Download or read book Big Data Analytics in Smart Manufacturing written by P Suresh and published by CRC Press. This book was released on 2022-12-14 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners

Download or read book Data Driven Smart Manufacturing Technologies and Applications written by Weidong Li and published by Springer Nature. This book was released on 2021-02-20 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.

Download or read book Predictive Analytics for Smart Manufacturing written by Hyunsoo Jeong and published by . This book was released on 2016 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: The manufacturing industry has, recently, been facing tremendous challenges, including cost efficiency, system safety, and process automation, and manufacturing companies are required to adopt new technologies to keep themselves sustainable in the fast-changing world of technology. This research focuses, in particular, on how to prevent cutting tool failures and catastrophic accidents in Computerized Numerically Controlled (CNC) machining processes by using a predictive model based on the cutting sound data. With advances in machine learning algorithms and predictive analytics techniques, it becomes possible to create a noise-robust predictive model from an unstructured dataset of sound data. It is an obviously desirable decision to make use of every technology as required and benefit from it. The predictive model introduced in this research uses cutting sound data rather than acoustic emission or force/torque sensor data, which have been widely used for machine failure detection but have shown some limitations. The model is an important stepping stone for realizing an unmanned and fully automated manufacturing system, the so-called "smart factory," and it would be a meaningful movement for the government side as well, taking into account government's responsibility to keep people safe in the workplace. In this research, several experiments were carried out to collect sound data in the CNC machining center in Korea, and particular features were extracted from the analog waveform signals, using the unstructured data to make the predictive model using various advanced data analytics techniques and cutting-edge machine learning algorithms. Then, several analysis methods with systems thinking were used to explore potential impacts of the predictive model on the manufacturing system because the systems thinking approach is the most effective way to analyze a wide range of potential impacts from a holistic perspective. Specifically, the impact analysis was successfully conducted by using a "Causal Analysis based on STAMP (CAST)," which is a system safety analysis method. Also used was "system dynamics modeling," which is generally employed to identify dynamic behaviors in a complex system. Finally, a "complete value template" was constructed to portray how the new system delivers value to its stakeholders from a system architecture perspective.

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 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 Model based Predictive Analytics for Additive and Smart Manufacturing written by Zhuo Yang and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Qualification and certification for additive and smart manufacturing systems can be uncertain and very costly. Using available historical data can mitigate some costs of producing and testing sample parts. However, use of such data lacks the flexibility to represent specific new problems which decreases predictive accuracy and efficiency. To address these compelling needs, in this dissertation modeling techniques are introduced that can proactively estimate results expected from additive and smart manufacturing processes swiftly and with practical levels of accuracy and reliability. More specifically, this research addresses the current challenges and limitations posed by use of available data and the high costs of new data by tailoring statistics-based metamodeling techniques to enable affordable prediction of these systems. The result is an integrated approach to customize and build predictive metamodels for the unique features of additive and smart manufacturing systems. This integrated approach is composed of five main parts that cover the broad spectrum of requirements. A domain-driven metamodeling approach uses physics-based knowledge to optimally select the most appropriate metamodeling algorithm without reliance upon statistical data. A maximum predictive error updating method iteratively improves predictability from a given dataset. A grey-box metamodeling approach combines statistics-based black-box and physics-based white-box models to significantly increase predictive accuracy with less expensive data overall. To improve computational efficiency for large datasets, a dynamic metamodeling method modifies the traditional Kriging technique to improve its efficiency and predictability for smart manufacturing systems. Finally, a super-metamodeling method optimizes results regardless of problem conditions by avoiding the challenge with selecting the most appropriate metamodeling algorithm. To realize the benefits of all five approaches, an integrated metamodeling process was developed and implemented into a tool package to systematically select the suitable algorithm, sampling method, and combination of models. All the functions of this tool package were validated and demonstrated by the use of two empirical datasets from additive manufacturing processes.

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 Smart Manufacturing written by Anthony Tarantino and published by John Wiley & Sons. This book was released on 2022-05-10 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the dramatic changes brought on by the new manufacturing technologies of Industry 4.0 In Smart Manufacturing, The Lean Six Sigma Way, Dr. Anthony Tarantino delivers an insightful and eye-opening exploration of the ways the Fourth Industrial Revolution is dramatically changing the way we manufacture products across the world and especially how it will revitalize manufacturing in North America and Europe. The author examines the role and impact of a variety of new Smart technologies including industrial IoT, computer vision, mobile/edge computing, 3D printing, robots, big data analytics, and the cloud. He demonstrates how to apply these new technologies to over 20 continuous improvement/Lean Six Sigma tools, greatly enhancing their effectiveness and ease of use. The book also discusses the role Smart technologies will play in improving: Career opportunities for women in manufacturing Cyber security, supply chain risk, and logistics resiliency Workplace health, safety, and security Life on the manufacturing floor Operational efficiencies and customer satisfaction Perfect for anyone involved in the manufacturing or distribution of products in the 21st century, Smart Manufacturing, The Lean Six Sigma Way belongs in the libraries of anyone interested in the intersection of technology, commerce, and physical manufacturing.

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 Real Time Optimization written by Dominique Bonvin and published by MDPI. This book was released on 2018-07-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Real-Time Optimization" that was published in Processes

Download or read book Digital Twins written by Yogini Borole and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-09-18 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Research in Intelligent and Computing in Engineering written by Raghvendra Kumar and published by Springer Nature. This book was released on 2021-01-04 with total page 975 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises select peer-reviewed proceedings of the international conference on Research in Intelligent and Computing in Engineering (RICE 2020) held at Thu Dau Mot University, Vietnam. The volume primarily focuses on latest research and advances in various computing models such as centralized, distributed, cluster, grid, and cloud computing. Practical examples and real-life applications of wireless sensor networks, mobile ad hoc networks, and internet of things, data mining and machine learning are also covered in the book. The contents aim to enable researchers and professionals to tackle the rapidly growing needs of network applications and the various complexities associated with them.

Download or read book Machine Learning Algorithms for Industrial Applications written by Santosh Kumar Das and published by Springer Nature. This book was released on 2020-07-18 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.

Download or read book Guide to Industrial Analytics written by Richard Hill and published by Springer Nature. This book was released on 2021-09-27 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.

Download or read book Advanced Information Systems Engineering Workshops written by Sophie Dupuy-Chessa and published by Springer Nature. This book was released on 2020-05-15 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the international workshops associated with the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, which was planned to take place in Grenoble, France, during June 8-12, 2020. Due to the Coronavirus pandemic the conference was held virtually. The workshops included in this book are: KET4DF, The Second International Workshop on Key Enabling Technologies for Digital Factories ISESL, The First International Workshop on Information Systems Engineering for Smarter Life The total of 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The book also contains one invited talk.

Download or read book Industry 4 0 Data Analytics written by Rajesh Agnihotri and published by Createspace Independent Publishing Platform. This book was released on 2016-07-31 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global supply chains are entering an exciting era driven by technological innovation. Buzzwords like Big Data Analytics, IoT, Smart Manufacturing, Smart Logistics and Industries 4.0 are generating both interest and confusion in the business community. This book's comprehensive, one-of-a-kind coverage, journeys from the birth of digital data during Industries 3.0, to the latest practices, trends, and emerging developments in Industries 4.0. The balanced approach of the book follows the natural flow of supply chain processes and provides a deeper insight into the role data analytics plays in streamlining today's business models. Well-organized chapters demonstrate the practical applications of data analytics in today's supply chain workplace, and provide a wealth of real-world business examples. The book provides a step-by-step approach to building your own data analytics strategy.

Download or read book Intelligent Manufacturing Systems written by Andrew Kusiak and published by Prentice Hall. This book was released on 1990 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Defining structure and functions of knowledge-based systems, this book presents hardware and software components of flexible machining, flexible assembly and computer-integrated manufacturing systems. Discussed are such areas as process planning, group technology and lay-out design.