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| artificial intelligence in mechanical design: Artificial Intelligence in Mechanical and Industrial Engineering Kaushik Kumar, Divya Zindani, J. Paulo Davim, 2021-06-20 Artificial Intelligence in Mechanical and Industrial Engineering offers a unified platform for the dissemination of basic and applied knowledge on the integration of artificial intelligence within the realm of mechanical and industrial engineering. The book covers the tools and information needed to build successful careers and a source of knowledge for those working with AI within these domains. The book offers a systematic approach to explicate fundamentals as well as recent advances. It incorporates various case studies for major topics as well as numerous examples. It will also include real-time intelligent automation and associated supporting methodologies and techniques, and cover decision-support systems, as well as applications of Chaos Theory and Fractals. The book will give scientists, researchers, instructors, students, and practitioners the tools and information needed to build successful careers and to be an impetus to advancements in next-generation mechanical and industrial engineering domains. |
| artificial intelligence in mechanical design: Artificial Intelligence in Engineering Design Bozzano G Luisa, 2012-12-02 Artificial Intelligence in Engineering Design is a three-volume edited collection of key papers from the field of AI and design, aimed at providing a state-of-the art description of the field, and focusing on how ideas and methods from artificial intelligence can help engineers in the design of physical artifacts and processes. The books survey a wide variety of applications in the areas of civil, chemical, electrical, computer, VLSI, and mechanical engineering. |
| artificial intelligence in mechanical design: Design Representation Gabriela Goldschmidt, William L. Porter, 2007-05-28 ...there is a global network of academics, researchers and methodologists who will buy this book or want it in their institute libraries.” Prof. John Harbraken As the field of human computer interaction grows, this book is likely to be a basic resource.” Prof. Chuck Eastman Design representation is necessary for all design activity. You will gain a guide to both theory and practical application in this discussion of representation as it occurs during the process of design. Goldschmidt and Porter give you perspectives on representational issues in design that are both informative and evocative of further inquiry. The unique interdisciplinary approach brings a new dimension to the study of representation, benefiting the global network of researchers, students and practitioners in all areas of design. Rather than addressing the larger framework directly, a series of smaller case studies are presented, each dealing with aspects of representation in architecture and engineering. Binding together historical-cultural, cognitive-social and technological perspectives eliminates the need for further reading. Innovative research methods based on numerous well-illustrated examples will leave you with new ideas to build on. International contributors focus on worldwide research activities, offering you more than just an expansion of a single viewpoint. Design Representation delves into the common roots of representation in all design disciplines through case studies, historical investigations, theoretical constructs and programming. If you are involved in any design activity, this will be a truly exciting addition to your bookshelf. |
| artificial intelligence in mechanical design: Artificial Intelligence in Structural Engineering Ian Smith, 1998-07-15 This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems. |
| artificial intelligence in mechanical design: Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering Gebrail Bekdas, Sinan Melih Nigdeli, Melda Yucel, 2019 This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering-- |
| artificial intelligence in mechanical design: Artificial Intelligence-Aided Materials Design Rajesh Jha, Bimal Kumar Jha, 2022-03-15 This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the MATLAB® and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference. Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats Helps readers to develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code Covers downloadable resources such as MATLAB GUI/APP and Python implementation that can be used on common mobile devices Discusses the CALPHAD approach and ways to use data generated from it Features a chapter on metallurgical/materials concepts to help readers understand the case studies and thus proper implementation of AI/ML algorithms under the framework of data-driven materials science Uses case studies to examine the importance of using unsupervised machine learning algorithms in determining patterns in datasets This book is written for materials scientists and metallurgists interested in the application of AI, ML, and data science in the development of new materials. |
| artificial intelligence in mechanical design: Artificial Intelligence in Engineering Design Christopher Tong, Duvvuru Sriram, 2012-12-02 Artificial Intelligence in Engineering Design is a three volume edited collection of key papers from the field of artificial intelligence and design, aimed at providing a description of the field, and focusing on how ideas and methods from artifical intelligence can help engineers in the design of physical artifacts and processes. The book surveys a wide variety of applications in the areas of civil, mechanical, chemical, VLSI, electrical, and computer engineering. The contributors are from leading academic computer-aided design centers as well as from industry. |
| artificial intelligence in mechanical design: Designing Autonomous AI Kence Anderson, 2022-06-14 Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial control technologies to make robust decisions in the real world. Using concrete examples, minimal theory, and a proven architectural framework, author Kence Anderson demonstrates how to teach autonomous AI explicit skills and strategies. You'll learn when and how to use and combine various AI architecture design patterns, as well as how to design advanced AI without needing to manipulate neural networks or machine learning algorithms. Students, process operators, data scientists, machine learning algorithm experts, and engineers who own and manage industrial processes can use the methodology in this book to design autonomous AI. This book examines: Differences between and limitations of automated, autonomous, and human decision-making Unique advantages of autonomous AI for real-time decision-making, with use cases How to design an autonomous AI from modular components and document your designs |
| artificial intelligence in mechanical design: Mechanical Design and Simulation: Exploring Innovations for the Future Duc Truong Pham, Yaguo Lei, Yanshan Lou, 2024-11-23 This book is an open access publication. This book presents innovative strategies and cutting-edge research at the intersection of mechanical engineering and simulation technologies. Aimed at addressing the current challenges and limitations in mechanical design, this book presents an array of advanced methodologies and tools that promise to revolutionize the field. From integrating artificial intelligence and machine learning for design optimization to leveraging the latest in finite element analysis for enhanced stress modelling, the proceedings highlight the pivotal role of simulation in pushing the boundaries of what is possible in mechanical design. With a strong emphasis on sustainable design practices and the utilization of additive manufacturing, this collection not only serves as an indispensable resource for engineers, researchers, and students but also marks a significant step forward in bridging the gap between traditional mechanical design principles and modern computational innovations. |
| artificial intelligence in mechanical design: Data Science and Intelligent Applications Ketan Kotecha, Vincenzo Piuri, Hetalkumar N. Shah, Rajan Patel, 2020-06-17 This book includes selected papers from the International Conference on Data Science and Intelligent Applications (ICDSIA 2020), hosted by Gandhinagar Institute of Technology (GIT), Gujarat, India, on January 24–25, 2020. The proceedings present original and high-quality contributions on theory and practice concerning emerging technologies in the areas of data science and intelligent applications. The conference provides a forum for researchers from academia and industry to present and share their ideas, views and results, while also helping them approach the challenges of technological advancements from different viewpoints. The contributions cover a broad range of topics, including: collective intelligence, intelligent systems, IoT, fuzzy systems, Bayesian networks, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, speech processing, machine learning and deep learning, and intelligent applications and systems. Helping strengthen the links between academia and industry, the book offers a valuable resource for instructors, students, industry practitioners, engineers, managers, researchers, and scientists alike. |
| artificial intelligence in mechanical design: Materials and Mechanical Engineering Guo Long Ruan, 2014-02-19 Selected, peer reviewed papers from the International Workshop on Materials and Mechanical Engineering (WMME 2013), November 20-22, 2013, Xianning, China |
| artificial intelligence in mechanical design: Applications of Artificial Intelligence in Engineering Xiao-Zhi Gao, Rajesh Kumar, Sumit Srivastava, Bhanu Pratap Soni, 2021-05-10 This book presents best selected papers presented at the First Global Conference on Artificial Intelligence and Applications (GCAIA 2020), organized by the University of Engineering & Management, Jaipur, India, during 8–10 September 2020. The proceeding will be targeting the current research works in the domain of intelligent systems and artificial intelligence. |
| artificial intelligence in mechanical design: Smart Electrical and Mechanical Systems Rakesh Sehgal, Neeraj Gupta, Anuradha Tomar, Mukund Dutt Sharma, Vigna Kumaran, 2022-06-22 Smart Electrical and Mechanical Systems: An Application of Artificial Intelligence and Machine Learning is an international contributed work with the most up-to-date fundamentals and conventional methods used in smart electrical and mechanical systems. Detailing methods and procedures for the application of ML and AI, it is supported with illustrations of the systems, process diagrams visuals of the systems and/or their components, and supportive data and results leading to the benefits and challenges of the relevant applications. The multidisciplinary theme of the book will help researchers build a synergy between electrical and mechanical engineering systems. The book guides readers on not only how to effectively solve problems but also provide high accuracy needed for successful implementation. Interdisciplinary in nature, the book caters to the needs of the electrical and mechanical engineering industry by offering details on the application of AI and ML in robotics, design and manufacturing, image processing, power system operation and forecasting with suitable examples. - Includes significant case studies related to application of Artificial Intelligence and Machine Learning in Energy and Power, Mechanical Design and Manufacturing - Contains supporting illustrations and tables, along with a valuable set of references at the end of each chapter - Provides original, state-of-the-art research material written by international and national respected contributors |
| artificial intelligence in mechanical design: Machine Learning for Kids Dale Lane, 2021-01-19 A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+ |
| artificial intelligence in mechanical design: Systems Engineering and Artificial Intelligence William F. Lawless, Ranjeev Mittu, Donald A. Sofge, Thomas Shortell, Thomas A. McDermott, 2021-11-02 This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges. |
| artificial intelligence in mechanical design: Artificial Intelligence and Digital Systems Engineering Adedeji B. Badiru, 2021-08-11 The resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations. |
| artificial intelligence in mechanical design: Applications of Artificial Intelligence and Machine Learning Ankur Choudhary, Arun Prakash Agrawal, Rajasvaran Logeswaran, Bhuvan Unhelkar, 2021-07-27 The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications. |
| artificial intelligence in mechanical design: Applications of Machine Learning Prashant Johri, Jitendra Kumar Verma, Sudip Paul, 2020-05-04 This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics. |
| artificial intelligence in mechanical design: Artificial Intelligence in Construction Engineering and Management Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski, 2021-06-18 This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally. |
| artificial intelligence in mechanical design: What To Do When Machines Do Everything Malcolm Frank, Paul Roehrig, Ben Pring, 2017-02-13 “Refreshingly thought-provoking...” – The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created. Written by a team of business and technology expert practitioners—who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business—this book provides a clear path to the future of your work. The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives—Automate, Halos, Enhance, Abundance, and Discovery—that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation. Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you; Understand the untold full extent of technology's impact on the way we work and live. Find out where we're headed, and how soon the future will arrive Leverage the new emerging paradigm into a sustainable business advantage Adopt a strategic model for winning in the new economy The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business—or your career—get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril. |
| artificial intelligence in mechanical design: Artificial Intelligence for Materials Science Yuan Cheng, Tian Wang, Gang Zhang, 2021-03-26 Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers. |
| artificial intelligence in mechanical design: Engineering Design Clive L. Dym, David C. Brown, 2014-04-17 Contrary to popular mythology, the designs of favorable products and successful systems do not appear suddenly, or magically. This second edition of Engineering Design demonstrates that symbolic representation and related problem-solving methods, offer significant opportunities to clarify and articulate concepts of design to lay a better framework for design research and design education. Artificial Intelligence (AI) provides a substantial body of material concerned with understanding and modeling cognitive processes. This book adopts the vocabulary and a paradigm of AI to enhance the presentation and explanation of design. It includes concepts from AI because of their explanatory power and their utility as possible ingredients of practical design activity. This second edition has been enriched by the inclusion of recent work on design reasoning, computational design, AI in design, and design cognition, with pointers to a wide cross section of the current literature. |
| artificial intelligence in mechanical design: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| artificial intelligence in mechanical design: Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries Shmelova, Tetiana, Sikirda, Yuliya, Sterenharz, Arnold, 2019-10-11 With the emergence of smart technology and automated systems in today’s world, artificial intelligence (AI) is being incorporated into an array of professions. The aviation and aerospace industry, specifically, is a field that has seen the successful implementation of early stages of automation in daily flight operations through flight management systems and autopilot. However, the effectiveness of aviation systems and the provision of flight safety still depend primarily upon the reliability of aviation specialists and human decision making. The Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries is a pivotal reference source that explores best practices for AI implementation in aviation to enhance security and the ability to learn, improve, and predict. While highlighting topics such as computer-aided design, automated systems, and human factors, this publication explores the enhancement of global aviation security as well as the methods of modern information systems in the aeronautics industry. This book is ideally designed for pilots, scientists, engineers, aviation operators, air crash investigators, teachers, academicians, researchers, and students seeking current research on the application of AI in the field of aviation. |
| artificial intelligence in mechanical design: Machine Learning in Industry Shubhabrata Datta, J. Paulo Davim, 2021-07-24 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. |
| artificial intelligence in mechanical design: Materials Discovery and Design Turab Lookman, Stephan Eidenbenz, Frank Alexander, Cris Barnes, 2018-09-22 This book addresses the current status, challenges and future directions of data-driven materials discovery and design. It presents the analysis and learning from data as a key theme in many science and cyber related applications. The challenging open questions as well as future directions in the application of data science to materials problems are sketched. Computational and experimental facilities today generate vast amounts of data at an unprecedented rate. The book gives guidance to discover new knowledge that enables materials innovation to address grand challenges in energy, environment and security, the clearer link needed between the data from these facilities and the theory and underlying science. The role of inference and optimization methods in distilling the data and constraining predictions using insights and results from theory is key to achieving the desired goals of real time analysis and feedback. Thus, the importance of this book lies in emphasizing that the full value of knowledge driven discovery using data can only be realized by integrating statistical and information sciences with materials science, which is increasingly dependent on high throughput and large scale computational and experimental data gathering efforts. This is especially the case as we enter a new era of big data in materials science with the planning of future experimental facilities such as the Linac Coherent Light Source at Stanford (LCLS-II), the European X-ray Free Electron Laser (EXFEL) and MaRIE (Matter Radiation in Extremes), the signature concept facility from Los Alamos National Laboratory. These facilities are expected to generate hundreds of terabytes to several petabytes of in situ spatially and temporally resolved data per sample. The questions that then arise include how we can learn from the data to accelerate the processing and analysis of reconstructed microstructure, rapidly map spatially resolved properties from high throughput data, devise diagnostics for pattern detection, and guide experiments towards desired targeted properties. The authors are an interdisciplinary group of leading experts who bring the excitement of the nascent and rapidly emerging field of materials informatics to the reader. |
| artificial intelligence in mechanical design: Mind Design II John Haugeland, 1997-03-06 Mind design is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is built, how it works). Unlike traditional empirical psychology, it is more oriented toward the how than the what. An experiment in mind design is more likely to be an attempt to build something and make it work—as in artificial intelligence—than to observe or analyze what already exists. Mind design is psychology by reverse engineering. When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's Computing Machinery and Intelligence) and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are philosophical in that they address fundamental issues and concepts; and all are scientific in that they are technically sophisticated and concerned with concrete empirical research. Contributors Rodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder |
| artificial intelligence in mechanical design: Mechanical Design: Theory and Methodology Manjula B. Waldron, Kenneth J. Waldron, 2013-04-09 This volume, Mechanical Design: Theory and Methodology, has been put together over the past four years. Most of the work is ongoing as can be ascertained easily from the text. One can argue that this is so for any text or monograph. Any such book is only a snapshot in time, giving information about the state of knowledge of the authors when the book was compiled. The chapters have been updated and are representative of the state of the art in the field of design theory and methodology. It is barely over a decade that design as an area of study was revived, mostly at the behest of industry, government, and academic leaders. Profes sor Nam Suh, then the head of the Engineering Directorate at the National Science Foundation, provided much of the impetus for the needed effort. The results of early work of researchers, many of whom have authored chapters in this book, were fundamental in conceiving the ideas behind Design for X or DFX and concurrent engineering issues. The artificial intelli gence community had a strong influence in developing the required com puter tools mainly because the field had a history of interdisciplinary work. Psychologists, computer scientists, and engineers worked together to under stand what support tools will improve the design process. While this influ ence continues today, there is an increased awareness that a much broader community needs to be involved. |
| artificial intelligence in mechanical design: AI Applications in Sheet Metal Forming Shailendra Kumar, Hussein M. A. Hussein, 2016-10-25 This book comprises chapters on research work done around the globe in the area of artificial intelligence (AI) applications in sheet metal forming. The first chapter offers an introduction to various AI techniques and sheet metal forming, while subsequent chapters describe traditional procedures/methods used in various sheet metal forming processes, and focus on the automation of those processes by means of AI techniques, such as KBS, ANN, GA, CBR, etc. Feature recognition and the manufacturability assessment of sheet metal parts, process planning, strip-layout design, selecting the type and size of die components, die modeling, and predicting die life are some of the most important aspects of sheet metal work. Traditionally, these activities are highly experience-based, tedious and time consuming. In response, researchers in several countries have applied various AI techniques to automate these activities, which are covered in this book. This book will be useful for engineers working in sheet metal industries, and will serve to provide future direction to young researchers and students working in the area. |
| artificial intelligence in mechanical design: Artificial Intelligence in Design ’00 John S. Gero, 2012-12-06 Designing is one of the foundations for change in our society. It is a fundamental precursor to manufacturing, fabrication and construction. Design research aims to develop an understanding of designing and to produce models of designing that can be used to aid designing. The papers in this volume are from the Sixth International Conference on Artificial Intelligence in Design (AID'00) held in June 2000, in Worcester, Massachusetts, USA. They represent the state of the art and the cutting edge of research and development in this field, and demonstrate both the depth and breadth of the artificial intelligence paradigm in design. They point the way for the development of advanced computer-based tools to aid designers, and describe advances in both theory and application. This volume will be of particular interest to researchers, developers, and users of advanced computer systems in design. |
| artificial intelligence in mechanical design: Impact and Opportunities of Artificial Intelligence Techniques in the Steel Industry Valentina Colla, Costanzo Pietrosanti, 2021-02-04 This book collects perceptions and needs expectations and experiences concerning the application of Artificial Intelligence (AI) and Machine Learning in the steel sector. It contains a selection of themes discussed within the Workshop entitled “Impact and Opportunities of Artificial Intelligence in the Steel Industry” organized by the European Steel Technology Platform as an online event from October 15 until November 5, 2020. The event aimed at analyzing the diffusion of AI technologies in steelworks and at providing indications for future research, development and innovation actions addressing the sector demands. The chapters treat general analyses on transversal themes and applications for process optimization, product quality enhancement, yield increase, optimal exploitation of resources and smart data handling. The book is devoted to researchers and technicians in the steel or AI fields as well as for managers and policymakers exploring the opportunities provided by AI in industry. |
| artificial intelligence in mechanical design: MECHANICAL SYSTEMS and ARTIFICIAL INTELLIGENCE Dr. T.PREMKUMAR, Dr.G.S.SAMY, MRS. N.JEENATH SHAFANA, 2024-07-27 Table of Content The Mechanical Design Renaissance: How AI is reshaping the Field Artificial Intelligence (AI) CAD and CAD-Based Datasets Machine Learning in Mechanical Design and Optimization |
| artificial intelligence in mechanical design: Architectural Intelligence Molly Wright Steenson, 2017-12-22 Architects who engaged with cybernetics, artificial intelligence, and other technologies poured the foundation for digital interactivity. In Architectural Intelligence, Molly Wright Steenson explores the work of four architects in the 1960s and 1970s who incorporated elements of interactivity into their work. Christopher Alexander, Richard Saul Wurman, Cedric Price, and Nicholas Negroponte and the MIT Architecture Machine Group all incorporated technologies—including cybernetics and artificial intelligence—into their work and influenced digital design practices from the late 1980s to the present day. Alexander, long before his famous 1977 book A Pattern Language, used computation and structure to visualize design problems; Wurman popularized the notion of “information architecture”; Price designed some of the first intelligent buildings; and Negroponte experimented with the ways people experience artificial intelligence, even at architectural scale. Steenson investigates how these architects pushed the boundaries of architecture—and how their technological experiments pushed the boundaries of technology. What did computational, cybernetic, and artificial intelligence researchers have to gain by engaging with architects and architectural problems? And what was this new space that emerged within these collaborations? At times, Steenson writes, the architects in this book characterized themselves as anti-architects and their work as anti-architecture. The projects Steenson examines mostly did not result in constructed buildings, but rather in design processes and tools, computer programs, interfaces, digital environments. Alexander, Wurman, Price, and Negroponte laid the foundation for many of our contemporary interactive practices, from information architecture to interaction design, from machine learning to smart cities. |
| artificial intelligence in mechanical design: Artificial Intelligence Margaret A. Boden, 2018-08-13 The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction , Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. |
| artificial intelligence in mechanical design: Formal Engineering Design Synthesis Erik K. Antonsson, Jonathan Cagan, 2005-09-29 In the early 1960s systematic techniques were introduced to guide engineers in producing high-quality designs. By the mid-1980s, these methods evolved from their informal guideline-like origins to more formal computable methods. Recently, highly automated design synthesis techniques have emerged. This timely work reviews the state of the art in formal design synthesis methods. It also provides an in-depth exploration of several representative projects in formal design synthesis and examines future directions in computational design synthesis research. The chapters are written by internationally renowned experts in engineering and architectural design. |
| artificial intelligence in mechanical design: Artificial Intelligence in Engineering Design Duvvuru Sriram, Christopher Tong, 1992 |
| artificial intelligence in mechanical design: Advanced Mechanical Design Wen Zhe Chen, Pin Qiang Dai, Yong Lu Chen, Qian Ting Wang, Zheng Yi Jiang, 2012-02-27 Selected, peer reviewed papers from the 3rd international Conference on Manufacturing Science and Engineering (ICMSE 2012), March 27-29, 2012, Xiamen, China |
| artificial intelligence in mechanical design: Artificial Intelligence in Engineering Robert A. Adey, Duvvuru Sriram, 1987-08-01 |
| artificial intelligence in mechanical design: Artificial Intelligence in Process Engineering Michael Mavrovouniotis, 2012-12-02 Artificial Intelligence in Process Engineering aims to present a diverse sample of Artificial Intelligence (AI) applications in process engineering. The book contains contributions, selected by the editors based on educational value and diversity of AI methods and process engineering application domains. Topics discussed in the text include the use of qualitative reasoning for modeling and simulation of chemical systems; the use of qualitative models in discrete event simulation to analyze malfunctions in processing systems; and the diagnosis of faults in processes that are controlled by Programmable Logic Controllers. There are also debates on the issue of quantitative versus qualitative information. The control of batch processes, a design of a system that synthesizes bioseparation processes, and process design in the domain of chemical (rather than biochemical) systems are likewise covered in the text. This publication will be of value to industrial engineers and process engineers and researchers. |
| artificial intelligence in mechanical design: Artificial Intelligence in Engineering Design Bozzano G Luisa, 2012-12-02 Artificial Intelligence in Engineering Design, Volume II: Models of Innovative Design, Reasoning About Physical Systems, and Reasoning About Geometry focuses on the processes, programs, techniques, and technologies involved in the employment of artificial intelligence in engineering design. The selection first takes a look at the automated reuse of design plans in BOGART and ARGO, an analogical reasoning system for solving design problems. Topics include analogy mechanisms in ARGO, analogical reasoning and learning, ARGO development environment, using VEXED to construct a design plan, and how BOGART reuses a design plan. The text then ponders on retrieval strategies in a case-based design system and case-based design, including the functions-to-structure design task in the domain of physical devices, design retrieval, proposition, and modification, and the multi-layered case representation. The publication examines mechanism comparison and classification for design; a case-based approach to the design of mechanical linkages; and studies of heuristic knowledge-based approaches for automated configuration generation and innovation. Topics include applications of stress field estimation to geometric optimization, simplification and abstraction operators, mechanism comparison and classification, linkage synthesis, analytic synthesis techniques, and system architecture. The selection is a valuable reference for readers interested in the use of artificial intelligence in engineering design. |
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
artificial - Wiktionary, the free dictionary
6 days ago · artificial (comparative more artificial, superlative most artificial) Man-made; made by humans; of artifice. The flowers were artificial, and he thought them rather tacky. An artificial …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real …
Artificial Intelligence Is Not Intelligent - The Atlantic
Jun 6, 2025 · The good news is that nothing about this is inevitable: According to a study released in April by the Pew Research Center, although 56 percent of “AI experts” think artificial …
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is synthetic.
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
artificial - Wiktionary, the free dictionary
6 days ago · artificial (comparative more artificial, superlative most artificial) Man-made; made by humans; of artifice. The flowers were artificial, and he thought them rather tacky. An artificial …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real version, …
Artificial Intelligence Is Not Intelligent - The Atlantic
Jun 6, 2025 · The good news is that nothing about this is inevitable: According to a study released in April by the Pew Research Center, although 56 percent of “AI experts” think artificial …
