Download or read book Intelligent Maintenance and Monitoring Strategy for Smart Manufacturing Systems written by Honghan Ye and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In smart manufacturing systems, production scheduling, maintenance decision-making, and process monitoring are three key, closely interconnected components, which play significant roles in the system performance, quality control, and overall cost. Due to the rapid advancement of in-process measurements and sensor technology, massive data frequently appear in modern industries. While such a data-rich environment has the potential to better reveal real-time details of the underlying system and make better decisions for the system improvement, it also presents significant challenges in the following perspectives: (i) how to effectively leverage the acquired knowledge to balance trade-offs between conflicting objectives, (ii) how to optimally design the monitoring system given the practical resources constraint, and (iii) how to efficiently handle the high-dimensional heterogeneous information with different acquisition rates, distributions, and characteristics. This thesis concentrates on production and maintenance scheduling, and process monitoring to develop systematic analytics methodologies for quality control, cost reduction, and performance improvement in smart manufacturing systems. By incorporating engineering domain knowledge with advanced statistical techniques, the proposed methodologies facilitate (i) the real-time decisions that improve the system production and maintenance scheduling, (ii) the effective monitoring of system status, (iii) the informative and intelligent decisions on balancing between exploration and exploitation given the limited monitoring resources, and (iv) the asynchronous process monitoring with different data acquisition rates. The first chapter introduces the background and challenges in production and maintenance scheduling, and monitoring in smart manufacturing systems, and establishes the major research objective of the thesis. Chapter 2 addresses a joint scheduling problem that considers corrective maintenance (CM) due to unexpected breakdowns and scheduled preventive maintenance (PM) in a generic M-machine flow shop. The objective is to find the optimal job sequence and PM schedule such that the total of tardiness cost, PM cost, and CM cost is minimized. To address this critical research issue, our novel idea is to dynamically update the PM interval based on real-time machine age, such that maintenance activity coordinates with job scheduling to the maximum extent, which results in an overall cost saving. With the rapid development of sensor technology, real-time observations from the sensors can be used to describe the machine status more accurately and achieve early anomaly detection. In Chapter 3, we propose a nonparametric monitoring and sampling algorithm integrated with Thompson sampling to quickly detect abnormalities occurring in heterogeneous data streams. In particular, a Bayesian approach is incorporated with an antirank-based cumulative sum (CUSUM) procedure to collectively estimate the underlying status of all data streams based on the partially observed data. Furthermore, an intelligent sampling strategy based on Thompson sampling (TS) algorithm is proposed to dynamically observe the informative data streams and balance between exploration and exploitation to facilitate quick anomaly detection. While the proposed method in Chapter 3 shows good performance in monitoring heterogeneous data streams, it heavily relies on the assumption that full historical in-control observations of all data streams are available offline, which does not always hold in practice. To address this issue, Chapter 4 further proposes a generic online nonparametric monitoring and sampling scheme occurring in high-dimensional heterogeneous processes when only partial observations are available. Specifically, we integrate the TS algorithm with a quantile-based nonparametric CUSUM procedure to construct local statistics of all data streams based on the partially observed data. Further, we develop a global monitoring scheme by using the sum of top-r local statistics to screen out the most suspicious data streams. Chapter 5 proposes a generic top - r based asynchronous monitoring (TRAM) framework to online monitor high-dimensional heterogeneous and asynchronous processes, where measurements of each data stream follow arbitrary distributions and are collected at different sampling intervals. In particular, we first adopt a quantile-based nonparametric CUSUM scheme to monitor each data stream locally. Then, an effective compensation strategy is proposed for unsampled data streams at the local statistics level to alleviate severe detection delay when mean shifts occur to long-sampling-interval data streams. Furthermore, we develop a global monitoring scheme using the sum of top - r local statistics, which is able to quickly detect a wide range of possible mean shifts in all directions. Chapter 6 then summarizes the contribution of the thesis. In summary, this thesis contributes to developing systematic analytics methodologies for quality control, cost reduction, and performance improvement in smart manufacturing systems. The developed methods are generic and can also be applied to other applications such as healthcare, energy and climate research, which will lead to improved maintenance scheduling, efficient resource allocation, and significant overall cost savings.

Download or read book Condition Monitoring and Control for Intelligent Manufacturing written by Lihui Wang and published by Springer Science & Business Media. This book was released on 2006-08-02 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Condition modelling and control is a technique used to enable decision-making in manufacturing processes of interest to researchers and practising engineering. Condition Monitoring and Control for Intelligent Manufacturing will be bought by researchers and graduate students in manufacturing and control and engineering, as well as practising engineers in industries such as automotive and packaging manufacturing.

Download or read book Smart Sustainable Manufacturing Systems written by Dimitris Kiritsis (Kyritsis) and published by MDPI. This book was released on 2019-08-14 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities. Advanced manufacturing systems are of paramount importance in making key enabling technologies and new products more competitive, affordable, and accessible, as well as for fostering their economic and social impact. The manufacturing industry also serves as an innovator for sustainability since automation coupled with advanced manufacturing technologies have helped manufacturing practices transition into the circular economy. To that end, this Special Issue of the journal Applied Sciences, devoted to the broad field of Smart Sustainable Manufacturing Systems, explores recent research into the concepts, methods, tools, and applications for smart sustainable manufacturing, in order to advance and promote the development of modern and intelligent manufacturing systems. In light of the above, this Special Issue is a collection of the latest research on relevant topics and addresses the current challenging issues associated with the introduction of smart sustainable manufacturing systems. Various topics have been addressed in this Special Issue, which focuses on the design of sustainable production systems and factories; industrial big data analytics and cyberphysical systems; intelligent maintenance approaches and technologies for increased operating life of production systems; zero-defect manufacturing strategies, tools and methods towards online production management; and connected smart factories.

Download or read book Intelligent Manufacturing Management Systems written by Kamalakanta Muduli and published by John Wiley & Sons. This book was released on 2023-05-31 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTRELLIGENT MANUFACTURING MANAGEMENT SYSTEMS The book explores the latest manufacturing techniques in relation to AI and evolutionary algorithms that can monitor and control the manufacturing environment. The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration. In addition, the reader will find: Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems; Highlights of the current and highly relevant topics in manufacturing management; Structured presentations resolving the issues being faced by many real-world applications in a broad range of areas such as smart supply chains, knowledge management, intelligent inventory management, IoT adoption in manufacturing management, and more; Intelligent techniques for sustainable practices in industrial waste management. Audience The book will be used by researchers, industry engineers, and data scientists/AI specialists working in industrial engineering, mechanical engineering, production engineering, manufacturing engineering, and operations and supply chain management. The book will also be valuable to the service sector industry, such as logistics and those implementing smart cities.

Download or read book New Approaches in Management of Smart Manufacturing Systems written by Lucia Knapcikova and published by Springer Nature. This book was released on 2020-06-30 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and effective exchange of information on current developments in the management of manufacturing systems and Industry 4.0. The book aims to establish channels of communication and disseminate knowledge among professionals working in manufacturing and related institutions. In the book, researchers, academicians and practitioners in relevant fields share their knowledge from the sectors of management of manufacturing systems. The chapters were selected from several conferences in the field, with the topics including management of manufacturing systems with support for Industry 4.0, logistics and intelligent manufacturing systems and applications, cooperation management, and its effective applications. The book also includes case studies in logistics, RFID applications, and economic impacts in logistics, ICT support for industry 4.0, industrial and smart logistics, intelligent manufacturing systems and applications

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 Smart Manufacturing Factory written by Jiafu Wan and published by CRC Press. This book was released on 2023-12-14 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) technologies enable manufacturing systems to sense the environment, adapt to external needs, and extract process knowledge, including business models such as intelligent production, networked collaboration, and extended service models. This book therefore focuses on the implementation of AI in customized manufacturing (CM). The main topics include edge intelligence in manufacturing, heterogeneous networks, intelligent fault diagnosis and maintenance, dynamic resource scheduling in manufacturing, and the construction mode of the smart factory. Based on the insights of CM and AI, the authors demonstrate the implementation of AI in the smart factory for CM, including architecture, information fusion, data analysis, dynamic scheduling, flexible production line construction, and smart manufacturing services. This book will provide important research content for scholars in artificial intelligence, smart manufacturing, machine learning, multi-agent systems, and industrial Internet of Things.

Download or read book Smart Manufacturing written by Masoud Soroush and published by Elsevier. This book was released on 2020-08-04 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research efforts in the past ten years have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Concepts and Methods puts these advances in perspective, showing how process industries can benefit from these new techniques. The book consolidates results developed by leading academic and industrial groups in the area, providing a systematic, comprehensive coverage of conceptual and methodological advances made to date. Written by leaders in the field from around the world, Smart Manufacturing: Concepts and Methods is essential reading for graduate students, researchers, process engineers, and managers. It is complemented by a companion book titled Smart Manufacturing: Applications and Case Studies, which covers the applications of smart manufacturing concepts and methods in process industries and beyond. Takes a process-systems engineering approach to design, monitoring, and control of smart manufacturing systems Brings together the key concepts and methods of smart manufacturing, including the advances made in the past decade Includes coverage of computation methods for process optimization, control, and safety, as well as advanced modelling techniques

Download or read book Handbook of Intelligent and Sustainable Manufacturing written by Ajay Kumar and published by CRC Press. This book was released on 2024-08-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent and sustainable manufacturing is a broad category of manufacturing that employs computer-integrated manufacturing, high levels of adaptability and rapid design changes, digital information technology, and more flexible technical workforce training. Other goals sometimes include fast changes in production levels based on demand, optimization of the production system, efficient production, and recyclability. This handbook provides compiled knowledge of intelligent and sustainable manufacturing within the context of Industry 4.0. along with tools, principles, and strategies. Handbook of Intelligent and Sustainable Manufacturing: Tools, Principles, and Strategies offers recent developments, future outlooks, and advanced and analytical modeling techniques of intelligent and sustainable manufacturing with examples backed up by experimental and numerical data. It bridges the gap between R&D in intelligent and sustainable manufacturing–related fields and presents case studies and solutions alongside social and green environmental impact. The handbook includes a wide range of advanced tools and applications with modeling results and explains how different internet technologies integrate the manufacturing approach with people, products, and complex systems. By encompassing advanced technologies such as digital twins, big data informatics, artificial intelligence, nature-inspired algorithms, IoT, Industry 4.0, simulation approaches, analytical strategies, quality tools, roots and pillars, diagnostic tools, and methodical strategies, this handbook provides the most up-to-date and advanced information source available. This handbook will help industries and organizations to implement intelligent manufacturing and move towards the sustainability of manufacturing practices. It will also serve as a reference for senior graduate-level courses in mechanical, production, industrial, and aerospace engineering and a value-added asset to libraries of all technical institutions.

Download or read book Smart Manufacturing written by Masoud Soroush and published by Elsevier. This book was released on 2020-08-04 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research efforts in the past decade have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Applications and Case Studies includes information about the key applications of these new methods, as well as practitioners’ accounts of real-life applications and case studies. Written by thought leaders in the field from around the world, Smart Manufacturing: Applications and Case Studies is essential reading for graduate students, researchers, process engineers and managers. It is complemented by a companion book titled Smart Manufacturing: Concepts and Methods, which describes smart manufacturing methods in detail. Includes examples of applications of smart manufacturing in process industries Provides a thorough overview of the subject and practical examples of applications through well researched case studies Offers insights and accounts of first-hand experiences to motivate further implementations of the key concepts of smart manufacturing

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 Advances in Production Management Systems The Path to Intelligent Collaborative and Sustainable Manufacturing written by Hermann Lödding and published by Springer. This book was released on 2017-08-29 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set IFIP AICT 513 and 514 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2017, held in Hamburg, Germany, in September 2017. The 121 revised full papers presented were carefully reviewed and selected from 163 submissions. They are organized in the following topical sections: smart manufacturing system characterization; product and asset life cycle management in smart factories of industry 4.0; cyber-physical (IIoT) technology deployments in smart manufacturing systems; multi-disciplinary collaboration in the development of smart product-service solutions; sustainable human integration in cyber-physical systems: the operator 4.0; intelligent diagnostics and maintenance solutions; operations planning, scheduling and control; supply chain design; production management in food supply chains; factory planning; industrial and other services; operations management in engineer-to-order manufacturing; gamification of complex systems design development; lean and green manufacturing; and eco-efficiency in manufacturing operations.

Download or read book Artificial Intelligence Enabled Digital Twin for Smart Manufacturing written by Amit Kumar Tyagi and published by John Wiley & Sons. This book was released on 2024-09-11 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin—an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system’s behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI’s capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals.

Download or read book Proceedings of the UNIfied Conference of DAMAS IncoME and TEPEN Conferences UNIfied 2023 written by Andrew D. Ball and published by Springer Nature. This book was released on with total page 1186 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Industrial AI written by Jay Lee and published by Springer Nature. This book was released on 2020-02-07 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.

Download or read book Artificial Intelligence for Smart Manufacturing written by Kim Phuc Tran and published by Springer Nature. This book was released on 2023-06-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI). As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios. Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.

Download or read book Industry 4 0 Managing The Digital Transformation written by Alp Ustundag and published by Springer. This book was released on 2017-09-14 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive guide to Industry 4.0 applications, not only introducing implementation aspects but also proposing a conceptual framework with respect to the design principles. In addition, it discusses the effects of Industry 4.0, which are reflected in new business models and workforce transformation. The book then examines the key technological advances that form the pillars of Industry 4.0 and explores their potential technical and economic benefits using examples of real-world applications. The changing dynamics of global production, such as more complex and automated processes, high-level competitiveness and emerging technologies, have paved the way for a new generation of goods, products and services. Moreover, manufacturers are increasingly realizing the value of the data that their processes and products generate. Such trends are transforming manufacturing industry to the next generation, namely Industry 4.0, which is based on the integration of information and communication technologies and industrial technology.The book provides a conceptual framework and roadmap for decision-makers for this transformation