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 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 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 Predictive Maintenance in Smart Factories written by Tania Cerquitelli and published by Springer Nature. This book was released on 2021-08-26 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.

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 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 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 An Introduction to Predictive Maintenance written by R. Keith Mobley and published by Elsevier. This book was released on 2002-10-24 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of An Introduction to Predictive Maintenance helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of An Introduction to Predictive Maintenance will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. A comprehensive introduction to a system of monitoring critical industrial equipment Optimize the availability of process machinery and greatly reduce the cost of maintenance Provides the means to improve product quality, productivity and profitability of manufacturing and production plants

Download or read book Prognostics and Health Management of Engineering Systems written by Nam-Ho Kim and published by Springer. This book was released on 2016-10-24 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application.Among the many topics discussed in-depth are:• Prognostics tutorials using least-squares• Bayesian inference and parameter estimation• Physics-based prognostics algorithms including nonlinear least squares, Bayesian method, and particle filter• Data-driven prognostics algorithms including Gaussian process regression and neural network• Comparison of different prognostics algorithms divThe authors also present several applications of prognostics in practical engineering systems, including wear in a revolute joint, fatigue crack growth in a panel, prognostics using accelerated life test data, fatigue damage in bearings, and more. Prognostics tutorials with a Matlab code using simple examples are provided, along with a companion website that presents Matlab programs for different algorithms as well as measurement data. Each chapter contains a comprehensive set of exercise problems, some of which require Matlab programs, making this an ideal book for graduate students in mechanical, civil, aerospace, electrical, and industrial engineering and engineering mechanics, as well as researchers and maintenance engineers in the above fields.

Download or read book Advanced Manufacturing and Automation VII written by Kesheng Wang and published by Springer. This book was released on 2018-02-10 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings brings together a selection of papers from the 7th International Workshop of Advanced Manufacturing and Automation (IWAMA 2017), held in Changshu Institute of Technology, Changshu, China on September 11–12, 2017. Most of the topics are focusing on novel techniques for manufacturing and automation in Industry 4.0. These contributions are vital for maintaining and improving economic development and quality of life. The proceeding will assist academic researchers and industrial engineers to implement the concepts and theories of Industry 4.0 in industrial practice, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.

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 Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing written by Amit Kumar Tyagi and published by . This book was released on 2024-09-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics and Artificial Intelligence (AI) play an important role in Predictive Maintenance (PdM) within the manufacturing industry. 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.

Download or read book Artificial Intelligence for Digitising Industry Applications written by Ovidiu Vermesan and published by CRC Press. This book was released on 2022-09-01 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

Download or read book Advances in Production Management Systems Towards Smart and Digital Manufacturing written by Bojan Lalic and published by Springer Nature. This book was released on 2020-08-25 with total page 783 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set IFIP AICT 591 and 592 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2020, held in Novi Sad, Serbia, in August/September 2020. The 164 papers presented were carefully reviewed and selected from 199 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: Part I: advanced modelling, simulation and data analytics in production and supply networks; advanced, digital and smart manufacturing; digital and virtual quality management systems; cloud-manufacturing; cyber-physical production systems and digital twins; IIOT interoperability; supply chain planning and optimization; digital and smart supply chain management; intelligent logistics networks management; artificial intelligence and blockchain technologies in logistics and DSN; novel production planning and control approaches; machine learning and artificial intelligence; connected, smart factories of the future; manufacturing systems engineering: agile, flexible, reconfigurable; digital assistance systems: augmented reality and virtual reality; circular products design and engineering; circular, green, sustainable manufacturing; environmental and social lifecycle assessments; socio-cultural aspects in production systems; data-driven manufacturing and services operations management; product-service systems in DSN; and collaborative design and engineering Part II: the Operator 4.0: new physical and cognitive evolutionary paths; digital transformation approaches in production management; digital transformation for more sustainable supply chains; data-driven applications in smart manufacturing and logistics systems; data-driven services: characteristics, trends and applications; the future of lean thinking and practice; digital lean manufacturing and its emerging practices; new reconfigurable, flexible or agile production systems in the era of industry 4.0; operations management in engineer-to-order manufacturing; production management in food supply chains; gastronomic service system design; product and asset life cycle management in the circular economy; and production ramp-up strategies for product

Download or read book 2019 International Conference on Electrical and Computing Technologies and Applications ICECTA written by IEEE Staff and published by . This book was released on 2019-11-19 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference focuses on the latest theoretical and practical developments in the fields of Electrical Engineering, Computing Technologies, their Applications and the related fields It aims to provide engineers, professionals, academics and researchers with a platform to share their current research findings and explore recent developments, current practices and future research directions

Download or read book Intelligent Predictive Maintenance written by Min Liu and published by Springer. This book was released on 2024-08-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the field of equipment/product operation and maintenance (O&M) services, the new generation of information technologies such as the internet, big data, and artificial intelligence are deeply integrated with O&M services to form an internet-based Maintenance Repair & Operation (MRO) service network and an intelligent service environment. To deal with the uncertainties of multiple collaborative entities and highly random equipment failures in the large-scale MRO network, this book establishes the theory, technology, and methods of Intelligent Predictive Maintenance (IPdM) for the MRO service network through the study of high-quality acquisition and integration of multi-source heterogeneous data, data-driven equipment fault diagnosis and prediction, large-scale maintenance decision-making, feedback, and control. The book systematically elaborates on the emerging theories, technologies, and methods in the field of equipment/product O&M services, covering a wide range of topics with rich contents. It emphasizes both systematic and scientific approaches as well as practicality. It offers both comprehensive and specialized discussions to reflect the strategic deployment and implementation of China's new generation of intelligent manufacturing and artificial intelligence in this field. The basis of English translation of this book, originally in Chinese, was facilitated by artificial intelligence. The content was later revised by the author for accuracy.

Download or read book Powering the Digital Economy Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.