SIST-TP CEN/TR 17602-30-08:2022
(Main)Space product assurance - Components reliability data sources and their use
Space product assurance - Components reliability data sources and their use
This handbook identifies data sources and respective methods that can be used for reliability prediction of components. It proposes suitable data sources and an application matrix for component families.
Raumfahrtproduktsicherung - Datenquellen zur Bauteilezuverlässigkeit und ihre Anwendung
Assurance produit des projets spatiaux - Sources de données de fiabilité composants et leur utilisation
Zagotavljanje kakovosti proizvodov v vesoljski tehniki - Viri podatkov o zanesljivosti komponent in njihova uporaba
V tem priročniku so opredeljeni viri podatkov in ustrezne metode, ki jih je mogoče uporabiti za napoved zanesljivosti komponent. Podaja predloge za primerne vire podatkov in matrike uporabe za družine komponent.
General Information
Standards Content (Sample)
SLOVENSKI STANDARD
SIST-TP CEN/TR 17602-30-08:2022
01-februar-2022
Zagotavljanje kakovosti proizvodov v vesoljski tehniki - Viri podatkov o
zanesljivosti komponent in njihova uporaba
Space product assurance - Components reliability data sources and their use
Raumfahrtproduktsicherung - Datenquellen zur Bauteilezuverlässigkeit und ihre
Anwendung
Assurance produit des projets spatiaux - Sources de données de fiabilité composants et
leur utilisation
Ta slovenski standard je istoveten z: CEN/TR 17602-30-08:2021
ICS:
03.120.99 Drugi standardi v zvezi s Other standards related to
kakovostjo quality
49.140 Vesoljski sistemi in operacije Space systems and
operations
SIST-TP CEN/TR 17602-30-08:2022 en,fr,de
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
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SIST-TP CEN/TR 17602-30-08:2022
TECHNICAL REPORT CEN/TR 17602-30-08
RAPPORT TECHNIQUE
TECHNISCHER BERICHT
December 2021
ICS 49.140
English version
Space product assurance - Components reliability data
sources and their use
Assurance produit des projets spatiaux - Sources de Raumfahrtproduktsicherung - Datenquellen zur
données de fiabilité composants et leur utilisation Bauteilezuverlässigkeit und ihre Anwendung
This Technical Report was approved by CEN on 22 November 2021. It has been drawn up by the Technical Committee
CEN/CLC/JTC 5.
CEN and CENELEC members are the national standards bodies and national electrotechnical committees of Austria, Belgium,
Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy,
Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of North Macedonia, Romania, Serbia,
Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and United Kingdom.
CEN-CENELEC Management Centre:
Rue de la Science 23, B-1040 Brussels
© 2021 CEN/CENELEC All rights of exploitation in any form and by any means Ref. No. CEN/TR 17602-30-08:2021 E
reserved worldwide for CEN national Members and for
CENELEC Members.
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Table of contents
European Foreword . 4
1 Scope . 5
2 References . 6
3 Terms, definitions and abbreviated terms . 7
3.1 Terms from other documents .7
3.2 Abbreviated terms. 7
4 Selection of reliability data and methods . 8
4.1 Introduction .8
4.2 Selection process . 8
4.3 Description of data .11
4.3.1 Handbook reliability data .11
4.3.2 Manufacturer or user data .11
4.4 Selection criteria for input sources . 11
4.4.1 Reliability handbooks .11
4.4.2 Manufacturer or user data .12
4.5 Justification for choice .14
4.6 Instructions for use .15
4.6.1 Reliability handbooks .15
4.6.2 Manufacturer or user data .15
4.7 Considerations for reliability prediction for mechanical parts . 16
4.7.1 General . 16
4.7.2 Part failure data analysis .17
4.7.3 Empirical reliability relationships . 17
4.7.4 Analysis of the stress-strength . 17
4.7.5 Handbook data .18
4.8 Documentation .18
Annex A Potential data sources . 19
A.1 Introduction .19
A.2 EEE parts .19
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A.2.1 AT&T reliability manual .19
A.2.2 FIDES (UTE C 80-811) .19
A.2.3 HRD5 .19
A.2.4 IEEE Gold Book .20
A.2.5 IRPH .20
A.2.6 MIL-HDBK-217 .20
A.2.7 PRISM (RAC / EPRD) .20
A.2.8 RDF 2000 (UTE C 80-810, IEC-62380-TR Edition 1) . 20
A.2.9 Siemens SN29500 .21
A.2.10 Telcordia SR-332 .21
A.3 Mechanical parts .21
A.3.1 NPRD-95 .21
A.3.2 NSWC-94/L07 - Handbook of Reliability Prediction Procedures for
Mechanical Equipment .22
Annex B Applicability and limitations of MIL-HDBK-217F . 23
B.1 Introduction .23
B.2 EEE families applicability matrix .23
B.3 EEE packages applicability matrix (based on paragraph 5.6 MIL-HDBK-217) 26
B.4 EEE part equivalent quality grades .26
Annex C Justification . 28
Bibliography . 30
Figures
Figure 4-1: Boundaries of ECSS-Q-HB-30-08 (inputs and outputs) .8
Figure 4-2: Selection process .9
Figure 4-3: Decision logic . 10
Figure 4-4: Selection of manufacturer or user data . 13
Tables
Table 4-1: Reliability handbook selection criteria .12
Table 4-2: Percentiles of the χ² Distribution at 60 % and 90 % confidence for n<30 . 16
Table B-1 : EEE families applicability matrix for MIL-HDBK-217 . 24
Table B-2 : EEE package applicability .26
Table B-3 : Designation of EEE part quality grades . 27
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European Foreword
This document (CEN/TR 17602-30-08:2021) has been prepared by Technical Committee CEN/CLC/JTC 5
“Space”, the secretariat of which is held by DIN.
It is highlighted that this technical report does not contain any requirement but only collection of data
or descriptions and guidelines about how to organize and perform the work in support of EN 16602-30.
This Technical report (CEN/TR 17602-30-08:2021) originates from ECSS-Q-HB-30-08A.
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. CEN [and/or CENELEC] shall not be held responsible for identifying any or all such
patent rights.
This document has been prepared under a mandate given to CEN by the European Commission and
the European Free Trade Association.
This document has been developed to cover specifically space systems and has therefore precedence
over any TR covering the same scope but with a wider domain of applicability (e.g.: aerospace).
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1
Scope
This handbook identifies data sources and respective methods that can be used for reliability prediction
of components. It proposes suitable data sources and an application matrix for component families.
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2
References
EN Reference Reference in text Title
EN 16601-00-01 ECSS-S-ST-00-01 ECSS - Glossary of terms
EN 16602-30 ECSS-Q-ST-30 Space product assurance - Dependability
EN 16602-40 ECSS-Q-ST-40 Space product assurance - Safety
EN 16602-60 ECSS-Q-ST-60 Space product assurance - Electrical, electronic and
electromechanical (EEE) components
IEC 60050-191 International Electrotechnical Vocabulary - Chapter
191: Dependability and quality of service
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3
Terms, definitions and abbreviated terms
3.1 Terms from other documents
For the purpose of this document, the terms and definitions from ECSS-S-ST-00-01 and IEC 60050-191
apply.
3.2 Abbreviated terms
For the purpose of this document, the abbreviated terms from ECSS-S-ST-00-01 apply.
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4
Selection of reliability data and methods
4.1 Introduction
This handbook can be used whenever EEE and mechanical components reliability data or failure rates
are needed to perform quantitative dependability or safety analyses in accordance with ECSS-Q-ST-30
or ECSS-Q-ST-40.
The boundaries of this process are shown in Figure 4-1. Inputs are project requirements, handbook data
and manufacturer or user data. The selection process should consider selection criteria and methods of
use of data. Outputs are usually included in equipment reliability assessments. Selection is supported
by suitable justification.
Project
Requirements
Selection
Criteria
Equipment
Reliability
Assessment
Handbook
Methods for use of
Data and Selection Process
data
Methods
Justification
ECSS-Q-HB-30-08 Perimiter Outputs
Manufacturer/
User Data
Figure 4-1: Boundaries of ECSS-Q-HB-30-08 (inputs and outputs)
4.2 Selection process
The selection of a suitable methodology is made according to Figure 4-2. Where the customer requires
that a reliability prediction be computed according to a particular methodology, contractual
requirements are applicable.
The term “methodology” includes the process, data and equations as defined in a particular handbook
or prediction system.
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Does the methodology
Does customer require any Use the required
Yes adequately address the Yes
particular methodology? methodology
component?
No
Use this document to select
Use the selected
No between a particular handbook or
methodology
manufacturing data
Figure 4-2: Selection process
In the case where there is no prescribed methodology, this handbook should be applied and a suitable
methodology should be selected.
In the case where the prescribed methodology does not adequately address the component under
consideration, this handbook should be applied and a suitable methodology should be selected.
In order to perform any reliability predictions, reliability data is needed as an input, and a suitable
methodology needs to be applied.
Figure 3 shows the decision logic that should be applied when selecting data sources. Data should be
obtained from the following sources, in order of preference:
• Handbook data
• Manufacturer or user data.
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Start
Collect data on
Collect data on
application
components used
environment
Use scoring system
to examine
applicability of
methodology
Is there an applicable
Yes Use it
methodology
No
Use manufacturer/
User data
Figure 4-3: Decision logic
A description of data sources is given in clause 4.3.
The choice of a given data source is acceptable if it satisfies the criteria listed in clause 4.4. Data on the
handbook methodology, the components, environment and use should be collected. A suitable
methodology can be selected by using a weighted score ranking scheme, as described in clause 4.4.1.
The rationale for selection is justified according to clause 4.5.
A suitable methodology or instructions for use is described in clause 4.6.
If a handbook is determined to be not suitable for the component, then manufacturer or user data should
be used.
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4.3 Description of data
4.3.1 Handbook reliability data
There are a number of reliability handbooks available; these publish reliability metrics on a large
number of components. Some examples are provided in Annex A. Care should be taken with such data
since it is not always possible to ascertain the actual source of the data. The data can be a mix of field
and test data, and even interpolated or extrapolated data can be present.
4.3.2 Manufacturer or user data
4.3.2.1 Manufacturer data
Manufacturer’s data is that which is supplied by the manufacturer based on tests on a particular
component. Data is normally presented according to the methods laid out in IEC 60319.
4.3.2.2 User data
User data is that which is produced by the company performing the prediction for the sole purpose of
deriving reliability information about components that can be obtained in no other way. Data can be,
for instance, from in house testing, user experience, lessons learned, or expert judgement. This
procedure is most often used for unique component types.
4.4 Selection criteria for input sources
4.4.1 Reliability handbooks
Table 4-1 provides criteria to be considered for the selection of reliability handbooks. The criteria are
listed in order of importance. In order to provide an acceptable evaluation, each of the questions
mentioned should be addressed by the user.
The user should consider the use of a scoring scheme, which is shown in this table. In this example, if a
selection is made between handbooks, then that which has the higher score is considered acceptable. If
there is only one handbook, the scoring may be used to determine the adequacy of the handbook, by
defining a minimum acceptable score.
The scoring factors given in Table 4-1 are an example. A particular company may wish to change these
scoring factors depending upon their experience.
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Table 4-1: Reliability handbook selection criteria
Item Question Scoring factor
a.
Validity 1a) Is the considered technology covered by the GO / NO GO criteria
handbook?
1b) Is information available on the way in which the data 15 for yes
was collected?
0 for no
1c) If yes to 1a and 1b, are data collected and models 10 for yes
implemented according to an international standard
0 for no
or handbook (e.g. IEC)?
Suitability for 2a) Does the handbook cover the space environment? 10 for yes
space
0 for no
2b) Does the handbook consider the parts stress method? 10 for yes
0 for no
2c) Does the handbook address the quality levels of the 10 for yes
components being used?
0 for no
Maintenance of 3a) Has the handbook data been updated in the last 5 10 for yes
data years?
0 for no
3b) Are there any expectations to update the handbook 10 for yes
data in the next 5 years?
0 for no
International 4a) Is the handbook requested by the customer? 10 for yes
recognition
0 for no
4b) Is the handbook recognized by the reliability 5 for yes
community?
0 for no
Usability 5a) Is a commercial software tool available to support the 5 for yes
handbook?
0 for no
Suitability for 6a) Does the handbook provide extrapolation rules (e.g. 5 for yes
new technologies Moore’s law)?
0 for no
Cost Not considered -
a.
Technology includes the component type, technology, family and package
b.
Space environment includes launch vibrations, space vacuum, radiation, and temperature extremes.
c.
In space applications, the component quality is in accordance with ECSS-ST-Q-60, its equivalent, or as
otherwise specified.
d.
Recognition by the reliability community can include, for example:
- It is an international standard or handbook;
- It is a national standard or handbook (e.g. MIL-HDBK-217);
- It is a recognized industrial or other standard or handbook (e.g. Telcordia SR-332);
- It is otherwise recognized by the reliability community.
4.4.2 Manufacturer or user data
Use of manufacturer or user data is considered if data from a reliability handbook is not suitable. Figure
4-4 depicts the selection of manufacturer or user data.
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Select Data
Source
Is Manufacturer data available? No Is user data available?
Yes
Yes
Is data collected as per IEC
Is data presented as per IEC
60300-3-2 and analysed as per
60319 No
IEC 60300-3-5
No
Yes Yes
Perform very detailed check of
Check data provenance Check data provenance
data provenance
Quality review Quality review
Technical review
Data suitable for use? No Perform Risk Assessment
Yes
Use Data Generate reliability data
Figure 4-4: Selection of manufacturer or user data
The steps for selection are as follows:
1. Select the data source.
2. If manufacturer data is available, check whether data is presented in accordance with IEC
60319, in which case it can be considered for use.
If the data is not presented in accordance with IEC 60319, then a detailed review of the data
should be performed to ensure the following is available:
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o tests and test conditions applied to the components;
o lot sampling;
o number of lots;
o manufacturing and testing period;
o technological representativity;
o failure analysis.
Once this data is available, assess the effect of any missing data with respect to the expected
list above.
3. If user data is available, check whether data is collected and presented in accordance with
IEC 60300-3-2 and IEC 60300-3-5, in which case it can be considered for use.
If data is not presented in accordance with these standards, then a detailed review of data
should be made, to ensure the following is available:
For field return data the following should be reviewed:
o data collection procedures;
o relevance of failures;
o analysis techniques.
For test data the following should be reviewed:
o tests and test conditions applied to the components;
o lot sampling;
o number of lots;
o manufacturing and testing period;
o technological representativity;
o failure analysis.
Once this data is available, assess the effect of any missing data with respect to the expected
list above.
4. Once these checks have been performed, the analyst can decide on the use of the data.
5. In case suitability is not determined, the above steps are repeated to find an alternative.
6. In case a data source cannot be found, a risk assessment should be performed to determine
the necessity for obtaining further data, e.g. via a reliability test programme, whether to
use expert judgement or whether to accept the fact that data is not available for the
particular component under consideration.
4.5 Justification for choice
In order to ensure that any work performed is technically correct, justification for the choices made
should be presented whilst the work is performed. This allows the argument made for the methodology
followed to be understood at some later time. The justification should be included with the reliability
assessment report (see clause 4.7) and may be used as part of any reliability case argued. Annex C
provides more details of the justification.
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4.6 Instructions for use
4.6.1 Reliability handbooks
The reliability models and methods that are described within the selected reliability handbook should
be used. Modifications to the models or methods should be supported with the rationale in accordance
with clause 4.4.
4.6.2 Manufacturer or user data
The selected manufacturer or user data should be used in accordance with IEC 60300-3-5. Test or
manufacturing data that conforms to this criterion is suitable for failure rate calculation. The failure rate
calculation procedure is described hereafter.
The necessary inputs for failure rate calculation are:
• number and nature of defects, and
• device hours (test duration and number of devices).
The number of devices should be derived using lot sampling procedures in accordance with a
recognized sampling plan such as ISO 2859-0.
The failure rate can be assessed using the χ² (Chi-square) distribution for time truncated and failure
truncated tests.
Given the total number of successful part operating hours (T) and the number of failures (f), the
following equations are used to calculate failure rate (λ) from test data:
2 9
χ ×10
n
For a time truncated test, where n = 2f + 2:
λ=
2T
2 9
χ ×10
n
For a failure truncated test, where n = 2f:
λ=
2T
where
λ = is the failure rate in 10-9/hour (FIT) at test conditions;
χ² = is the percentile of the χ² distribution at confidence level (failure rates are provided at 60 %
confidence in the commonly used handbooks listed and described in Annex A);
n = is the degree of freedom of the statistics.
The failure rate can be extrapolated to the operating condition by applying the acceleration factor
between test conditions and operating conditions. Information on acceleration factors can be found in
IEC1709 or IEC 721-3-3
Percentiles of the χ² distribution at 60 % and 90% confidence level are given in Table 4-2 for up to 30
degrees of freedom.
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Table 4-2: Percentiles of the χ² Distribution at 60 % and 90 %
confidence for n<30
n χ² (60%) χ² (90%)
2 1,83 4,61
4 4,04 7,78
6 6,21 10,6
8 8,35 13,4
10 10,5 16,0
12 12,6 18,5
14 14,7 21,1
16 16,8 23,5
18 18,9 26,0
20 21,0 28,4
22 23,0 30,8
24 25,1 33,2
26 27,2 35,6
28 29,2 37,9
30 32,3 40,3
Percentiles of the χ² distribution can be found in various literature.
NOTE The calculated failure rate for a given failure mechanism is highly
influenced by test conditions and the physics of failure. Whatever
the failure mechanism, an acceleration limitation applies. Highly
accelerated tests can induce failure mechanisms that are not
observed in the actual application. This leads to an overestimation
of failure rates. This acceleration limitation applies to all
acceleration factors (e.g. temperature, voltage, and current).
4.7 Considerations for reliability prediction for
mechanical parts
4.7.1 General
For mechanical reliability prediction, four approaches are available:
• part failure data analysis,
• empirical reliability relationships,
• stress-strength, and
• handbook data.
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There are a number of problems that are encountered when performing mechanical predictions and
these are summarized below.
• Part failure analysis
Data often not available
Available data is often grouped (individual times to failure are not available)
For a completely new design, expensive testing may be required.
• Empirical reliability techniques
Models available for limited number of part types
New process/material not previously assessed
Models are often for life and not hazard rate.
• Stress or strength interference analysis
Results are probability of failure not hazard rate
Interference often at extremes of distribution tails
Standard deviation for stress is difficult to get.
• Handbook data
Constant failure rates are assumed
Failure rates are not application sensitive
Design improvements doubtful.
4.7.2 Part failure data analysis
Statistical data analysis is the preferred approach to prediction when accurate failure data exist as part
of a manufacturer’s historical database. This data can also exist as a result of a dedicated reliability test
programme. When such data does exist, the underlying time to failure distribution should be identified
using statistical techniques such as the Weibull analysis. In every case a detailed analysis of failed parts
and their data should be performed to identify trends and failure mechanisms.
4.7.3 Empirical reliability relationships
Empirical reliability relationships are based on extensive testing for different combinations of, for
instance, loading, materials, and dimensions. The tools required to use these models include some
measures of part life and the ability to determine Weibull characteristic life.
4.7.4 Analysis of the stress-strength
An analysis of the stress-strength relationship involves characterization of statistical distributions for
stresses acting on a mechanical part and material strength. The most positive benefit is the
understanding that stress and strength are subject to variability, and if an incorrect underlying
distribution is selected or variability is not accurately characterized, estimated probability of failure can
be significantly in error. In order to perform a stress-strength analysis, the stress distribution and
strength distribution should be determined using best engineering practices.
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If stress is greater than strength, failure occurs. This failure generally occurs in the area under the
intersection of the strength and stress distribution. Hence it is important to understand the shape and
location of these distributions.
More information on stress-strength analysis can be found in IEC 60300-3-1.
4.7.5 Handbook data
Handbook data exists for mechanical parts and contain generic failure rate data, for example the RAC
publication NPRD. Care should be taken since the data can be quoted in, for instance, Failures/h,
Failures/Cycle, or Failures/Mile and should not be directly compared with data available on other
component types.
4.8 Documentation
Reliability assessment documentation should be prepared in accordance with ECSS-Q-ST-30 and ECSS-
Q-ST-40. The documentation includes:
• the selection process for the data sources,
• the description of calculation methods,
• the derived failure rates, and
• the justification for the methodology and data source choices made.
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Annex A
Potential data sources
A.1 Introduction
This Annex provides information to the user concerning data sources for component failure rate
determination. This list is not comprehensive, and is not intended to give a preference for sources. It
remains up to the user to determine which data source is relevant for the application.
A.2 EEE parts
A.2.1 AT&T reliability manual
The AT&T reliability manual is more than just a prediction methodology. Although it outlines
prediction models and contains component failure data the book also describes the AT&T app
...
SLOVENSKI STANDARD
kSIST-TP FprCEN/TR 17602-30-08:2021
01-oktober-2021
Zagotavljanje kakovosti proizvodov v vesoljski tehniki - Viri podatkov o
zanesljivosti komponent in njihova uporaba
Space product assurance - Components reliability data sources and their use
Raumfahrtproduktsicherung - Datenquellen zur Bauteilezuverlässigkeit und ihre
Anwendung
Assurance produit des projets spatiaux - Sources de données de fiabilité composants et
leur utilisation
Ta slovenski standard je istoveten z: FprCEN/TR 17602-30-08
ICS:
03.120.99 Drugi standardi v zvezi s Other standards related to
kakovostjo quality
49.140 Vesoljski sistemi in operacije Space systems and
operations
kSIST-TP FprCEN/TR 17602-30-08:2021 en,fr,de
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
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kSIST-TP FprCEN/TR 17602-30-08:2021
TECHNICAL REPORT
FINAL DRAFT
FprCEN/TR 17602-30-08
RAPPORT TECHNIQUE
TECHNISCHER BERICHT
July 2021
ICS 49.140
English version
Space product assurance - Components reliability data
sources and their use
Assurance produit des projets spatiaux - Sources de Raumfahrtproduktsicherung - Datenquellen zur
données de fiabilité composants et leur utilisation Bauteilezuverlässigkeit und ihre Anwendung
This draft Technical Report is submitted to CEN members for Vote. It has been drawn up by the Technical Committee
CEN/CLC/JTC 5.
CEN and CENELEC members are the national standards bodies and national electrotechnical committees of Austria, Belgium,
Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy,
Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of North Macedonia, Romania, Serbia,
Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and United Kingdom.
Recipients of this draft are invited to submit, with their comments, notification of any relevant patent rights of which they are
aware and to provide supporting documentation.
Warning : This document is not a Technical Report. It is distributed for review and comments. It is subject to change without
notice and shall not be referred to as a Technical Report.
CEN-CENELEC Management Centre:
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reserved worldwide for CEN national Members and for
CENELEC Members.
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Table of contents
European Foreword . 4
1 Scope . 5
2 References . 6
3 Terms, definitions and abbreviated terms . 7
3.1 Terms from other documents . 7
3.2 Abbreviated terms. 7
4 Selection of reliability data and methods . 8
4.1 Introduction . 8
4.2 Selection process . 8
4.3 Description of data . 11
4.3.1 Handbook reliability data . 11
4.3.2 Manufacturer or user data . 11
4.4 Selection criteria for input sources . 11
4.4.1 Reliability handbooks . 11
4.4.2 Manufacturer or user data . 12
4.5 Justification for choice . 14
4.6 Instructions for use . 15
4.6.1 Reliability handbooks . 15
4.6.2 Manufacturer or user data . 15
4.7 Considerations for reliability prediction for mechanical parts . 16
4.7.1 General . 16
4.7.2 Part failure data analysis . 17
4.7.3 Empirical reliability relationships . 17
4.7.4 Analysis of the stress-strength . 17
4.7.5 Handbook data . 18
4.8 Documentation . 18
Annex A Potential data sources . 19
A.1 Introduction . 19
A.2 EEE parts . 19
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A.2.1 AT&T reliability manual . 19
A.2.2 FIDES (UTE C 80-811) . 19
A.2.3 HRD5 . 19
A.2.4 IEEE Gold Book . 20
A.2.5 IRPH . 20
A.2.6 MIL-HDBK-217 . 20
A.2.7 PRISM (RAC / EPRD) . 20
A.2.8 RDF 2000 (UTE C 80-810, IEC-62380-TR Edition 1) . 20
A.2.9 Siemens SN29500 . 21
A.2.10 Telcordia SR-332 . 21
A.3 Mechanical parts . 21
A.3.1 NPRD-95 . 21
A.3.2 NSWC-94/L07 - Handbook of Reliability Prediction Procedures for
Mechanical Equipment . 22
Annex B Applicability and limitations of MIL-HDBK-217F . 23
B.1 Introduction . 23
B.2 EEE families applicability matrix . 23
B.3 EEE packages applicability matrix (based on paragraph 5.6 MIL-HDBK-217) 26
B.4 EEE part equivalent quality grades . 26
Annex C Justification . 28
Bibliography . 30
Figures
Figure 4-1: Boundaries of ECSS-Q-HB-30-08 (inputs and outputs) . 8
Figure 4-2: Selection process . 9
Figure 4-3: Decision logic . 10
Figure 4-4: Selection of manufacturer or user data . 13
Tables
Table 4-1: Reliability handbook selection criteria . 12
Table 4-2: Percentiles of the χ² Distribution at 60 % and 90 % confidence for n<30 . 16
Table B-1 : EEE families applicability matrix for MIL-HDBK-217 . 24
Table B-2 : EEE package applicability . 26
Table B-3 : Designation of EEE part quality grades . 27
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European Foreword
This document (FprCEN/TR 17602-30-08:2021) has been prepared by Technical Committee
CEN/CLC/JTC 5 “Space”, the secretariat of which is held by DIN.
It is highlighted that this technical report does not contain any requirement but only collection of data
or descriptions and guidelines about how to organize and perform the work in support of EN 16602-30.
This Technical report (FprCEN/TR 17602-30-08:2021) originates from ECSS-Q-HB-30-08A.
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. CEN [and/or CENELEC] shall not be held responsible for identifying any or all such
patent rights.
This document has been prepared under a mandate given to CEN by the European Commission and
the European Free Trade Association.
This document has been developed to cover specifically space systems and has therefore precedence
over any TR covering the same scope but with a wider domain of applicability (e.g.: aerospace).
This document is currently submitted to the CEN CONSULTATION.
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1
Scope
This handbook identifies data sources and respective methods that can be used for reliability prediction
of components. It proposes suitable data sources and an application matrix for component families.
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2
References
EN Reference Reference in text Title
EN 16601-00-01 ECSS-S-ST-00-01 ECSS - Glossary of terms
EN 16602-30 ECSS-Q-ST-30 Space product assurance - Dependability
EN 16602-40 ECSS-Q-ST-40 Space product assurance - Safety
EN 16602-60 ECSS-Q-ST-60 Space product assurance - Electrical, electronic and
electromechanical (EEE) components
IEC 60050-191 International Electrotechnical Vocabulary - Chapter
191: Dependability and quality of service
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3
Terms, definitions and abbreviated terms
3.1 Terms from other documents
For the purpose of this document, the terms and definitions from ECSS-S-ST-00-01 and IEC 60050-191
apply.
3.2 Abbreviated terms
For the purpose of this document, the abbreviated terms from ECSS-S-ST-00-01 apply.
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4
Selection of reliability data and methods
4.1 Introduction
This handbook can be used whenever EEE and mechanical components reliability data or failure rates
are needed to perform quantitative dependability or safety analyses in accordance with ECSS-Q-ST-30
or ECSS-Q-ST-40.
The boundaries of this process are shown in Figure 4-1. Inputs are project requirements, handbook data
and manufacturer or user data. The selection process should consider selection criteria and methods of
use of data. Outputs are usually included in equipment reliability assessments. Selection is supported
by suitable justification.
Project
Requirements
Selection
Criteria
Equipment
Reliability
Assessment
Handbook
Methods for use of
Data and Selection Process
data
Methods
Justification
ECSS-Q-HB-30-08 Perimiter Outputs
Manufacturer/
User Data
Figure 4-1: Boundaries of ECSS-Q-HB-30-08 (inputs and outputs)
4.2 Selection process
The selection of a suitable methodology is made according to Figure 4-2. Where the customer requires
that a reliability prediction be computed according to a particular methodology, contractual
requirements are applicable.
The term “methodology” includes the process, data and equations as defined in a particular handbook
or prediction system.
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D o e s th e m e th o d o lo g y
D o e s c u s to m e r re q u ire a n y U s e th e re q u ire d
Y e s a d e q u a te ly a d d re s s th e Y e s
p a rtic u la r m e th o d o lo g y ? m e th o d o lo g y
c o m p o n e n t?
No
U s e th is d o c u m e n t to s e le c t
U s e th e s e le c te d
No b e tw e e n a p a rtic u la r h a n d b o o k o r
m e th o d o lo g y
m a n u fa c tu rin g d a ta
Figure 4-2: Selection process
In the case where there is no prescribed methodology, this handbook should be applied and a suitable
methodology should be selected.
In the case where the prescribed methodology does not adequately address the component under
consideration, this handbook should be applied and a suitable methodology should be selected.
In order to perform any reliability predictions, reliability data is needed as an input, and a suitable
methodology needs to be applied.
Figure 3 shows the decision logic that should be applied when selecting data sources. Data should be
obtained from the following sources, in order of preference:
Handbook data
Manufacturer or user data.
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S ta rt
C o lle c t d a ta o n
C o lle c t d a ta o n
a p p lic a tio n
c o m p o n e n ts u s e d
e n v iro n m e n t
U s e s c o rin g s y s te m
to e x a m in e
a p p lic a b ility o f
m e th o d o lo g y
Is th e re a n a p p lic a b le
Y e s U s e it
m e th o d o lo g y
No
U s e m a n u fa c tu re r /
U s e r d a ta
Figure 4-3: Decision logic
A description of data sources is given in clause 4.3.
The choice of a given data source is acceptable if it satisfies the criteria listed in clause 4.4. Data on the
handbook methodology, the components, environment and use should be collected. A suitable
methodology can be selected by using a weighted score ranking scheme, as described in clause 4.4.1.
The rationale for selection is justified according to clause 4.5.
A suitable methodology or instructions for use is described in clause 4.6.
If a handbook is determined to be not suitable for the component, then manufacturer or user data should
be used.
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4.3 Description of data
4.3.1 Handbook reliability data
There are a number of reliability handbooks available; these publish reliability metrics on a large
number of components. Some examples are provided in Annex A. Care should be taken with such data
since it is not always possible to ascertain the actual source of the data. The data can be a mix of field
and test data, and even interpolated or extrapolated data can be present.
4.3.2 Manufacturer or user data
4.3.2.1 Manufacturer data
Manufacturer’s data is that which is supplied by the manufacturer based on tests on a particular
component. Data is normally presented according to the methods laid out in IEC 60319.
4.3.2.2 User data
User data is that which is produced by the company performing the prediction for the sole purpose of
deriving reliability information about components that can be obtained in no other way. Data can be,
for instance, from in house testing, user experience, lessons learned, or expert judgement. This
procedure is most often used for unique component types.
4.4 Selection criteria for input sources
4.4.1 Reliability handbooks
Table 4-1 provides criteria to be considered for the selection of reliability handbooks. The criteria are
listed in order of importance. In order to provide an acceptable evaluation, each of the questions
mentioned should be addressed by the user.
The user should consider the use of a scoring scheme, which is shown in this table. In this example, if a
selection is made between handbooks, then that which has the higher score is considered acceptable. If
there is only one handbook, the scoring may be used to determine the adequacy of the handbook, by
defining a minimum acceptable score.
The scoring factors given in Table 4-1 are an example. A particular company may wish to change these
scoring factors depending upon their experience.
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Table 4-1: Reliability handbook selection criteria
Item Question Scoring factor
a.
Validity 1a) Is the considered technology covered by the GO / NO GO criteria
handbook?
1b) Is information available on the way in which the data 15 for yes
was collected?
0 for no
1c) If yes to 1a and 1b, are data collected and models 10 for yes
implemented according to an international standard
0 for no
or handbook (e.g. IEC)?
Suitability for 2a) Does the handbook cover the space environment? 10 for yes
space
0 for no
2b) Does the handbook consider the parts stress method? 10 for yes
0 for no
2c) Does the handbook address the quality levels of the 10 for yes
components being used?
0 for no
Maintenance of 3a) Has the handbook data been updated in the last 5 10 for yes
data years?
0 for no
3b) Are there any expectations to update the handbook 10 for yes
data in the next 5 years?
0 for no
International 4a) Is the handbook requested by the customer? 10 for yes
recognition
0 for no
4b) Is the handbook recognized by the reliability 5 for yes
community?
0 for no
Usability 5a) Is a commercial software tool available to support the 5 for yes
handbook?
0 for no
Suitability for 6a) Does the handbook provide extrapolation rules (e.g. 5 for yes
new technologies Moore’s law)?
0 for no
Cost Not considered -
a.
Technology includes the component type, technology, family and package
b.
Space environment includes launch vibrations, space vacuum, radiation, and temperature extremes.
c.
In space applications, the component quality is in accordance with ECSS-ST-Q-60, its equivalent, or as
otherwise specified.
d.
Recognition by the reliability community can include, for example:
- It is an international standard or handbook;
- It is a national standard or handbook (e.g. MIL-HDBK-217);
- It is a recognized industrial or other standard or handbook (e.g. Telcordia SR-332);
- It is otherwise recognized by the reliability community.
4.4.2 Manufacturer or user data
Use of manufacturer or user data is considered if data from a reliability handbook is not suitable. Figure
4-4 depicts the selection of manufacturer or user data.
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S e le c t D a ta
S o u rc e
Is M a n u fa c tu re r d a ta a v a ila b le ? No Is u s e r d a ta a v a ila b le ?
Y e s
Y e s
Is d a ta c o lle c te d a s p e r IE C
Is d a ta p re s e n te d a s p e r IE C
60300 -3 -2 a n d a n a ly s e d a s p e r
60319 No
IE C 60300 -3 -5
No
Y e s Y e s
P e rfo rm v e ry d e ta ile d c h e c k o f
C h e c k d a ta p ro v e n a n c e C h e c k d a ta p ro v e n a n c e
d a ta p ro v e n a n c e
Q u a lity re v ie w Q u a lity re v ie w
T e c h n ic a l re v ie w
D a ta s u ita b le fo r u s e ? No P e rfo rm R is k A s s e s s m e n t
Y e s
U s e D a ta G e n e ra te re lia b ility d a ta
Figure 4-4: Selection of manufacturer or user data
The steps for selection are as follows:
1. Select the data source.
2. If manufacturer data is available, check whether data is presented in accordance with IEC
60319, in which case it can be considered for use.
If the data is not presented in accordance with IEC 60319, then a detailed review of the data
should be performed to ensure the following is available:
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o tests and test conditions applied to the components;
o lot sampling;
o number of lots;
o manufacturing and testing period;
o technological representativity;
o failure analysis.
Once this data is available, assess the effect of any missing data with respect to the expected
list above.
3. If user data is available, check whether data is collected and presented in accordance with
IEC 60300-3-2 and IEC 60300-3-5, in which case it can be considered for use.
If data is not presented in accordance with these standards, then a detailed review of data
should be made, to ensure the following is available:
For field return data the following should be reviewed:
o data collection procedures;
o relevance of failures;
o analysis techniques.
For test data the following should be reviewed:
o tests and test conditions applied to the components;
o lot sampling;
o number of lots;
o manufacturing and testing period;
o technological representativity;
o failure analysis.
Once this data is available, assess the effect of any missing data with respect to the expected
list above.
4. Once these checks have been performed, the analyst can decide on the use of the data.
5. In case suitability is not determined, the above steps are repeated to find an alternative.
6. In case a data source cannot be found, a risk assessment should be performed to determine
the necessity for obtaining further data, e.g. via a reliability test programme, whether to
use expert judgement or whether to accept the fact that data is not available for the
particular component under consideration.
4.5 Justification for choice
In order to ensure that any work performed is technically correct, justification for the choices made
should be presented whilst the work is performed. This allows the argument made for the methodology
followed to be understood at some later time. The justification should be included with the reliability
assessment report (see clause 4.7) and may be used as part of any reliability case argued. Annex C
provides more details of the justification.
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4.6 Instructions for use
4.6.1 Reliability handbooks
The reliability models and methods that are described within the selected reliability handbook should
be used. Modifications to the models or methods should be supported with the rationale in accordance
with clause 4.4.
4.6.2 Manufacturer or user data
The selected manufacturer or user data should be used in accordance with IEC 60300-3-5. Test or
manufacturing data that conforms to this criterion is suitable for failure rate calculation. The failure rate
calculation procedure is described hereafter.
The necessary inputs for failure rate calculation are:
number and nature of defects, and
device hours (test duration and number of devices).
The number of devices should be derived using lot sampling procedures in accordance with a
recognized sampling plan such as ISO 2859-0.
The failure rate can be assessed using the χ² (Chi-square) distribution for time truncated and failure
truncated tests.
Given the total number of successful part operating hours (T) and the number of failures (f), the
following equations are used to calculate failure rate (λ) from test data:
2 9
10
n
For a time truncated test, where n = 2f + 2:
2T
2 9
10
n
For a failure truncated test, where n = 2f:
2T
where
λ = is the failure rate in 10-9/hour (FIT) at test conditions;
χ² = is the percentile of the χ² distribution at confidence level (failure rates are provided at 60 %
confidence in the commonly used handbooks listed and described in Annex A);
n = is the degree of freedom of the statistics.
The failure rate can be extrapolated to the operating condition by applying the acceleration factor
between test conditions and operating conditions. Information on acceleration factors can be found in
IEC1709 or IEC 721-3-3
Percentiles of the χ² distribution at 60 % and 90% confidence level are given in Table 4-2 for up to 30
degrees of freedom.
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Table 4-2: Percentiles of the χ² Distribution at 60 % and 90 %
confidence for n<30
n ² (60%) ² (90%)
2 1,83 4,61
4 4,04 7,78
6 6,21 10,6
8 8,35 13,4
10 10,5 16,0
12 12,6 18,5
14 14,7 21,1
16 16,8 23,5
18 18,9 26,0
20 21,0 28,4
22 23,0 30,8
24 25,1 33,2
26 27,2 35,6
28 29,2 37,9
30 32,3 40,3
Percentiles of the χ² distribution can be found in various literature.
NOTE The calculated failure rate for a given failure mechanism is highly
influenced by test conditions and the physics of failure. Whatever
the failure mechanism, an acceleration limitation applies. Highly
accelerated tests can induce failure mechanisms that are not
observed in the actual application. This leads to an overestimation
of failure rates. This acceleration limitation applies to all
acceleration factors (e.g. temperature, voltage, and current).
4.7 Considerations for reliability prediction for
mechanical parts
4.7.1 General
For mechanical reliability prediction, four approaches are available:
part failure data analysis,
empirical reliability relationships,
stress-strength, and
handbook data.
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There are a number of problems that are encountered when performing mechanical predictions and
these are summarized below.
Part failure analysis
Data often not available
Available data is often grouped (individual times to failure are not available)
For a completely new design, expensive testing may be required.
Empirical reliability techniques
Models available for limited number of part types
New process/material not previously assessed
Models are often for life and not hazard rate.
Stress or strength interference analysis
Results are probability of failure not hazard rate
Interference often at extremes of distribution tails
Standard deviation for stress is difficult to get.
Handbook data
Constant failure rates are assumed
Failure rates are not application sensitive
Design improvements doubtful.
4.7.2 Part failure data analysis
Statistical data analysis is the preferred approach to prediction when accurate failure data exist as part
of a manufacturer’s historical database. This data can also exist as a result of a dedicated reliability test
programme. When such data does exist, the underlying time to failure distribution should be identified
using statistical techniques such as the Weibull analysis. In every case a detailed analysis of failed parts
and their data should be performed to identify trends and failure mechanisms.
4.7.3 Empirical reliability relationships
Empirical reliability relationships are based on extensive testing for different combinations of, for
instance, loading, materials, and dimensions. The tools required to use these models include some
measures of part life and the ability to determine Weibull characteristic life.
4.7.4 Analysis of the stress-strength
An analysis of the stress-strength relationship involves characterization of statistical distributions for
stresses acting on a mechanical part and material strength. The most positive benefit is the
understanding that stress and strength are subject to variability, and if an incorrect underlying
distribution is selected or variability is not accurately characterized, estimated probability of failure can
be significantly in error. In order to perform a stress-strength analysis, the stress distribution and
strength distribution should be determined using best engineering practices.
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If stress is greater than strength, failure occurs. This failure generally occurs in the area under the
intersection of the strength and stress distribution. Hence it is important to understand the shape and
location of these distributions.
More information on stress-strength analysis can be found in IEC 60300-3-1.
4.7.5 Handbook data
Handbook data exists for mechanical parts and contain generic failure rate data, for example the RAC
publication NPRD. Care should be taken since the data can be quoted in, for instance, Failures/h,
Failures/Cycle, or Failures/Mile and should not be directly compared with data available on other
component types.
4.8 Documen
...
Questions, Comments and Discussion
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