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 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 Dynamic Systems written by Edwin Lughofer and published by Springer. This book was released on 2019-02-28 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.
Download or read book Fundamentals of Machine Learning for Predictive Data Analytics second edition written by John D. Kelleher and published by MIT Press. This book was released on 2020-10-20 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
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 Predictive Analytics with Microsoft Azure Machine Learning written by Valentine Fontama and published by Apress. This book was released on 2014-11-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.
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 Machine Learning for Cyber Physical Systems written by Jürgen Beyerer and published by Springer. This book was released on 2018-12-17 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Download or read book Knowledge Management in Organizations written by Lorna Uden and published by Springer. This book was released on 2018-07-30 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the refereed proceedings of the 13th International Conference on Knowledge Management in Organizations, KMO 2018, held in Žilina, Slovakia, in August 2018. The theme of the conference was "Emerging Research for Knowledge Management in Organizations." The 59 papers accepted for KMO 2018 were selected from 141 submissions and are organized in topical sections on: Knowledge management models and analysis; knowledge sharing; knowledge transfer and learning; knowledge and service innovation; knowledge creation; knowledge and organization; information systems and information science; knowledge and technology management; data mining and intelligent science; business and customer relationship management; big data and IoT; and new trends in IT.
Download or read book Advances in Production Management Systems Smart Manufacturing for Industry 4 0 written by Ilkyeong Moon and published by Springer. This book was released on 2018-08-24 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set IFIP AICT 535 and 536 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2018, held in Seoul, South Korea, in August 2018. The 129 revised full papers presented were carefully reviewed and selected from 149 submissions. They are organized in the following topical sections: lean and green manufacturing; operations management in engineer-to-order manufacturing; product-service systems, customer-driven innovation and value co-creation; collaborative networks; smart production for mass customization; global supply chain management; knowledge based production planning and control; knowledge based engineering; intelligent diagnostics and maintenance solutions for smart manufacturing; service engineering based on smart manufacturing capabilities; smart city interoperability and cross-platform implementation; manufacturing performance management in smart factories; industry 4.0 - digital twin; industry 4.0 - smart factory; and industry 4.0 - collaborative cyber-physical production and human systems.
Download or read book Ensemble Machine Learning written by Cha Zhang and published by Springer Science & Business Media. This book was released on 2012-02-17 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
Download or read book Industry 4 1 written by Fan-Tien Cheng and published by John Wiley & Sons. This book was released on 2021-10-26 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industry 4.1 Intelligent Manufacturing with Zero Defects Discover the future of manufacturing with this comprehensive introduction to Industry 4.0 technologies from a celebrated expert in the field Industry 4.1: Intelligent Manufacturing with Zero Defects delivers an in-depth exploration of the functions of intelligent manufacturing and its applications and implementations through the Intelligent Factory Automation (iFA) System Platform. The book’s distinguished editor offers readers a broad range of resources that educate and enlighten on topics as diverse as the Internet of Things, edge computing, cloud computing, and cyber-physical systems. You’ll learn about three different advanced prediction technologies: Automatic Virtual Metrology (AVM), Intelligent Yield Management (IYM), and Intelligent Predictive Maintenance (IPM). Different use cases in a variety of manufacturing industries are covered, including both high-tech and traditional areas. In addition to providing a broad view of intelligent manufacturing and covering fundamental technologies like sensors, communication standards, and container technologies, the book offers access to experimental data through the IEEE DataPort. Finally, it shows readers how to build an intelligent manufacturing platform called an Advanced Manufacturing Cloud of Things (AMCoT). Readers will also learn from: An introduction to the evolution of automation and development strategy of intelligent manufacturing A comprehensive discussion of foundational concepts in sensors, communication standards, and container technologies An exploration of the applications of the Internet of Things, edge computing, and cloud computing The Intelligent Factory Automation (iFA) System Platform and its applications and implementations A variety of use cases of intelligent manufacturing, from industries like flat-panel, semiconductor, solar cell, automotive, aerospace, chemical, and blow molding machine Perfect for researchers, engineers, scientists, professionals, and students who are interested in the ongoing evolution of Industry 4.0 and beyond, Industry 4.1: Intelligent Manufacturing with Zero Defects will also win a place in the library of laypersons interested in intelligent manufacturing applications and concepts. Completely unique, this book shows readers how Industry 4.0 technologies can be applied to achieve the goal of Zero Defects for all product
Download or read book Machine Learning and Data Science in the Oil and Gas Industry written by Patrick Bangert and published by Gulf Professional Publishing. This book was released on 2021-03-04 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)
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 Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Download or read book Congress on Intelligent Systems written by Harish Sharma and published by Springer. This book was released on 2021-05-28 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of selected papers presented at the First Congress on Intelligent Systems (CIS 2020), held in New Delhi, India during September 5 – 6, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers topics such as Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro fuzzy systems.
Download or read book Machine Learning Models for Predictive Maintenance written by Sergii Voronov and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
