Download Free Artificial Intelligence Aided Processing Of Sustainable Composite Polymers Book in PDF and EPUB Free Download. You can read online Artificial Intelligence Aided Processing Of Sustainable Composite Polymers and write the review.

"The superior multi-functional properties of polymer composites have made them a suitable candidate for biomedical, defense, automobile, agriculture, and domestic applications. The growing demand for these composites calls for an extensive investigation of their physical, chemical, and mechanical behaviour under different exposure conditions. Characterization techniques are very vital considering the extensive investigation. The criticality and consideration of several parameters for the characterization make this investigation more complex. The self-learning ability of machine learning algorithms makes this investigation more accurate and accommodates all the complex requirements. The recent development in neural codes can accommodate the data in all the forms such as numerical values as well as images. The aim of the Research Topic is to address the design, characterization, and development of prediction analysis of sustainable polymer composites using machine learning algorithms. This topic encourages the development of sustainable polymer composites using machine learning algorithms before manufacturing them. Recent development AI & ML techniques help in the development of sustainable development polymers. This research topic also encourages the development of AI & ML technique for effective characterization based on the research data available for different polymers. Considering the capability of AI&ML techniques, various properties such as physical, mechanical, chemical, thermal, and electrical can be predicted for desired sustainable polymer composite. This research topic also provides the scope of possible combinations of reinforcement in the polymer with the ability to predict the life span of the composite, energy appropriation using local density, manufacturing optimization, phase diagrams, precision machining, micrograph analysis, and damage assessment"--
The self-learning ability of machine learning algorithms makes the investigations more accurate and accommodates all the complex requirements. Development in neural codes can accommodate the data in all the forms such as numerical values as well as images. The techniques also review the sustainability, life-span, the energy consumption in production polymer, etc. This book addresses the design, characterization, and development of prediction analysis of sustainable polymer composites using machine learning algorithms.
The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods. Focusses on machine learning applications in Industry 4.0 ecosystem, such as resource optimization, data analysis, and predictions. Highlights the importance of the explainable machine learning model in the manufacturing processes. Presents the integration of machine learning and big data analytics from an industry 4.0 perspective. Discusses advanced computational techniques for sustainable manufacturing. Examines environmental impacts of operations and supply chain from an industry 4.0 perspective. This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.
This book provides the latest technical information on sustainable materials that are feedstocks for additive manufacturing (AM). Topics covered include an up-to-date and extensive overview of raw materials, their chemistry, and functional properties of their commercial versions; a description of the relevant AM processes, products, applications, advantages, and limitations; prices and market data; and a forecast of sustainable materials used in AM, their properties, and applications in the near future. Data included are relative to current commercial products and are presented in easy-to-read tables and charts. Features Highlights up-to-date information and data of actual commercial materials Offers a broad survey of state-of the-art information Forecasts future materials, applications, and areas of R&D Contains simple language, explains technical terms, and minimizes technical lingo Includes over 200 tables, nearly 200 figures, and more than 1,700 references to technical publications, mostly very recent Handbook of Sustainable Polymers for Additive Manufacturing appeals to a diverse audience of students and academic, technical, and business professionals in the fields of materials science and mechanical, chemical, and manufacturing engineering.
Supplying nearly 350 expertly-written articles on technologies that can maximize and enhance the research and production phases of current and emerging chemical manufacturing practices and techniques, this second edition provides gold standard articles on the methods, practices, products, and standards recently influencing the chemical industries. New material includes: design of key unit operations involved with chemical processes; design, unit operation, and integration of reactors and separation systems; process system peripherals such as pumps, valves, and controllers; analytical techniques and equipment; current industry practices; and pilot plant design and scale-up criteria.
This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.
This second edition Encyclopedia supplies nearly 350 gold standard articles on the methods, practices, products, and standards influencing the chemical industries. It offers expertly written articles on technologies at the forefront of the field to maximize and enhance the research and production phases of current and emerging chemical manufacturing practices and techniques. This collecting of information is of vital interest to chemical, polymer, electrical, mechanical, and civil engineers, as well as chemists and chemical researchers. A complete reconceptualization of the classic reference series the Encyclopedia of Chemical Processing and Design, whose first volume published in 1976, this resource offers extensive A-Z treatment of the subject in five simultaneously published volumes, with comprehensive indexing of all five volumes in the back matter of each tome. It includes material on the design of key unit operations involved with chemical processes; the design, unit operation, and integration of reactors and separation systems; process system peripherals such as pumps, valves, and controllers; analytical techniques and equipment; and pilot plant design and scale-up criteria. This reference contains well-researched sections on automation, equipment, design and simulation, reliability and maintenance, separations technologies, and energy and environmental issues. Authoritative contributions cover chemical processing equipment, engineered systems, and laboratory apparatus currently utilized in the field. It also presents expert overviews on key engineering science topics in property predictions, measurements and analysis, novel materials and devices, and emerging chemical fields. ALSO AVAILABLE ONLINE This Taylor & Francis encyclopedia is also available through online subscription, offering a variety of extra benefits for both researchers, students, and librarians, including: Citation tracking and alerts Active reference linking Saved searches and marked lists HTML and PDF format options Contact Taylor and Francis for more information or to inquire about subscription options and print/online combination packages. US: (Tel) 1.888.318.2367; (E-mail) [email protected] International: (Tel) +44 (0) 20 7017 6062; (E-mail) [email protected]
Computer aided process engineering (CAPE) tools have been very successfully used in process design and product engineering for a long time. In particular, simulation and modelling tools have enabled engineers to analyse and understand the behaviour of selected processes prior to building actual plants. The aim of design or retrofit of chemical processes is to produce profitably products that satisfy the societal needs, ensuring safe and reliable operation of each process, as well as minimising any effects on the environment. This involves the conceptual design or retrofit of plants and processes, novel manufacturing approaches, process/control system design interactions and operability, manufacturability, environmental and safety issues. Backed by current studies, this 2-volume set gives a comprehensive survey of the various approaches and latest developments on the use of CAPE in the process industry. An invaluable reference to the scientific and industrial community in the field of computer aided process and product engineering.
In today's context of intricate global challenges, encompassing climate crises, resource scarcity, and social disparities, the imperative for sustainable development has never been more pressing. While academic scholars and researchers are instrumental in crafting solutions, they often grapple with the intricate balance between theoretical concepts and practical implementation. This gap impedes the transformation of innovative ideas into tangible societal progress, leaving a void where effective real-world strategies for cross-industry sustainability should flourish. "Fostering Cross-Industry Sustainability With Intelligent Technologies" seeks to bridge this divide. This book is more than just a collection of pages; it serves as a roadmap for those determined to make a tangible impact. It brings together a diverse group of esteemed experts from various disciplines, offering a comprehensive spectrum of actionable insights, all grounded in the ethical imperatives of inclusivity and environmental responsibility. Anchored in the United Nations Sustainable Development Goals (SDGs), this volume serves as a guiding star, channeling theoretical expertise into practical solutions. For academic scholars, scientists, innovators, and students alike, Fostering Cross-Industry Sustainability With Intelligent Technologies is the definitive guidepost. It fosters a profound understanding of the real-world implications of research, promoting interdisciplinary collaborations that transcend conventional boundaries. This comprehensive book presents a wealth of sustainable science and intelligent technology applications, all while emphasizing the importance of ethics and societal impact. With visionary insights woven throughout its pages, it calls upon humanity to envision a future where challenges transform into opportunities, and sustainable development becomes an attainable reality.
The book highlights the role of artificial intelligence in driving innovation, productivity, and efficiency. It further covers applications of artificial intelligence for digital marketing in Industry 5.0 and discusses data security and privacy issues in artificial intelligence, risk assessments, and identification strategies. This book: Discusses the role of artificial intelligence applications for digital manufacturing in Industry 5.0 Presents blockchain methods and data-driven decision-making with autonomous transportation Covers reinforcement learning algorithm and highly predicted models for accurate data analysis in industry automation Highlights the importance of robust authentication mechanisms and access control policies to protect sensitive information, prevent unauthorized access, and enable secure interactions between humans and machines Explains attack pattern detection and prediction which play a crucial role in ensuring the security of business systems and networks It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, industrial engineering, manufacturing engineering, and production engineering.