Maintenance Audits Handbook: A Performance Measurement Framework explores the maintenance function and performance of an organization, and outlines the key aspects required for an effective and efficient maintenance performance measurement (MPM) system. Incorporating different aspects of traditional literature and considering various frameworks on the subject, it examines the auditing process as well as the use and development of maintenance metrics. It identifies different frameworks and models showcasing how MPM systems should be implemented as well as the values that are created when different frameworks are used. The book presents performance indicators within a framework that classifies and sorts according to functional and hierarchical aspects. It introduces techniques that can help determine the right set of performance indicators. It also outlines a process that combines both numerical indicators with the classical result of massive questionnaires successfully incorporating both the quantitative and qualitative aspects of maintenance performance. In addition, the author provides examples of MPM frameworks that are used in organizations with condition-based, vibration-based, and reliability-centered maintenance. A useful handbook for students and maintenance professionals, this book provides readers with an understanding of how to Align the organizational strategy to the strategies of the maintenance function Link the maintenance performance measures to the different hierarchies of the organization and establish effective communication between them Translate the MPIs at operational level to the corporate level (to create value for the whole organization and its customers) Identify the weaknesses and strengths of the implemented maintenance strategy Maintenance Audits Handbook: A Performance Measurement Framework provides readers with a sound foundation for developing and measuring a comprehensive maintenance improvement strategy using qualitative and quantitative data, and serves as an ideal resource for maintenance/mechanical engineers, maintenance/performance/business/production managers and industry professionals involved in maintenance.

Presents compendium of Remaining Useful Life (RUL) estimation methods and technologies used in predictive maintenance. Describes different approaches and prognosis methods for different assets. Includes comprehensive compilation of methods from model based, data driven to hybrid. Discusses benchmarking of RUL estimation methods according to accuracy an uncertainty depending on the target application, type of asset and forecast performance expected. Contains toolset of methods and way of deployment aimed at versatile audience.

This book provides insights on how to approach and utilize data science tools, technologies and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI-technologies, and their inter-connections. Description of various technology and methodology approaches, and their purpose and benefits when developing AI-solution in industrial contexts is included. In addition, it summarizes experiences from AI technology deployment projects from several industrial sectors. Features: Presents compendium of methodologies and technologies in Industrial AI and digitalization. Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept. Covers a broad range of academic and industrial issues within the field of asset management. Discusses impact of Industry 4.0 in other sectors. Includes a dedicated chapter on real-time case studies. This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and ML, engineering managers, operational and maintenance specialists, asset managers, digital and AI manufacturing specialists.

Authors have attempted to create coherent chapters and sections on how the fundamentals of maintenance cost should be organized, to present them in a logical and sequential order. Necessarily, the text starts with importance of maintenance function in the organization and moves to life cycle cost (LCC) considerations followed by the budgeting constraints. In the process, they have intentionally postponed the discussion about intangible costs and downtime costs later on in the book mainly due to the controversial part of it when arguing with managers. The book will be concluding with a short description of a number of sectors where maintenance cost is of critical importance. The goal is to train the readers for a deeper study and understanding of these elements for decision making in maintenance, more specifically in the context of asset management. This book is intended for managers, engineers, researchers, and practitioners, directly or indirectly involved in the area of maintenance. The book is focused to contribute towards better understanding of maintenance cost and use of this knowledge to improve the maintenance process. Key Features: * Emphasis on maintenance cost and life cycle cost especially under uncertainty. * Systematic approach of how cost models can be applied and used in the maintenance field. * Compiles and reviews existing maintenance cost models. * Consequential and direct costs considered. * Comparison of maintenance costs in different sectors, infrastructure, manufacturing, transport.

Authors have attempted to create coherent chapters and sections on how the fundamentals of maintenance cost should be organized, to present them in a logical and sequential order. Necessarily, the text starts with importance of maintenance function in the organization and moves to life cycle cost (LCC) considerations followed by the budgeting constraints. In the process, they have intentionally postponed the discussion about intangible costs and downtime costs later on in the book mainly due to the controversial part of it when arguing with managers. The book will be concluding with a short description of a number of sectors where maintenance cost is of critical importance. The goal is to train the readers for a deeper study and understanding of these elements for decision making in maintenance, more specifically in the context of asset management. This book is intended for managers, engineers, researchers, and practitioners, directly or indirectly involved in the area of maintenance. The book is focused to contribute towards better understanding of maintenance cost and use of this knowledge to improve the maintenance process. Key Features: * Emphasis on maintenance cost and life cycle cost especially under uncertainty. * Systematic approach of how cost models can be applied and used in the maintenance field. * Compiles and reviews existing maintenance cost models. * Consequential and direct costs considered. * Comparison of maintenance costs in different sectors, infrastructure, manufacturing, transport.

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB (R) code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

Industry 4.0 refers to fourth generation of industrial activity characterized by smart systems and internet-based solutions. This book describes the fourth revolution based on instrumented, interconnected and intelligent assets. The different book chapters provide a perspective on technologies and methodologies developed and deployed leading to this concept. With an aim to increase performance, productivity and flexibility, major application area of maintenance through smart system has been discussed in detail. Applicability of 4.0 in transportation, energy and infrastructure is explored, with effects on technology, organisation and operations from a systems perspective.

Industrial assets (such as railway lines, roads, pipelines) are usually huge, span long distances, and can be divided into clusters or segments that provide different levels of functionality subject to different loads, degradations and environmental conditions, and their efficient management is necessary. The aim of the book is to give comprehensive understanding about the use of autonomous vehicles (context of robotics) for the utilization of inspection and maintenance activities in industrial asset management in different accessibility and hazard levels. The usability of deploying inspection vehicles in an autonomous manner is explained with the emphasis on integrating the total process. Key Features Aims for solutions for maintenance and inspection problems provided by robotics, drones, unmanned air vehicles and unmanned ground vehicles Discusses integration of autonomous vehicles for inspection and maintenance of industrial assets Covers the industrial approach to inspection needs and presents what is needed from the infrastructure end Presents the requirements for robot designers to design an autonomous inspection and maintenance system Includes practical case studies from industries

eMaintenance: Essential Electronic Tools for Efficiency enables the reader to improve efficiency of operations, maintenance staff, infrastructure managers and system integrators, by accessing a real time computerized system from data to decision. In recent years, the exciting possibilities of eMaintenance have become increasingly recognized as a source of productivity improvement in industry. The seamless linking of systems and equipment to control centres for real time reconfiguring is improving efficiency, reliability, and sustainability in a variety of settings. The book provides an introduction to collecting and processing data from machinery, explains the methods of overcoming the challenges of data collection and processing, and presents tools for data driven condition monitoring and decision making. This is a groundbreaking handbook for those interested in the possibilities of running a plant as a smart asset.

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB (R) code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

Maintenance Audits Handbook: A Performance Measurement Framework explores the maintenance function and performance of an organization, and outlines the key aspects required for an effective and efficient maintenance performance measurement (MPM) system. Incorporating different aspects of traditional literature and considering various frameworks on the subject, it examines the auditing process as well as the use and development of maintenance metrics. It identifies different frameworks and models showcasing how MPM systems should be implemented as well as the values that are created when different frameworks are used. The book presents performance indicators within a framework that classifies and sorts according to functional and hierarchical aspects. It introduces techniques that can help determine the right set of performance indicators. It also outlines a process that combines both numerical indicators with the classical result of massive questionnaires successfully incorporating both the quantitative and qualitative aspects of maintenance performance. In addition, the author provides examples of MPM frameworks that are used in organizations with condition-based, vibration-based, and reliability-centered maintenance. A useful handbook for students and maintenance professionals, this book provides readers with an understanding of how to Align the organizational strategy to the strategies of the maintenance function Link the maintenance performance measures to the different hierarchies of the organization and establish effective communication between them Translate the MPIs at operational level to the corporate level (to create value for the whole organization and its customers) Identify the weaknesses and strengths of the implemented maintenance strategy Maintenance Audits Handbook: A Performance Measurement Framework provides readers with a sound foundation for developing and measuring a comprehensive maintenance improvement strategy using qualitative and quantitative data, and serves as an ideal resource for maintenance/mechanical engineers, maintenance/performance/business/production managers and industry professionals involved in maintenance.