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A practical, step-by-step guide to designing world-class, high availability systems using both classical and DFSS reliability techniques
Whether designing telecom, aerospace, automotive, medical, financial, or public safety systems, every engineer aims for the utmost reliability and availability in the systems he, or she, designs. But between the dream of world-class performance and reality falls the shadow of complexities that can bedevil even the most rigorous design process. While there are an array of robust predictive engineering tools, there has been no single-source guide to understanding and using them . . . until now.
Offering a case-based approach to designing, predicting, and deploying world-class high-availability systems from the ground up, this book brings together the best classical and DFSS reliability techniques. Although it focuses on technical aspects, this guide considers the business and market constraints that require that systems be designed right the first time.
Written in plain English and following a step-by-step "cookbook" format, Designing High Availability Systems:
* Shows how to integrate an array of design/analysis tools, including Six Sigma, Failure Analysis, and Reliability Analysis
* Features many real-life examples and case studies describing predictive design methods, tradeoffs, risk priorities, "what-if" scenarios, and more
* Delivers numerous high-impact takeaways that you can apply to your current projects immediately
* Provides access to MATLAB programs for simulating problem sets presented, along with PowerPoint slides to assist in outlining the problem-solving process
Designing High Availability Systems is an indispensable working resource for system engineers, software/hardware architects, and project teams working in all industries.
Sommario
Preface xiii
List of Abbreviations xvii
1. Introduction 1
2. Initial Considerations for Reliability Design 3
2.1 The Challenge 3
2.2 Initial Data Collection 3
2.3 Where Do We Get MTBF Information? 5
2.4 MTTR and Identifying Failures 6
2.5 Summary 7
3. A Game of Dice: An Introduction to Probability 8
3.1 Introduction 8
3.2 A Game of Dice 10
3.3 Mutually Exclusive and Independent Events 10
3.4 Dice Paradox Problem and Conditional Probability 15
3.5 Flip a Coin 21
3.6 Dice Paradox Revisited 23
3.7 Probabilities for Multiple Dice Throws 24
3.8 Conditional Probability Revisited 27
3.9 Summary 29
4. Discrete Random Variables 30
4.1 Introduction 30
4.2 Random Variables 31
4.3 Discrete Probability Distributions 33
4.4 Bernoulli Distribution 34
4.5 Geometric Distribution 35
4.6 Binomial Coeffi cients 38
4.7 Binomial Distribution 40
4.8 Poisson Distribution 43
4.9 Negative Binomial Random Variable 48
4.10 Summary 50
5. Continuous Random Variables 51
5.1 Introduction 51
5.2 Uniform Random Variables 52
5.3 Exponential Random Variables 53
5.4 Weibull Random Variables 54
5.5 Gamma Random Variables 55
5.6 Chi-Square Random Variables 59
5.7 Normal Random Variables 59
5.8 Relationship between Random Variables 60
5.9 Summary 61
6. Random Processes 62
6.1 Introduction 62
6.2 Markov Process 63
6.3 Poisson Process 63
6.4 Deriving the Poisson Distribution 64
6.5 Poisson Interarrival Times 69
6.6 Summary 71
7. Modeling and Reliability Basics 72
7.1 Introduction 72
7.2 Modeling 75
7.3 Failure Probability and Failure Density 77
7.4 Unreliability, F(t) 78
7.5 Reliability, R(t) 79
7.6 MTTF 79
7.7 MTBF 79
7.8 Repairable System 80
7.9 Nonrepairable System 80
7.10 MTTR 80
7.11 Failure Rate 81
7.12 Maintainability 81
7.13 Operability 81
7.14 Availability 82
7.15 Unavailability 84
7.16 Five 9s Availability 85
7.17 Downtime 85
7.18 Constant Failure Rate Model 85
7.19 Conditional Failure Rate 88
7.20 Bayes's Theorem 94
7.21 Reliability Block Diagrams 98
7.22 Summary 107
8. Discrete-Time Markov Analysis 110
8.1 Introduction 110
8.2 Markov Process Defined 112
8.3 Dynamic Modeling 116
8.4 Discrete Time Markov Chains 116
8.5 Absorbing Markov Chains 123
8.6 Nonrepairable Reliability Models 129
8.7 Summary 140
9. Continuous-Time Markov Systems 141
9.1 Introduction 141
9.2 Continuous-Time Markov Processes 141
9.3 Two-State Derivation 143
9.4 Steps to Create a Markov Reliability Model 147
9.5 Asymptotic Behavior (Steady-State Behavior) 148
9.6 Limitations of Markov Modeling 154
9.7 Markov Reward Models 154
9.8 Summary 155
10. Markov Analysis: Nonrepairable Systems 156
10.1 Introduction 156
10.2 One Component, No Repair 156
10.3 Nonrepairable Systems: Parallel System with No Repair 165
10.4 Series System with No Repair: Two Identical Components 172
10.5 Parallel System with Partial Repair: Identi
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A wizard with words and a man of the bush. Aaron is a 25-year-old father of two and a beloved husband. He has spent five years assisting the bush to regenerate in the South Coast of New South Wales, and spent far too much of that time daydreaming and fantasizing. The Wizard and the Birdsong is the first fruit of his laborious fantasizing, and a gift he hopes will be read by families all over the world to help honour old ways of community-mindedness and caring for our loved ones.
Riassunto
A practical, step-by-step guide to designing world-class, high availability systems using both classical and DFSS reliability techniques Whether designing telecom, aerospace, automotive, medical, financial, or public safety systems, every engineer aims for the utmost reliability and availability in the systems he, or she, designs.
