Download or read book Artificial Intelligence in Maintenance written by J. Jeffrey Richardson and published by William Andrew. This book was released on 1985 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning for Predictive Maintenance written by Jacqueline Hawkins and published by Independently Published. This book was released on 2023-08-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Machine Learning for Predictive Maintenance: AI in Industrial Operations" is a comprehensive guide for anyone interested in understanding how artificial intelligence is transforming industry practices and providing solutions to complex problems. Wrapping up technical concepts in an easy-to-understand language, this report is an indispensable tool for navigating the realm of machine learning and its applications in predictive maintenance. In the heart of manufacturing, machinery failures can result in decreased operational efficiency and increased costs. With the advent of machine learning and AI, such issues can now be predicted and prevented, a revelation that this report brings to light. Taking readers on a step-by-step journey, it covers the collection and preprocessing of data, the application of machine learning models for predictive maintenance, to the fine-tuning and optimization of these models for ideal results. Jacqueline Hawkins, an expert in AI applications and industrial operations, infuses her extensive experience and insights into this report, making it an outstanding resource. From detailed case studies to a look at future trends and opportunities, her grasp on the subject comes through in her playfully articulated content. This book is more than just a technical manual; it's a starting point for industry professionals, tech enthusiasts, or anyone curious about the innovative solutions provided by AI and machine learning for industrial operations. Embrace the future of manufacturing. Discover the exciting world of AI and machine learning. Pick up this report today to start your journey into the tech industry's biggest game changer.
Download or read book Intelligent Predictive Maintenance written by Min Liu and published by Springer Nature. This book was released on with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Driven Energy Centered Maintenance written by Fadi Alshakhshir and published by CRC Press. This book was released on 2021-07-19 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over recent years, many new technologies have been introduced to drive the digital transformation in the building maintenance industry. The current trend in digital evolution involves data-driven decision making which opens new opportunities for an energy centered maintenance model. Artificial Intelligence and Machine Learning are helping the maintenance team to get to the next level of maintenance intelligence to provide real-time early warning of abnormal equipment performance. This edition follows the same methodology as the First. It provides detailed descriptions of the latest technologies associated with Artificial Intelligence and Machine Learning which enable data-driven decision-making processes about the equipment’s operation and maintenance. Technical topics discussed in the book include: Different Maintenance Types and The Need for Energy Centered Maintenance The Centered Maintenance Model Energy Centered Maintenance Process Measures of Equipment and Maintenance Efficiency and Effectiveness Data-Driven Energy Centered Maintenance Model: Digitally Enabled Energy Centered Maintenance Tasks Artificial Intelligence and Machine Learning in Energy Centered Maintenance Model Capabilities and Analytics Rules Building Management System Schematics The book contains a detailed description of the digital transformation process of most of the maintenance inspection tasks as they move away from being manually triggered. The book is aimed at building operators as well as those building automation companies who are working continuously to digitalize building operation and maintenance procedures. The benefits are reductions in the equipment failure rate, improvements in equipment reliability, increases in equipment efficiency and extended equipment lifespan.
Download or read book Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing written by Amit Kumar Tyagi and published by CRC Press. This book was released on 2024-10-23 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.
Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.
Download or read book Energy Centered Maintenance written by Marvin T. Howell and published by CRC Press. This book was released on 2020-11-26 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Energy Centered Maintenance proves a detailed description of how to implement Energy Centered Maintenance (ECM) at any organization. It includes a new six-step technical process with detailed instructions of each of these steps explained with clear examples. Areas covered include preventative maintenance, predictive maintenance and reliability centered maintenance. ECM uses energy consumption excesses or energy waste as the primary criterion for determining specific maintenance or repair needs. Therefore, the primary purpose of this book is to provide strategies to reduce energy use by identifying equipment or items that can become energy hogs while still performing their function and prevent that from occurring. The primary reasons organizations need ECM is due to poor maintenance of energy-using systems and energy losses from motors not turning off when they should. The book includes ECM for electrical, mechanical, building transportation, HVAC, fire-fighting, water supply, drainage and storm water management systems. In some cases, ECM in data centers can help reduce energy consumption by as much as 30%. The six-step process detailed in this text will enable any organization to implement ECM in an orderly, cost effective manner thus improving your equipment and machines, lowering your energy consumption and helping save the planet.
Download or read book Artificial Intelligence written by Marco Antonio Aceves-Fernandez and published by BoD – Books on Demand. This book was released on 2018-06-27 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.
Download or read book IoT Streams for Data Driven Predictive Maintenance and IoT Edge and Mobile for Embedded Machine Learning written by Joao Gama and published by Springer Nature. This book was released on 2021-01-09 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.
Download or read book New Generation Artificial Intelligence Driven Diagnosis and Maintenance Techniques written by Guangrui Wen and published by Springer. This book was released on 2024-06-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance. This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools. The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.
Download or read book Automated Predictive Maintenance System Using Artificial Intelligence Algorithms written by Mateusz Marzec (inżynieria mechaniczna) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence in Structural Engineering written by Ian Smith and published by Springer Science & Business Media. This book was released on 1998-07-15 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems.
Download or read book Artificial Intelligence for Maintenance 4 0 written by Eduardo Calixto and published by . This book was released on 2020-08-05 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: The motivation for this book is to give my homely contribution to the application of Artificial Intelligence concept to the maintenance engineering. In the last 10 years, with the advent of Industry 4.0, new computational algorithms supported by mathematical methods have been implemented in all industries and more intensively in the process industry. Together with such new technology to capture data by using sensor, combined with Artificial Intelligence methods the new concept of Maintenance 4.0 came out. Therefore, this book is structured as follows: The first chapter introduces the concept of Artificial intelligence and its application on the maintenance domain.The second chapter introduces the maintenance concepts by explained the different types of maintenance as well as equipment criticality classification and state of art of maintenance management system.The third Chapter introduces the Prognostic Health management concept and how to predict the Remaining Useful Life and State of Health based on sensor data or data from the non-destructive test.The fourth Chapter introduces the concept of Different types of Machine learning methods such as Unsupervised Machine Learning and Supervised Machine Learning.The Fifth Chapter introduces the concept of Artificial Intelligence Unsupervised Machine Learning (UML) that aims to group data based on it features by demonstrating examples of maintenance planning and equipment clustering. By doing so, different UML methods such as Principal Component Analysis (PCA), Multidimensional Scaling (MDS), K-Means, Gaussian Mixture, Hierarchical Cluster, and Neural Network Self Organized Map are presented.The sixth chapter presents the Artificial intelligence Supervised Machine Learning Classification that aims to classify the equipment based on different class of risk or criticality as well as to define high level of equipment degradation for alarm set up. Therefore, different method with several examples applied to maintenance such as K-Nearest Neighbor (K-NN), Decision Tree, Naïve Bayes, Discriminant Analysis, Support Vector Machine (SVM) and Neural Network Classification are presented.The seventh chapter presents the Artificial Intelligence Supervised Machine Learning Regression methods that aims to predict a dependent variable such as RUL or SoH based on the past dependent and independent variable values. Therefore, different methods with several examples of RUL regression prediction take place such as Linear Regression, Support Vector Machine, Decision Tree, Ridge and Lasso methods, Stepwise and Neural network.The eighth chapter presents the concept of Ensemble methods that aims to reduce the classification or regression prediction error by creating new subset samples from the main database. The different Ensemble methods such as Random treeThe ninth chapter aims to present the concept of Deep Neural Network and Convolutional Neural Network by given an example of image classification applied to RUL prediction and Infrared thermography image classification.The tenth chapter aims to present the concept of Asset Management Intelligence 4.0 that aims to encompasses the concepts defined in the ISO55001 and the PHM and Artificial Intelligence concepts presented in the previous chapter. Therefore, AMI in a system that integrate the data and display intelligent information and prediction that enable maintenance leaders and expert out their effort in data assessment and fast decision rather than data collection, preparation, and predictions.
Download or read book AI Based Predictive Maintenance written by Minghai Zheng and published by Independently Published. This book was released on 2023-06-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Want to ensure optimal equipment performance and availability in your business? Check out this must-read book on #AI-based predictive maintenance! 2. Don't risk downtime and lost revenue due to equipment failure! Discover how #AI can help you achieve optimal performance and availability with this insightful book. 3. Looking to boost your business's operational efficiency and productivity? Learn how #AI-based predictive maintenance can help with this essential read. 4. If you're in the manufacturing or industrial sector, you can't afford to miss this book on #AI-based predictive maintenance for achieving maximum equipment performance and availability. 5. Searching for ways to reduce maintenance costs and improve equipment uptime? Look no further than this comprehensive guide to #AI-based predictive maintenance. AI-based predictive maintenance is a rapidly growing field that involves the use of artificial intelligence (AI) algorithms to predict when equipment maintenance issues are likely to occur. By analyzing data from equipment sensors, AI-based predictive maintenance can identify potential problems before they become major issues, allowing businesses to take proactive measures to ensure optimal equipment performance and availability. The benefits of AI-based predictive maintenance are numerous, including reduced downtime and maintenance costs, increased equipment uptime and availability, and improved operational efficiency. However, implementing AI-based predictive maintenance requires a careful assessment of equipment and maintenance practices and consideration of ethical considerations and challenges associated with its use. This book, "AI-Based Predictive Maintenance: Ensuring Optimal Equipment Performance and Availability," explores the various techniques and strategies used in AI-based predictive maintenance, including condition-based maintenance, prognostics and health management, and integration into industrial systems. The book also discusses ethical considerations and challenges associated with the use of AI in predictive maintenance. By examining these topics, this book provides businesses with the knowledge and tools necessary to implement effective AI-based predictive maintenance programs. Whether you are a maintenance professional seeking to optimize your equipment performance or a business leader looking to gain a competitive edge, this book is an essential resource for anyone interested in the power of AI-based predictive maintenance. MingHai Zheng is the founder of zhengpublishing.com and lives in Wuhan, China. His main publishing areas are business, management, self-help, computers and other emerging foreword fields.
Download or read book Applying Artificial Intelligence to Project Management written by Paul Boudreau and published by . This book was released on 2019-11-13 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author Paul Boudreau shares the keys to project management success using a modern approach: artificial intelligence. Within the pages of Applying Artificial Intelligence to Project Management, Boudreau describes five AI tools in concept and how they apply directly to project success, as well as the strategy and method to use to purchase and implement AI tools for project management. Understand the difference between automating a task and changing it by using AI. Discover how AI uses data and the importance of data maintenance. Learn why projects fail and how using artificial intelligence for project management improves project success rates. Read project management success stories in one of the best business books on machine learning, and prepare to leave behind that 50 percent project success rate for one that's 95 percent or higher.
Download or read book Photovoltaic Systems written by K.Mohana Sundaram and published by CRC Press. This book was released on 2022-03-07 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive insight into the fault detection techniques implemented for photovoltaic (PV) panels. It includes studies related to predictive maintenance needed to improve the performance of the solar PV systems using Artificial Intelligence (AI) techniques. The readers gain knowledge on the fault identification algorithm and the significance of all such algorithms in real-time power system applications. Gives detailed overview of fundamental concepts of fault diagnosis algorithm for solar PV system Explains AC and DC side of the solar PV system-based electricity generation with real-time examples Covers effective extraction of the energy from solar radiation Illustrates artificial intelligence techniques for detecting the faults occurring in the solar PV system Includes MATLAB® based simulations and results on fault diagnosis including case studies This book is aimed at researchers, professionals and graduate students in electrical engineering, artificial intelligence, control algorithms, energy engineering, photovoltaic systems, industrial electronics.
Download or read book Data Driven Energy Centered Maintenance written by Fadi Alshakhshir and published by CRC Press. This book was released on 2021-07-20 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over recent years, many new technologies have been introduced to drive the digital transformation in the building maintenance industry. The current trend in digital evolution involves data-driven decision making which opens new opportunities for an energy centered maintenance model. Artificial Intelligence and Machine Learning are helping the maintenance team to get to the next level of maintenance intelligence to provide real-time early warning of abnormal equipment performance. This edition follows the same methodology as the First. It provides detailed descriptions of the latest technologies associated with Artificial Intelligence and Machine Learning which enable data-driven decision-making processes about the equipment’s operation and maintenance. Technical topics discussed in the book include: Different Maintenance Types and The Need for Energy Centered Maintenance The Centered Maintenance Model Energy Centered Maintenance Process Measures of Equipment and Maintenance Efficiency and Effectiveness Data-Driven Energy Centered Maintenance Model: Digitally Enabled Energy Centered Maintenance Tasks Artificial Intelligence and Machine Learning in Energy Centered Maintenance Model Capabilities and Analytics Rules Building Management System Schematics The book contains a detailed description of the digital transformation process of most of the maintenance inspection tasks as they move away from being manually triggered. The book is aimed at building operators as well as those building automation companies who are working continuously to digitalize building operation and maintenance procedures. The benefits are reductions in the equipment failure rate, improvements in equipment reliability, increases in equipment efficiency and extended equipment lifespan.
