Emaintenance

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. Provides an introduction to collecting and processing data from machinery Explains how to use sensor-based tools to increase efficiency of diagnosis, prognosis, and decision-making in maintenance Describes methods for overcoming the challenges of data collection and processing

This proceedings brings together the papers presented at the International Congress and Workshop on Industrial AI and eMaintenance 2023 (IAI2023). The conference integrates the themes and topics of three conferences: Industrial AI & eMaintenance, Condition Monitoring and Diagnostic Engineering Management (COMADEM) and, Advances in Reliability, Maintainability and Supportability (ARMS) on a single platform. This proceedings serves both academy and industry in providing an excellent platform for collaboration by providing a forum for exchange of ideas and networking. The 21st century has seen remarkable progress in Artificial Intelligence, with application to a variety of fields (computer vision, automatic translation, sentiment analysis in social networks, robotics, etc.) The IAI2023 focuses on Industrial Artificial Intelligence, or IAI. The emergence of industrial AI applications holds tremendous promises in terms of achieving excellence and cost-effectiveness in the operation and maintenance of industrial assets. Opportunities in Industrial AI exist in many industries such as aerospace, railways, mining, construction, process industry, etc. Its development is powered by several trends: the Internet of Things (IoT); the increasing convergence between OT (operational technologies) and IT (information technologies); last but not least, the unabated fast-paced developments of advanced analytics. However, numerous technical and organizational challenges to the widespread development of industrial AI still exist. The IAI2023 conference and its proceedings foster fruitful discussions between AI creators and industrial practitioners.

An indispensable guide for engineers and data scientists in design, testing, operation, manufacturing, and maintenance A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management (PHM), this important work covers all areas of electronics and explains how to: assess methods for damage estimation of components and systems due to field loading conditions assess the cost and benefits of prognostic implementations develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions enable condition-based (predictive) maintenance increase system availability through an extension of maintenance cycles and/or timely repair actions; obtain knowledge of load history for future design, qualification, and root cause analysis reduce the occurrence of no fault found (NFF) subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.

This text represents state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Sixth World Congress on Engineering Asset Management (WCEAM) held in Cincinnati, OH, USA from October 3-5, 2011 The Proceedings of the WCEAM 2011 is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering topics such as: Asset condition monitoring and intelligent maintenance; Asset data warehousing, data mining and fusion; Asset performance and level-of-service models; Design and lifecycle integrity of physical assets; Deterioration and preservation models for assets; Education and training in asset management; Engineering standards in asset management; Fault diagnosis and prognostics; Financial analysis methods for physical assets; Human dimensions in integrated asset management; Information quality management; Information systems and knowledge management; Intelligent maintenance; Intelligent sensors and devices; Maintenance strategies in asset management; Optimization decisions in asset management; Prognostics & Health Management; Risk management in asset management; Strategic asset management; and Sustainability in asset management.

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

This book discusses action-oriented, concise and easy-to-communicate goals and challenges related to quality, reliability, infocomm technology and business operations. It brings together groundbreaking research in the area of software reliability, e-maintenance and big data analytics, highlighting the importance of maintaining the current growth in information technology (IT) adoption in businesses, while at the same time proposing process innovations to ensure sustainable development in the immediate future. In its thirty-seven chapters, it covers various areas of e-maintenance solutions, software architectures, patching problems in software reliability, preventive maintenance, industrial big data and reliability applications in electric power systems. The book reviews the ways in which countries currently attempt to resolve the conflicts and opportunities related to quality, reliability, IT and business operations, and proposes that internationally coordinated research plans are essential for effective and sustainable development, with research being most effective when it uses evidence-based decision-making frameworks resulting in clear management objectives, and is organized within adaptive management frameworks. Written by leading experts, the book is of interest to researchers, academicians, practitioners and policy makers alike who are working towards the common goal of making business operations more effective and sustainable.

Whether used for communication, entertainment, socio-economic growth, crowd-sourcing social and political events, monitoring vital signs in patients, helping to drive vehicles, or delivering education, mobile technology has been transformed from a mode to a medium. Mobile Technology Consumption: Opportunities and Challenges explores essential questions related to the cost, benefit, individual and social impact, and security risks associated with the rapid consumption of mobile technology. This book presents the current state of mobile technologies and their use in various domains including education, healthcare, government, entertainment, and emerging economic sectors.

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