Yan-Fu Li – författare

This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively.

The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization.

The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively.The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization.The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively.

The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization.

The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

Enhancing Life Cycle Reliability with Robust Engineering and Predictive Health Management Complete process for ensuring product performance through robust concept design, robust optimization, selection, and verification in an uncontrollable user environment Enhancing Life Cycle Reliability with Robust Engineering and Predictive Health Management enables readers to build a robustness-thinking-based approach for robust design for reliability and prognostic health management (PHM), explaining best practices from early product design through the entire product lifecycle, leading to lower costs and shorter development cycles. The text integrates key tools and emerging reliability management systems into a comprehensive program for developing more robust and reliable technology-based products. The text provides value-added strategies for robustness development in new products and health management with three main types of robustness development and reliability growth case studies: intrinsic, instrumental, and collective. Readers can harness multiple forms of engineering knowledge to inform decision-making within reliability contexts. To ensure customer satisfaction, the text helps readers consciously consider noise factors (environmental variation during the product’s usage, manufacturing variation, and component deterioration) and cost of failure in the field for the Robust Design method. Written by two highly qualified authors, this book includes information on: Effective reliability efforts in an integrated product development environment, failure mode avoidance, and reliability analysis using the physics-of-failure processEssentials of robustness and robust design in reliability improvement, covering design-in reliability up front, eliminating failures prior to testing, and increasing fielded reliabilityRapid, cost-effective deployment of health and usage monitoring systems and improving diagnostic and prognostic techniques and processesROI analyses for PHM, selecting and deploying sensors, setting up data transmission channels, and developing data collection and data pre-processing functionsComprehensive in scope, this book is an essential resource on the subject for all individuals responsible for product development and design, increasing life-cycle product reliability, process quality, or reducing costs in a design, development, manufacturing, and maintenance.

Enhancing Life Cycle Reliability with Robust Engineering and Predictive Health Management Complete process for ensuring product performance through robust concept design, robust optimization, selection, and verification in an uncontrollable user environment Enhancing Life Cycle Reliability with Robust Engineering and Predictive Health Management enables readers to build a robustness-thinking-based approach for robust design for reliability and prognostic health management (PHM), explaining best practices from early product design through the entire product lifecycle, leading to lower costs and shorter development cycles. The text integrates key tools and emerging reliability management systems into a comprehensive program for developing more robust and reliable technology-based products. The text provides value-added strategies for robustness development in new products and health management with three main types of robustness development and reliability growth case studies: intrinsic, instrumental, and collective. Readers can harness multiple forms of engineering knowledge to inform decision-making within reliability contexts. To ensure customer satisfaction, the text helps readers consciously consider noise factors (environmental variation during the product s usage, manufacturing variation, and component deterioration) and cost of failure in the field for the Robust Design method. Written by two highly qualified authors, this book includes information on: Effective reliability efforts in an integrated product development environment, failure mode avoidance, and reliability analysis using the physics-of-failure process Essentials of robustness and robust design in reliability improvement, covering design-in reliability up front, eliminating failures prior to testing, and increasing fielded reliability Rapid, cost-effective deployment of health and usage monitoring systems and improving diagnostic and prognostic techniques and processes ROI analyses for PHM, selecting and deploying sensors, setting up data transmission channels, and developing data collection and data pre-processing functions Comprehensive in scope, this book is an essential resource on the subject for all individuals responsible for product development and design, increasing life-cycle product reliability, process quality, or reducing costs in a design, development, manufacturing, and maintenance.

Enhancing Life Cycle Reliability with Robust Engineering and Predictive Health Management Complete process for ensuring product performance through robust concept design, robust optimization, selection, and verification in an uncontrollable user environment Enhancing Life Cycle Reliability with Robust Engineering and Predictive Health Management enables readers to build a robustness-thinking-based approach for robust design for reliability and prognostic health management (PHM), explaining best practices from early product design through the entire product lifecycle, leading to lower costs and shorter development cycles. The text integrates key tools and emerging reliability management systems into a comprehensive program for developing more robust and reliable technology-based products. The text provides value-added strategies for robustness development in new products and health management with three main types of robustness development and reliability growth case studies: intrinsic, instrumental, and collective. Readers can harness multiple forms of engineering knowledge to inform decision-making within reliability contexts. To ensure customer satisfaction, the text helps readers consciously consider noise factors (environmental variation during the product s usage, manufacturing variation, and component deterioration) and cost of failure in the field for the Robust Design method. Written by two highly qualified authors, this book includes information on: Effective reliability efforts in an integrated product development environment, failure mode avoidance, and reliability analysis using the physics-of-failure process Essentials of robustness and robust design in reliability improvement, covering design-in reliability up front, eliminating failures prior to testing, and increasing fielded reliability Rapid, cost-effective deployment of health and usage monitoring systems and improving diagnostic and prognostic techniques and processes ROI analyses for PHM, selecting and deploying sensors, setting up data transmission channels, and developing data collection and data pre-processing functions Comprehensive in scope, this book is an essential resource on the subject for all individuals responsible for product development and design, increasing life-cycle product reliability, process quality, or reducing costs in a design, development, manufacturing, and maintenance.

This book focuses on software fault detection and correction processes, presenting 5 different paired models introduced over the last decade and discussing their applications, in particular to determining software release time. The first work incorporates the testing effort function and the fault introduction process into the paired fault detection and fault correction models. The second work incorporates fault dependency, while the third adopts a Markov approach for studying fault detection and correction processes. The fourth work considers the multi-release property of various software, and models fault detection and correction processes. The last work classifies faults into four types and models the fault-detection and correction processes. Enabling readers to familiarize themselves with how software reliability can be modeled when different factors need to be considered, and how the approaches can be used to analyze other systems, the book is important referenceguide for researchers in the field of software reliability engineering and practitioners working on software projects. To gain the most from the book, readers should have a firm grasp of the fundamentals of the stochastic process.