Artificial Intelligence Applications in Manufacturing PDF Download

Author: A. Fazel Famili
Publisher: Menlo Press, Calif. : AAAI Press/MIT Press
ISBN:
Category : Computers
Languages : en
Pages : 486

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Book Description
The past decade has seen considerable advances in CAE tools that employ leading-edge artificial intelligence techniques and that can be used with CAD/CAM tools to reduce design costs. In three parts, this book covers current Al applications that can prove beneficial in the design and planning stages of manufacturing, that can assist in solving scheduling and control problems, and that can be used in manufacturing integration.A. F. Famili is Research Scientist at the Knowledge Systems Laboratory of the National Research Council of Canada. Steven H. Kim is Visiting Fellow at the Design Research Institute, Cornell University. Dana S. Nau an Associate Professor in the Computer Science Department at the University of Maryland.Contents: Application of Machine Learning to Industrial Planning and Decision Making. Incorporating Special Purpose Resource Design in Planning to Make More Efficient Plans. Geometric Reasoning Using a Feature Algebra. Backward Assembly Planning Symmetry Groups in Solid Model-Based Assembly Planning. An Expert System Approach for Economic Evaluation of Machining Operation Planning. Interactive Problem Solving for Production Planning. An Abstraction-Based Search and Learning Approach for Effective Scheduling. ADDYMS: Architecture for Distributed Dynamic Manufacturing Scheduling. An Architecture for Real Time Distributed Scheduling. Teamwork Among Intelligent Agents: Framework and Case Study in Robotic Service. Exploiting Local Flexibility During Execution of Precomputed Schedules. Symbolic Representation and Planning for Robot Control Systems in Manufacturing. An Architecture for Integrating Enterprise Automation. An Intelligent Agent Framework for Enterprise Integration. Integrated Software System for Intelligent Manufacturing. Enterprise Management Network Architecture: A Tool for Manufacturing Enterprise Integration. Design and Manufacturing: Integration through Quality.

Author: Greg Shaw
Publisher:
ISBN: 9780999750827
Category :
Languages : en
Pages :

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Book Description
The Future Computed: AI and Manufacturing is the next book in Microsoft's The Future Computed series looking at the impact of AI on society. The book features stories from industry leaders and policymakers from around the world, sharing insights into how customers can progress their AI journey. IT also sets out suggestions about how countries can build competitive manufacturing sectors while delivering AI and addressing short-term disruption.

Author: Geeta Rana
Publisher: CRC Press
ISBN: 9780367702106
Category : Business & Economics
Languages : en
Pages : 0

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Book Description
This book describes how newly emerging Artificial Intelligence (AI) technologies will provide unprecedented opportunities to penetrate technology and automation into everything we do, and at the same time, provide a huge playing field for businesses to develop newer models to capture market share.

Author: Alexiei Dingli
Publisher: Springer Nature
ISBN: 3030610454
Category : Technology & Engineering
Languages : en
Pages : 248

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Book Description
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.

Author: Sachin Salunkhe
Publisher: Engineering Science Reference
ISBN: 9781799885160
Category : Additive manufacturing
Languages : en
Pages : 272

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Book Description
"This book provides introductory instruction on how to learn how to use artificial intelligence to produce additively manufactured parts, including a description of the starting points, what you can know, how it blends and how artificial intelligence in additive manufacturing apply"--

Author: Aboul Ella Hassanien
Publisher: Academic Press
ISBN: 0323906397
Category : Technology & Engineering
Languages : en
Pages : 264

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Book Description
Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT. - Explores artificial intelligence applications within the industrial manufacturing and communications sectors - Presents a wide range of machine learning, computer vision, and digital twin applications across the IoT sector - Explores how deep learning and cognitive computing tools enable processing vast data sets, precise and comprehensive forecast of risks, and delivering recommended actions

Author: Sambit Kumar Mishra
Publisher: CRC Press
ISBN: 1000171892
Category : Technology & Engineering
Languages : en
Pages : 172

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Book Description
This book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology. This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing. The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.

Author: Karabegovi?, Isak
Publisher: IGI Global
ISBN: 1799827267
Category : Business & Economics
Languages : en
Pages : 661

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Book Description
In Industry 4.0, industrial productions are adjusted to complete smart automation, which means introducing self-automation methods, self-configuration, self-diagnosis of problems and removal, cognition, and intelligent decision making. This implementation of Industry 4.0 brings about a change in business paradigms and production models, and this will be reflected at all levels of the production process including supply chains and will involve all workers in the production process from managers to cyber-physical systems designers and customers as end-users. The Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing is an essential reference source that explores the development and integration of Industry 4.0 by examining changes and innovations to manufacturing processes as well as its applications in different industrial areas. Featuring coverage on a wide range of topics such as cyber physical systems, integration criteria, and artificial intelligence, this book is ideally designed for mechanical engineers, electrical engineers, manufacturers, supply chain managers, logistics specialists, investors, managers, policymakers, production scientists, researchers, academicians, and students at the postgraduate level.

Author: Ovidiu Vermesan
Publisher: CRC Press
ISBN: 1000794318
Category : Medical
Languages : en
Pages : 435

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Book Description
This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

Author: Shubhabrata Datta
Publisher: Springer Nature
ISBN: 3030758478
Category : Technology & Engineering
Languages : en
Pages : 202

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Book Description
This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.