysis

The statistical analysis of an item’s failure data is widely regarded as one of the most accurate techniques for assessing its reliability in a specific application or environment. Though there are many different statistical distributions (e.g., exponential, lognormal, etc.), the Weibull distribution is especially useful because of its ability to characterize a wide range of potential data trends. More specifically, it can be fit to a dataset exhibiting an increasing, constant or decreasing failure rate, a unique feature that separates the Weibull distribution from its counterparts. This feature also allows the Weibull distribution to mimic other statistical distributions, and is the reason why it is often used as a first approximation for fitting a collection of failure data. Learn more.


To learn more about reliability data collection and analysis, visit Quanterion’s associated reliability data collection and analysis informational page.

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