Machine Learning for Survival Analysis: A Survey <s> Reliability <s> Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository. <s> BIB001 </s> Machine Learning for Survival Analysis: A Survey <s> Reliability <s> Chapter 1 Reliability Engineering in Perspective 1.1 Why Study Reliability? 1.2 Failure Models 1.3 Failure Mechanisms 1.4 Performance Measures 1.5 Formal Definition of Reliability 1.6 Definition of Availability 1.7 Definition of Risk Chapter 2 Basic Reliability Mathematics: Review of Probability and Statistics 2.1 Introduction 2.2 Elements of Probability 2.3 Probability Distributions 2.4 Basic Characteristics of Random Variables 2.5 Estimation and Hypothesis Testing 2.6 Frequency Tables and Histograms 2.7 Goodness-of-Fit Tests 2.8 Regression Analysis Chapter 3 Elements of Component Reliability 3.1 Concept of Reliability 3.2 Common Distributions in Component Reliability 3.3 Component Reliability Model Selection 3.4 Maximum Likelihood Estimation of Reliability Distribution Parameters 3.5 Classical Nonparametric Distribution Estimation 3.6 Bayesian Estimation Procedures 3.7 Methods of Generic Failure Rate Determination Chapter 4 System Reliability Analysis 4.1 Reliability Block Diagram Method 4.2 Fault Tree and Success Tree Methods 4.3 Event Tree Method 4.4 Master Logic Diagram 4.5 Failure Mode and Effect Analysis Chapter 5 Reliability and Availability of Repairable Components and Systems 5.1 Repairable System Reliability 5.2 Availability of Repairable Systems 5.3 Use of Markov Processes for Determining System Availability 5.4 Use of System Analysis Techniques in the Availability Calculations of Complex Systems Chapter 6 Selected Topics in Reliability Modeling 6.1 Probabilistic Physics-of-Failure Reliability Modeling 6.2 Software Reliability Analysis 6.3 Human Reliability 6.4 Measures of Importance 6.5 Reliability-Centered Maintenance 6.6 Reliability Growth Chapter 7 Selected Topics in Reliability Data Analysis 7.1 Accelerated Life Testing 7.2 Analysis of Dependent Failures 7.3 Uncertainty Analysis 7.4 Use of Expert Opinion for Estimating Reliability Parameters 7.5 Probabilistic Failure Analysis Chapter 8 Risk Analysis 8.1 Determination of Risk Values8.2 Formalization of Quantitative Risk Assessment 8.3 Probabilistic Risk Assessment 8.4 Compressed Natural Gas Powered Buses: A PRA Case Study 8.5 A Simple Fire Protection Risk Analysis 8.6 Precursor Analysis Appendices Index <s> BIB002
In the field of reliability, it is common to collect data over a period of time and record the interesting events that occur within this period. Reliability prediction focuses on developing methods which are good at accurately estimating the reliability of new products BIB002 BIB001 . The event of interest here corresponds to the time taken for a device to fail. In such applications, it is desirable to be able to estimate which devices will fail and, if they do, when they will fail. Survival analysis methods can help to build such prediction models using the information available for these devices. These models can provide early warnings about potential failures, which is significantly important to either prevent or reduce the likelihood of failures and to identify and correct the causes of device failures.