<p>Foreword xi<br /><i>Philippe EUDELINE</i></p> <p>Preface xiii<br /><i>Abdelkhalak EL HAMI, David DELAUX and Henri GRZESKOWIAK</i></p> <p><b>Chapter 1 FIDES, a Method for Assessing and Building the Reliability of Electronic Systems 1</b><br /><i>Franck DAVENEL</i></p> <p>1.1 The inadequacy of existing methods 2</p> <p>1.1.1 MIL-HDBK-217F 2</p> <p>1.1.2 UTE-C-80810 (or RDF2000, or IEC 62380 TR Ed.1) 2</p> <p>1.1.3 PRISM or 217plus 2</p> <p>1.2 The ambition of FIDES 3</p> <p>1.3 General presentation of the FIDES method 5</p> <p>1.3.1 Failure rate 6</p> <p>1.3.2 The structure of FIDES models 7</p> <p>1.3.3 Physical models 8</p> <p>1.3.4 The exploitation of manufacturer data 8</p> <p>1.3.5 Exploiting databases of failure mechanisms (not failure rates) 9</p> <p>1.3.6 Life profile 10</p> <p>1.3.7 Other contributors 11</p> <p>1.3.8 Sensitivity of FIDES models 13</p> <p>1.3.9 Industrial applications 14</p> <p>1.4 Validity of reliability studies with FIDES 14</p> <p>1.5 Conclusion 16</p> <p>1.6 References 18</p> <p><b>Chapter 2 Reliability in Maritime Transport: Choosing a Container Handling System 19</b><br /><i>Julien RULLIER, Benjamin ECHARD and Ghislaine DELAPAYRE</i></p> <p>2.1 Introduction 19</p> <p>2.2 Proposed case study 20</p> <p>2.3 Inputs of the RAMS approach 22</p> <p>2.3.1 Presentation of the system 22</p> <p>2.3.2 Component reliability data 25</p> <p>2.3.3 Reliability of carabiners over time 25</p> <p>2.4 Assessment of the system’s RAMS 31</p> <p>2.4.1 Reliability assessment 31</p> <p>2.4.2 Assessment of the intrinsic availability 32</p> <p>2.4.3 Maintainability assessment 33</p> <p>2.4.4 Safety assessment 33</p> <p>2.5 Conclusion 55</p> <p>2.5.1 FMECA or fault trees, how to choose? 55</p> <p>2.5.2 Pitfalls to avoid 57</p> <p>2.5.3 Note on low reliability targets in innovative systems 59</p> <p>2.6 General conclusion 59</p> <p>2.7 References 60</p> <p><b>Chapter 3 Generation of a Failure Model through Probabilistic "Stress--Strength" Interaction in a Context of Poor Information 61</b><br /><i>Lambert PIERRAT</i></p> <p>3.1 Introduction 61</p> <p>3.2 Aims and objectives 62</p> <p>3.3 Choosing types of legislation 63</p> <p>3.3.1 Principle of maximum entropy 63</p> <p>3.3.2 The strength distribution 64</p> <p>3.3.3 The law of constraint 65</p> <p>3.3.4 Relationship between the two laws 66</p> <p>3.4 Probability of failure 67</p> <p>3.4.1 Formulation 67</p> <p>3.4.2 Analytical solution 68</p> <p>3.4.3 Parametric expression 69</p> <p>3.5 Safety factor 69</p> <p>3.5.1 Simplified expressions 70</p> <p>3.5.2 Validity limits 70</p> <p>3.6 Validation and applications 72</p> <p>3.6.1 Comparative analyses 72</p> <p>3.6.2 Applications 75</p> <p>3.7 Conclusion and extensions 79</p> <p>3.8 References 79</p> <p><b>Chapter 4 Reliable Optimization of Dental Implants Using the Generalized Polynomial Chaos Method 83</b><br /><i>Fatma ABID, Abdelkhalak EL HAMI, Tarek MERZOUKI, Hassen TRABELSI, Lassaad WALHA and Mohamed HADDAR</i></p> <p>4.1 Introduction 83</p> <p>4.2 Stochastic approach 84</p> <p>4.2.1 The MC method 84</p> <p>4.2.2 The GPC method 85</p> <p>4.3 Deterministic design optimization 86</p> <p>4.4 Reliability-based design optimization 87</p> <p>4.4.1 The classic method 88</p> <p>4.4.2 OSF using GPC 89</p> <p>4.5 Numerical result 91</p> <p>4.5.1 2D dental implant 91</p> <p>4.6 Conclusion 96</p> <p>4.7 References 96</p> <p><b>Chapter 5 Multi-objective Reliability Optimization Based on Substitution Models Applied Case Study of a Hip Prosthesis 101</b><br /><i>Khalil DAMMAK and Abdelkhalak EL HAMI</i></p> <p>5.1 Introduction 101</p> <p>5.2 Description of metamodeling methods 103</p> <p>5.2.1 Application of a substitution model 103</p> <p>5.2.2 Construction of a metamodel 104</p> <p>5.2.3 Validation of metamodels 110</p> <p>5.3 Optimization of multi-objective design 111</p> <p>5.3.1 Deterministic MOO 111</p> <p>5.3.2 Reliability-based multi-objective design optimization 113</p> <p>5.4 RBMDO based on hip prosthesis surrogate models 114</p> <p>5.4.1 Deterministic simulation using the finite element method 114</p> <p>5.4.2 Construction of substitution models 116</p> <p>5.4.3 Optimization of multi-objective design based on reliability 118</p> <p>5.5 Conclusion 121</p> <p>5.6 References 122</p> <p><b>Chapter 6 CMA-ES Assisted by the Kriging Metamodel for the Optimization of Thermomechanical Performances of Mechatronic Packaging 129</b><br /><i>Hamid HAMDANI, Bouchaib RADI and Abdelkhalak EL HAMI</i></p> <p>6.1 Introduction 130</p> <p>6.2 Presentation of the system under study 131</p> <p>6.2.1 The case of wire bonding 133</p> <p>6.2.2 The case of solder joints 133</p> <p>6.3 Thermal fatigue models of solder joints 135</p> <p>6.3.1 The Coffin--Manson model 136</p> <p>6.3.2 The Morrow model 137</p> <p>6.3.3 The Coffin--Manson frequency-modified model 138</p> <p>6.3.4 The Morrow frequency-modified model 138</p> <p>6.3.5 The Darveaux model 138</p> <p>6.4 Modeling and finite element analysis of the PQFP housing 139</p> <p>6.4.1 Modeling 139</p> <p>6.4.2 Material properties 141</p> <p>6.4.3 Thermal load 142</p> <p>6.4.4 Fatigue model selected for solder joints 143</p> <p>6.4.5 Numerical results 144</p> <p>6.5 Evolutionary strategies 145</p> <p>6.5.1 Presentation of evolutionary strategies 145</p> <p>6.5.2 Principles of ESs 146</p> <p>6.5.3 Covariance matrix adaptation evolution strategy 146</p> <p>6.5.4 Metamodeling techniques 151</p> <p>6.5.5 Kriging-assisted CMA-ES 154</p> <p>6.6 Global optimization of the PQFP housing solder joints 158</p> <p>6.6.1 Formulation of the problem 158</p> <p>6.6.2 Numerical simulations 160</p> <p>6.7 Conclusion 162</p> <p>6.8 References 164</p> <p><b>Chapter 7 Reliable Optimization of Vibro-acoustic Problems in the Presence of Uncertainties via Polynomial Chaos 171</b><br /><i>Khalil DAMMAK and Abdelkhalak EL HAMI</i></p> <p>7.1 Introduction 171</p> <p>7.2 Robust approaches to uncertainty propagation 172</p> <p>7.2.1 The Monte Carlo method 172</p> <p>7.2.2 Generalized polynomial chaos 174</p> <p>7.3 Structural optimization 180</p> <p>7.3.1 Formulation of the optimization problem 180</p> <p>7.3.2 Deterministic design optimization 181</p> <p>7.3.3 Reliability design optimization 182</p> <p>7.4 OSF method coupled with GPC applied to vibro-acoustic systems in the presence of uncertainties 187</p> <p>7.4.1 Deterministic model 191</p> <p>7.4.2 Probabilistic analysis 193</p> <p>7.4.3 OSF method coupled with GPC 194</p> <p>7.5 Conclusion 197</p> <p>7.6 References 197</p> <p>List of Authors 205</p> <p>Index 207</p> <p>Summaries of other volumes 211</p>