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Books > Professional & Technical > Mechanical engineering & materials > Production engineering > General
This book includes best selected, high-quality research papers presented at the International Conference on Intelligent Manufacturing and Energy Sustainability (ICIMES 2020) held at the Department of Mechanical Engineering, Malla Reddy College of Engineering & Technology (MRCET), Maisammaguda, Hyderabad, India, during August 21-22, 2020. It covers topics in the areas of automation, manufacturing technology and energy sustainability and also includes original works in the intelligent systems, manufacturing, mechanical, electrical, aeronautical, materials, automobile, bioenergy and energy sustainability.
This book relates research being implemented in three main research areas: secure connectivity and intelligent systems, real-time analytics and manufacturing knowledge and virtual manufacturing. Manufacturing SMEs and MNCs want to see how Industry 4.0 is implemented. On the other hand, groundbreaking research on this topic is constantly growing. For the aforesaid reason, the Singapore Agency for Science, Technology and Research (A*STAR), has created the model factory initiative. In the model factory, manufacturers, technology providers and the broader industry can (i) learn how I4.0 technologies are implemented on real-world manufacturing use-cases, (ii) test process improvements enabled by such technologies at the model factory facility, without disrupting their own operations, (iii) co-develop technology solutions and (iv) support the adoption of solutions at their everyday industrial operation. The book constitutes a clear base ground not only for inspiration of researchers, but also for companies who will want to adopt smart manufacturing approaches coming from Industry 4.0 in their pathway to digitization.
This book introduces the metal magnetic memory (MMM) technique, one of the nondestructive testing methods, and its applications in remanufacturing engineering. It discusses the advantages of MMM and how to evaluate the early damage degree of remanufacturing cores, as well as the repairing quality of remanufactured components. Various MMM signal characteristics are extracted to reflect the damage degree of remanufacturing cores, coatings and interfaces. All the theoretical models, analysis methods and testing results of MMM in this book provide guidance to control the quality of remanufactured parts and products. This book can help readers make the best use of the MMM technique in remanufacturing engineering.
This book reports on innovative research and developments in automation. Spanning a wide range of disciplines, including communication engineering, power engineering, control engineering, instrumentation, signal processing and cybersecurity, it focuses on methods and findings aimed at improving the control and monitoring of industrial and manufacturing processes as well as safety. Based on the International Russian Automation Conference, held on September 6-12, 2020, in Sochi, Russia, the book provides academics and professionals with a timely overview of and extensive information on the state of the art in the field of automation and control systems, and fosters new ideas and collaborations between groups in different countries.
This book presents the latest advances in manufacturing from both the experimental and simulation point of view. It covers most aspects of manufacturing engineering, i.e. theoretical, analytical, computational and experimental studies. Experimental studies on manufacturing processes require funds, time and expensive facilities, while numerical simulations and mathematical models can improve the efficiency of using the research results. It also provides high level of prediction accuracy and the basis for novel research directions.
This book systematically describes the weld pool behavior in laser welding and its influencing factors from the perspectives of testing technology, theoretical calculation and process simulation technology, physical state transformation behavior of weld pools, and the impact of technical conditions on the weld pool behavior. The book covers extensive research achievements made in China in this field, some of which represent the latest cutting-edging researches conducted by the authors' research team. These latest research efforts mainly relate to the weld pool behavior of dual-beam laser welding, laser welding with filler wires, full-penetration laser welding of very-thick parts, and laser welding in vacuum and low vacuum conditions. The book is intended for undergraduate, graduate students and researchers who are interested in laser welding.
This book is the first monograph focusing on ellipsoidal heads, which are commonly used as an end closure of pressure vessels in chemical, petroleum, nuclear, marine, aerospace and food processing industries. It provides a comprehensive coverage of stress, failure, design and fabrication of ellipsoidal heads. This book investigates in detail buckling/plastic collapse behaviors of ellipsoidal heads using nonlinear finite element methods and experiments. Buckling/plastic collapse experiments are performed on 37 ellipsoidal heads which cover various geometric parameters, material and fabrication methods. In particular, modern measurement technologies, such as 3D laser scanning, are used in the experiments of these ellipsoidal heads including large heads with a diameter up to 5 metres. Moreover, this book presents new formulas for accurate prediction of buckling/plastic collapse pressures of ellipsoidal heads. Using elastic-plastic theory, this book proposes a new failure mechanism-based method for design of ellipsoidal heads. Compared to other methods in current codes and standards based on elastic or perfectly plastic theory, the new design method can fully develop the head's load-carrying capacity, which reduces head thickness and thus cost. Also, this book studies control on fabrication quality of ellipsoidal heads, including shape deviation, forming strain and forming temperature. It is useful as a technical reference for researchers and engineers in the fields of engineering mechanics, engineering design, manufacturing engineering and industrial engineering.
This book comprises the proceedings of the conference "Future Production of Hybrid Structures 2020", which took place in Wolfsburg. The conference focused on hybrid lightweight design, which is characterized by the combination of different materials with the aim of improving properties and reducing weight. In particular, production technologies for hybrid lightweight design were discussed, new evaluation methods for the ecological assessment of hybrid components were presented and future-oriented approaches motivated by nature for the development of components, assemblies and systems were introduced. Lightweight design is a key technology for the development of sustainable and resource-efficient mobility concepts. Vehicle manufacturers operate in an area of conflict between customer requirements, competition and legislation. Material hybrid structures, which combine the advantages of different materials, have a high potential for reducing weight, while simultaneously expanding component functionality. The future, efficient use of function-integrated hybrid structures in vehicle design requires innovations and constant developments in vehicle and production technology. There is a great demand, especially with regard to new methods and technologies, for "affordable" lightweight construction in large-scale production, taking into account the increasing requirements with regard to variant diversity, safety and quality.
This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.
This book provides discussions and the exchange of information on principles, strategies, models, techniques, methodologies and applications of industrial engineering. It communicates the latest developments and research activity on industrial engineering and is useful for all those interested in the technological challenges in the field.
The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: * Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. * Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. * Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. * Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. * Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. * Discusses a systematic and exhaustive analysis of intelligent software effort estimation models. It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
This book comprises select papers presented at the Conference on Innovative Product Design and Intelligent Manufacturing System (IPDIMS 2020). The book discusses the latest methods and advanced tools from different areas of design and manufacturing technology. The main topics covered include design methodologies, industry 4.0, smart manufacturing, and advances in robotics among others. The contents of this book are useful for academics as well as professionals working in the areas of industrial design, mechatronics, robotics, and automation.
This book presents part of the proceedings of the Manufacturing and Materials track of the iM3F 2020 conference held in Malaysia. This collection of articles deliberates on the key challenges and trends related to manufacturing as well as materials engineering and technology in setting the stage for the world in embracing the fourth industrial revolution. It presents recent findings with regards to manufacturing and materials that are pertinent towards the realizations and ultimately the embodiment of Industry 4.0, with contributions from both industry and academia.
This collection honoring Professor Jiann-Yang Hwang focuses on characterization and processing development in minerals, metals, and materials. Topics include but are not limited to:* Characterization methodology of minerals, metals, and materials * Microwave-assisted material processes * Recycling and reuse of metallurgical byproducts * Materials for hydrogen storage * Wastewater treatment and environmental protection * Natural materials for value-added applications * Principles and interactions of material characterization and manufacturing processing
This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy.
This book offers an introduction to various models and methods for green supplier evaluation and selection (GSES) within different information settings. As such, it provides valuable knowledge, useful GSES methods and practical examples that can be considered by manufacturers in selecting appropriate green suppliers to improve their environmental performance and customer satisfaction. This book is useful for practitioners and researchers working in the fields of supply chain management, operation management, information science, industrial engineering, and management science. It is also useful as a textbook for postgraduate and senior undergraduate students.
This book presents the characteristics and benefits industrial organizations can reap from the Industrial Internet of Things (IIoT). These characteristics and benefits include enhanced competitiveness, increased proactive decision-making, improved creativity and innovation, augmented job creation, heightened agility to respond to continuously changing challenges, and intensified data-driven decision making. In a straightforward fashion, the book also helps readers understand complex concepts that are core to IIoT enterprises, such as Big Data, analytic architecture platforms, machine learning (ML) and data science algorithms, and the power of visualization to enrich the domains experts' decision making. The book also guides the reader on how to think about ways to define new business paradigms that the IIoT facilitates, as well how to increase the probability of success in managing analytic projects that are the core engine of decision-making in the IIoT enterprise. The book starts by defining an IIoT enterprise and the framework used to efficiently operate. A description of the concepts of industrial analytics, which is a major engine for decision making in the IIoT enterprise, is provided. It then discusses how data and machine learning (ML) play an important role in increasing the competitiveness of industrial enterprises that operate using the IIoT technology and business concepts. Real world examples of data driven IIoT enterprises and various business models are presented and a discussion on how the use of ML and data science help address complex decision-making problems and generate new job opportunities. The book presents in an easy-to-understand manner how ML algorithms work and operate on data generated in the IIoT enterprise. Useful for any industry professional interested in advanced industrial software applications, including business managers and professionals interested in how data analytics can help industries and to develop innovative business solutions, as well as data and computer scientists who wish to bridge the analytics and computer science fields with the industrial world, and project managers interested in managing advanced analytic projects.
This book provides an insight into the welding techniques with a cross-disciplinary treatment to address the shortcomings of contemporary learning of welding terminology. Various topics covered include introduction to welding processes, design requirements, prominence of design, case studies presenting structural defacements due to inappropriate design, comprehensive surveys on welding processes selected from various process categories, design calculations to be adopted for specific applications and sample calculations. This book is useful for researchers, engineers and professionals working on welding equipment and technologies.
The scientific theme of the book concerns "Manufacturing as a Service (MaaS)" which is developed in a layered cloud networked manufacturing perspective, from the shop floor resource sharing model to the virtual enterprise collaborative model, by distributing the cost of the manufacturing infrastructure - equipment, software, maintenance, networking - across all customers. MaaS is approached in terms of new models of service-oriented, knowledge-based manufacturing systems optimized and reality-aware, that deliver value to customer and manufacturer via Big data analytics, Internet of Things communications, Machine learning and Digital twins embedded in Cyber-Physical System frameworks. From product design to after-sales services, MaaS relies on the servitization of manufacturing operations such as: Design as a Service, Predict as a Service or Maintain as a service. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book's readership is comprised by researchers and engineers working in the manufacturing value chain area who develop and use digital control solutions in the 'Industry of the Future' vision. The book also addresses to master and Ph.D. students enrolled in Engineering Sciences programs.
This book is intended to help management and other interested parties such as engineers, to understand the state of the art when it comes to the intersection between AI and Industry 4.0 and get them to realise the huge possibilities which can be unleashed by the intersection of these two fields. We have heard a lot about Industry 4.0, but most of the time, it focuses mainly on automation. In this book, the authors are going a step further by exploring advanced applications of Artificial Intelligence (AI) techniques, ranging from the use of deep learning algorithms in order to make predictions, up to an implementation of a full-blown Digital Triplet system. The scope of the book is to showcase what is currently brewing in the labs with the hope of migrating these technologies towards the factory floors. Chairpersons and CEOs must read these papers if they want to stay at the forefront of the game, ahead of their competition, while also saving huge sums of money in the process.
This book comprises the select proceedings of the 2nd International Conference on Future Learning Aspects of Mechanical Engineering (FLAME) 2020. In particular, this volume discusses different topics of industrial and production engineering such as sustainable manufacturing processes, logistics, Industry 4.0 practices, circular economy, lean six sigma, agile manufacturing, additive manufacturing, IoT and Big Data in manufacturing, 3D printing, simulation, manufacturing management and automation, surface roughness, multi-objective optimization and modelling for production processes, developments in casting, welding, machining, and machine tools. The contents of this book will be useful for researchers as well as industry professionals.
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.
This volume gathers the latest advances, innovations, and applications in the field of structural health monitoring (SHM) and more broadly in the fields of smart materials and intelligent systems. The volume covers highly diverse topics, including signal processing, smart sensors, autonomous systems, remote sensing and support, UAV platforms for SHM, Internet of Things, Industry 4.0, and SHM for civil structures and infrastructures. The contributions, which are published after a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists. The contents of this volume reflect the outcomes of the activities of EWSHM (European Workshop on Structural Health Monitoring) in 2020.
This book includes the introduction of emerging manufacturing technologies and planning cases with established technologies. The planning of eco-efficient process chains is crucial for manufacturing companies. However, in the state-of-the-art planning, various barriers exist towards the integration of the environmental dimension. Against this background, a concept for the integration of classic lean and environmental criteria into the three planning phases of process chains is presented. During concept planning, the Technology Assessment Tool supports planners in the identification of eco-efficient technologies. During rough planning, the Value Stream Design Tool enables the derivation of a production line based on workpiece characteristics. For detailed planning, tools for eco-efficient machine and process chain configuration are provided. Three case studies from large-scale automotive component manufacturing with established and emerging technologies demonstrate the tool applicability.
This edited book presents scientific results of the International Semi-Virtual Workshop on Data Science and Digital Transformation in the Fourth Industrial Revolution (DSDT 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference's most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science. |
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