Artificial Intelligence In Manufacturing Research

Artificial intelligence is a sub-field of computer science concerned with understanding the nature of intelligence and constructing computer systems capable of intelligent action. This book aims to provide the research and review studies on artificial intelligence in manufacturing.

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.

After the recent launch of home-based personal 3D printers as well as government funding and company investments in advancing manufacturing initiatives, additive manufacturing has rapidly come to the forefront of discussion and become a more approachable lucrative career of particular interest to the younger generation. It is essential to identify the long-term competitive advantages and how to teach, inspire, and create a resolute community of supporters, learners, and new leaders in this important industry progression. Applications of Artificial Intelligence in Additive Manufacturing provides instruction on how to use artificial intelligence to produce additively manufactured parts. It discusses an overview of the field, the strategic blending of artificial intelligence and additive manufacturing, and features case studies on the various emerging technologies. Covering topics such as artificial intelligence models, experimental investigations, and online detections, this book is an essential resource for engineers, manufacturing professionals, computer scientists, AI scientists, researchers, educators, academicians, and students.

"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. It establishes a milestone in understanding global transformational changes occurring in the manufacturing and corporate world due to AI and tries to find powerful and sophisticated solutions that will improve and streamline operations. Reinventing Manufacturing and Business Processes through Artificial Intelligence will be of interest to students, researchers, and professionals of the AI community as well as interdisciplinary researchers"--

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.

Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management addresses prominent concepts and applications of AI technologies in the management of networked manufacturing enterprises. The aim of this book is to align latest practices, innovation and case studies with academic frameworks and theories, where AI techniques are used efficiently for networked manufacturing enterprises. More specifically, it includes the latest research results and projects at different levels addressing quick-response system, theoretical performance analysis, performance and capability demonstration. The role of emerging AI technologies in the modelling, evaluation and optimisation of networked enterprises’ activities at different decision levels is also covered. Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management is a valuable guide for postgraduates and researchers in industrial engineering, computer science, automation and operations research.