Artificial Intelligence in Industrial Applications

Artificial Intelligence in Industrial Applications PDF

Author: Steven Lawrence Fernandes

Publisher: Springer Nature

Published: 2021-12-07

Total Pages: 203

ISBN-13: 3030853837

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This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence.

Artificial Intelligence and Industrial Applications

Artificial Intelligence and Industrial Applications PDF

Author: Tawfik Masrour

Publisher: Springer Nature

Published: 2020-07-18

Total Pages: 341

ISBN-13: 3030539709

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This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.

Artificial Intelligence and Industrial Applications

Artificial Intelligence and Industrial Applications PDF

Author: Tawfik Masrour

Publisher: Springer Nature

Published: 2023-10-16

Total Pages: 318

ISBN-13: 3031435249

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Amid the dynamic growth of artificial intelligence, this book presents a collection of findings and advancements from the second edition of the A2IA-Artificial Intelligence and Industrial Applications conference. The conference, hosted by ENSAM-Meknès at Moulay Ismail University, Morocco, fosters knowledge exchange in AI, focusing primarily on its industrial applications. Covering a wide range of topics, the book highlights the adaptable nature of AI and its increasing impact on industrial sectors. It brings together contributions from an international cohort of researchers, discussing themes such as intelligent manufacturing and maintenance, intelligent supply chain management, various modes of learning including supervised, unsupervised, reinforcement, semi-supervised, and graph-based, as well as neural networks, deep learning, planning, and optimization. A defining feature of this edition is its extensive scope and emphasis on the practical applications of AI, along with its foundational elements. It facilitates an understanding of AI's current state and potential future direction, showcasing recent developments that bridge the gap between theory and practice. Designed for a diverse readership, this book is of interest to AI practitioners, academics, and enthusiasts, as well as to those new to the field. It provides an opportunity to explore AI's critical role in industrial applications, and the practical insights it offers are likely to be beneficial for decision-making within industrial settings.

AI and Learning Systems

AI and Learning Systems PDF

Author: Konstantinos Kyprianidis

Publisher: BoD – Books on Demand

Published: 2021-02-17

Total Pages: 274

ISBN-13: 1789858771

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Over the last few years, interest in the industrial applications of AI and learning systems has surged. This book covers the recent developments and provides a broad perspective of the key challenges that characterize the field of Industry 4.0 with a focus on applications of AI. The target audience for this book includes engineers involved in automation system design, operational planning, and decision support. Computer science practitioners and industrial automation platform developers will also benefit from the timely and accurate information provided in this work. The book is organized into two main sections comprising 12 chapters overall: •Digital Platforms and Learning Systems •Industrial Applications of AI

Machine Learning Algorithms for Industrial Applications

Machine Learning Algorithms for Industrial Applications PDF

Author: Santosh Kumar Das

Publisher: Springer Nature

Published: 2020-07-18

Total Pages: 321

ISBN-13: 303050641X

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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.

Machine Learning and Artificial Intelligence with Industrial Applications

Machine Learning and Artificial Intelligence with Industrial Applications PDF

Author: Diego Carou

Publisher: Springer Nature

Published: 2022-03-11

Total Pages: 216

ISBN-13: 3030910067

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This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.

Artificial Intelligence Applications in Manufacturing

Artificial Intelligence Applications in Manufacturing PDF

Author: A. Fazel Famili

Publisher: Menlo Press, Calif. : AAAI Press/MIT Press

Published: 1992

Total Pages: 486

ISBN-13:

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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.

Artificial Intelligence for Digitising Industry – Applications

Artificial Intelligence for Digitising Industry – Applications PDF

Author: Ovidiu Vermesan

Publisher: CRC Press

Published: 2022-09-01

Total Pages: 435

ISBN-13: 1000794318

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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.

Artificial Intelligence and Industrial Applications

Artificial Intelligence and Industrial Applications PDF

Author: A. Leung

Publisher:

Published: 2015

Total Pages: 0

ISBN-13: 9781784660529

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The papers presented in this book are from the 2014 International Conference on Artificial Intelligence and Industrial Application (AIIA). The work shared at AIIA 2014 explored views and ideas on current issues emerging in the field of artificial intelligence. The contents of the book are organised in 7 topics groups: Artificial Intelligence and Application, including AI and the Web; Cognitive Systems and Game Playing and Interactive Entertainment; Industrial Engineering and Applications, Software Process, Communication Technology, Network and Information Security, Data Mining and Knowledge-based Systems, which discussed areas such as Mechatronics; Multimedia & Cognitive Informatics, Recent Trends and Developments and Web Intelligence Applications & Search.