Hong-Zhong Huang - Böcker

This book is a detailed introduction to selective maintenance and updates readers on recent advances in this field, emphasizing mathematical formulation and optimization techniques. The book is useful for reliability engineers and managers engaged in the practice of reliability engineering and maintenance management.

This book is a detailed introduction to selective maintenance and updates readers on recent advances in this field, emphasizing mathematical formulation and optimization techniques. The book is useful for reliability engineers and managers engaged in the practice of reliability engineering and maintenance management. It also provides references that will lead to further studies at the end of each chapter. This book is a reference for researchers in reliability and maintenance and can be used as an advanced text for students.

This book provides a comprehensive guide to using data-driven methods in reliability and safety engineering for industrial systems. It explores how modern technologies like data analytics, machine learning, and artificial intelligence can enhance decision-making, predict failures, and improve system resilience.In an era of increasingly complex industrial systems, traditional methods often fail to address reliability and safety challenges. This book highlights how integrating data-driven techniques can optimize system performance, reduce risks, and enhance safety outcomes. Key topics include predictive maintenance, risk assessment, AI integration, and the challenges of implementing these technologies in real-world environments. Case studies across industries like energy and manufacturing illustrate the practical applications of these methods.This book is aimed at professionals in reliability engineering, safety, risk management, and industrial systems, as well as researchers and students seeking to understand the role of data-driven methods in modern engineering practices.

These proceedings gather selected peer-reviewed papers from the 11th World Congress on Engineering Asset Management (WCEAM), which was held in Jiuzhaigou, China, on 25–28 July, 2016. These proceedings cover a wide range of topics in engineering asset management, including:·         strategic asset management;·         condition monitoring and diagnostics;·         integrated intelligent maintenance;·         sensors and devices;·         information quality and management;·         sustainability in asset management;·         asset performance and knowledge management;·         data mining and AI techniques in asset management;·         engineering standards; and·         education in engineering asset management.The breadth and depth of these state-of-the-art, comprehensive proceedings make them an excellent resource for asset management practitioners, researchers and academics, as wellas undergraduate and postgraduate students.

These proceedings gather selected peer-reviewed papers from the 11th World Congress on Engineering Asset Management (WCEAM), which was held in Jiuzhaigou, China, on 25–28 July, 2016. These proceedings cover a wide range of topics in engineering asset management, including:·         strategic asset management;·         condition monitoring and diagnostics;·         integrated intelligent maintenance;·         sensors and devices;·         information quality and management;·         sustainability in asset management;·         asset performance and knowledge management;·         data mining and AI techniques in asset management;·         engineering standards; and·         education in engineering asset management.The breadth and depth of these state-of-the-art, comprehensive proceedings make them an excellent resource for asset management practitioners, researchers and academics, as wellas undergraduate and postgraduate students.

This book gathers selected papers from 2023 International Conference on Mechanical Design (2023 ICMD), held in Chengdu, China.