Product Maturity, Volume 2 E-Book

Franck Bayle

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 129

Veröffentlichungsjahr: 2022

Beschreibung

Every parent is concerned when a child is slow to become a mature adult. This is also true for any product designer, regardless of their industry sector. For a product to be mature, it must have an expected level of reliability from the moment it is put into service, and must maintain this level throughout its industrial use. While there have been theoretical and practical advances in reliability from the 1960s to the end of the 1990s, to take into account the effect of maintenance, the maturity of a product is often only partially addressed. Product Maturity 2 fills this gap as much as possible; a difficult exercise given that maturity is a transverse activity in the engineering sciences; it must be present throughout the lifecycle of a product.

Leseprobe

Table of Contents

Cover

Title Page

Copyright

Foreword by Laurent Denis

Foreword by Serge Zaninotti

Acknowledgements

Introduction

1 Sampling in Manufacturing

1.1. Cost aspects

1.2. Considering the distribution of defects

1.3. Considering the test coverage

2 Compliance Test

3 Non-Regression Tests

3.1. Non-regression on a physical quantity

3.2. Non-regression depending on time

4 Zero-Failure Reliability Demonstration

4.1. Purpose of zero-failure tests

4.2. Theoretical principle

4.3. Optimization of test costs

4.4. Specific cases

5 Reliability Management

5.1. Context

5.2. Physical architecture division

5.3. Classification of subsets

5.4. Allocation of initial reliability

5.5. Estimation of the reliability of subsets

5.6. Optimal allocation of the reliability of subsets

5.7. Illustration

5.8. Definition of design rules

5.9. Construction of a global predicted reliability model with several manufacturers

6 Confirmation of Maturity

6.1. Internal data from equipment manufacturer

6.2. System manufacturer data

6.3. End-customer data

6.4. Burn-in optimization

List of Notations

List of Definitions

List of Acronyms

References

Index

End User License Agreement

List of Illustrations

Chapter 1

Figure 1.1. Evolution of the total average cost depending on the size of the sam...

Figure 1.2. Evolution of the total average cost depending on the size of the sam...

Figure 1.3. Evolution of the total average cost depending on the size of the sam...

Figure 1.4. Evolution of the total average cost depending on the sample size – E...

Figure 1.5. Evolution of the total average cost depending on the sample size – E...

Figure 1.6. Evolution of the total average cost depending on the sample size – E...

Figure 1.7. Illustration

Chapter 2

Figure 2.1. Overview diagram of the non-compliance test

Figure 2.2. Test of normality

Chapter 3

Figure 3.1. Overview diagram of non-regression on a physical quantity

Figure 3.2. Test of normality on variable 1

Figure 3.3. Test of normality on variable 2

Figure 3.4. Diagram of a non-regression test

Figure 3.5. Example of a non-regression test

Chapter 4

Figure 4.1. Example of demonstration of reliability of non-maintained products

Figure 4.2. Testing time depending on the number of parts of non-maintained prod...

Figure 4.3. Example of reliability demonstration for maintained products

Figure 4.4. Testing time depending on the number of parts of maintained products

Figure 4.5. Weibull plot for the welding strength during thermal cycling

Figure 4.6. Weibull plot of electrolytic capacitors

Figure 4.7. Example of optimum cost for tests of non-maintained products

Figure 4.8. Example of optimum cost of testing maintained products

Figure 4.9. Survival function for the two tests

Figure 4.10. Example of MTBF demonstrated with two tests

Figure 4.11. Demonstrated reliability under various conditions

Figure 4.12. Reliability demonstrated under various conditions

Figure 4.13. Principle of testing the same parts under different conditions

Figure 4.14. Temperature profile under different conditions

Figure 4.15. Objective failure rate

Chapter 5

Figure 5.1. Overview diagram of product reliability management

Figure 5.2. Principle of product division into subsets (S/S)

Figure 5.3. Example of how the proper manufacturing of coins can be verified

Figure 5.4. Credibility curve example 5.1

Figure 5.5. Credibility curve example 5.2

Figure 5.6. Credibility curve example 5.3

Figure 5.7. Illustration of reliability management

Figure 5.8. Initial reliability allocation of the subsets in case of reliability...

Figure 5.9. Initial reliability allocation of the subsets in case of MTBF object...

Figure 5.10. Reliability allocation of the subsets in case of reliability object...

Figure 5.11. Reliability allocation of the subsets in case of MTBF objective aft...

Figure 5.12. Weibull plot voltage reference reliability test

Figure 5.13. 3D Weibull plot voltage reference reliability test

Figure 5.14. Final reliability allocation of the subsets in case of reliability ...

Figure 5.15. Final reliability allocation of the subsets in case of MTBF objecti...

Figure 5.16. Establishment of design rules

Figure 5.17. Example of global failure rates for manufacturers of components

Figure 5.18. Global weighted failure rate of manufacturers

Chapter 6

Figure 6.1. Test cone example

Figure 6.2. Global test cone

Figure 6.3. Example of removal rate over a three-year delivery period

Figure 6.4. Removal rate over a sliding period of six months

Figure 6.5. Example of removal rate with various sizes of sliding window

Figure 6.6. Overview diagram of how feedback data can be used

Figure 6.7. Root cause-based estimation of burn-in effectiveness

Figure 6.8. Product maturity depending on parameter β

Figure 6.9. Example of product maturity

Figure 6.10. Example of product non-maturity

Figure 6.11. Illustration of the component alert principle

Figure 6.12. Example of the product that does not have the expected reliability ...

Figure 6.13. Example of mature product

Figure 6.14. Example of failure distribution over four HASS cycles

Figure 6.15. Example of failure distribution over four HASS cycles after optimiz...

Figure 6.16. Example of evolution of the number of failures

List of Tables

Chapter 2

Table 2.1. Example of data for a non-compliance test

Chapter 3

Table 3.1. Example of a non-regression test

Chapter 4

Table 4.1. Values of parameter β for mechanical components

Table 4.2. Physical laws of failure

Table 4.3. Activation energy according to the FIDES guide

Table 4.4. Activation energies according to the JEDEC JEP122 standard

Table 4.5. Activation energy

Table 4.6. Activation energy according to EDR (2000)

Table 4.7. Activation energy for TOSHIBA semiconductors

Table 4.8. Coffin–Manson coefficient according to (Livingston 2000)

Table 4.9. Tests conducted on a quartz crystal according to the Automotive Elect...

Table 4.10. Example of life profile with negligible thermal constant

Chapter 5

Table 5.1. Classification of subsets

Table 5.2. Reliability estimation methods for the subsets

Table 5.3. Parameters of mission profile example

Table 5.4. Results of the accelerated tests of reliability

Table 5.5. Value of C and Ea parameters for different manufacturers

Table 5.6. Values of C and Ea parameters for different manufacturers and associa...

Chapter 6

Table 6.1. Examples of various cases of Weibull law combinations

Table 6.2. Boundaries of β parameter of a PLP model

Table 6.3. Boundaries of parameter β of a PLP model

Table 6.4. Delivery flow and number of observed failures

Table 6.5. Delivery flow and number of observed failures

Table 6.6. Scoreboard of burn-in effectiveness

Table 6.7. Example of evolution of the number of failures

Guide

Cover

Table of Contents

Title Page

Copyright

Foreword by Laurent Denis

Foreword by Serge Zaninotti

Acknowledgements

Introduction

Begin Reading

List of Notations

List of Definitions

List of Acronyms

References

Index

Other titles from iSTE in Mechanical Engineering and Solid Mechanics

End User License Agreement

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Reliability of Multiphysical Systems Set

coordinated by

Abdelkhalak El Hami

Volume 13

Product Maturity 2

Principles and Illustrations

Franck Bayle

First published 2022 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd

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UK

www.iste.co.uk

John Wiley & Sons, Inc.

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USA

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© ISTE Ltd 2022

The rights of Franck Bayle to be identified as the author of this work have been asserted by him in accordance with the Copyright, Designs and Patents Act 1988.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.

Library of Congress Control Number: 2021952701

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN 978-1-78630-740-8

Foreword by Laurent Denis

Human beings are plagued by major worries, such as fear of death and fear of illness. “How long will I live?” is a question that arises even in childhood. “Will I one day have to deal with a condition similar to my neighbor’s?”. We live in an age where disease, death, old age and disability are subjects to be avoided in polite conversation. “How are you?” is a standard greeting to which a different and darker reply than the traditional, “I’m very well, thank you, and you?” risks embarrassing or even annoying the other party. Avoiding the problems of others, for fear they may be contagious, gives us a sense of immortality on a daily basis.

This is a rather recent phenomenon, as many previous generations did not hide the elderly or sick, although the risk of accidents in everyday life was higher and so death was a more common occurrence. It was certainly a source of anxiety, but the Church was there to alleviate it. Today we hide this subject by paying attention to a society made up of young, healthy people whom we must emulate at all costs so as to be part of it. Since our days are more or less the same, we succumb to procrastination at the first opportunity and Seneca’s carpe diem loses its wonderful charm to give way to flat Platonic reflection.

Surprisingly, a similar problem exists in industry: there is a willingness to forget that a product may be subject to failure during its lifetime, given it has been optimally designed for the required functions. Some simple principles of upstream reliability analysis, from the design phase onwards, are now well-established, but they thwart the deep-seated notion that proper design outweighs everything else. Two essential points are overlooked: when a technology naturally reaches maturity, only a technological breakthrough can mark a distinction between two products performing the same function, unless it can be demonstrated that product A will last longer and be safer than product B. Moreover, the uses of the same product can multiply according to its ability to adapt to multiple environments. A good understanding of these uses in the field makes it possible to improve robustness properly at the design stage, in order that it can withstand any mission profile assigned to it during operation; this is one way to increase competitiveness.

Many companies still see the reliability study of a system before it becomes operational as a mandatory step to be overcome, bypassing or minimizing it as soon as possible. In the design phase, a signed product FMECA will end up in a folder, its purpose merely to certify that the rules have been followed correctly. The objective of the test phase is to confirm that the device being tested meets the requirements of a standard, without taking the opportunity to validate that the mission profiles on the ground will not unpredictably damage the product. During production, process control cards are used to verify that tolerance limits are not exceeded, without establishing forecasting instances that could lead to accidental stops. Hence, only data in the form of returned products, found to be defective by the end user, are subjected to a posteriori analyses by customer support. This can incur various costs and may lead to product recall if a serious defect is found.

Fortunately, however, the reality tends to be a little less bleak than the situation described above, with the emergence and dissemination of best practices that are based on theories validated by various industry sectors. These are now adapting to the challenges that companies face: making increasingly complex products that are more adaptable and ever-faster, while maintaining quality standards and reducing costs. This no longer involves applying deterministic models in which a single value is assigned to an objective to be reached. Instead, it is about drawing up a range of possible solutions that allow the supplier or integrator to make sure that the worst case a product might be subjected to on the ground can still be controlled by statistical modeling. The best way to achieve this is through the combined use of theoretical and technical resources: an in-depth understanding of the possible technological problems and solutions given by the manufacturer allows the qualified reliability engineer to build the most suitable predictive models. Ideally, a single person would have these two complementary sets of skills.