|Author||: Laha, Dipak,Mandal, Purnendu|
|Publisher||: IGI Global|
|Release Date||: 2007-11-30|
|ISBN 10||: 1599045842|
|Pages||: 516 pages|
During the last two decades, computer and information technologies have forced great changes in the ways businesses manage operations in meeting the desired quality of products and services, customer demands, competition, and other challenges. The Handbook of Computational Intelligence in Manufacturing and Production Management focuses on new developments in computational intelligence in areas such as forecasting, scheduling, production planning, inventory control, and aggregate planning, among others. This comprehensive collection of research provides cutting-edge knowledge on information technology developments for both researchers and professionals in fields such as operations and production management, Web engineering, artificial intelligence, and information resources management.
|Author||: Abdolhossein Hemmati Sarapardeh,Aydin Larestani,Nait Amar Menad,Sassan Hajirezaie|
|Publisher||: Gulf Professional Publishing|
|Release Date||: 2020-08-26|
|ISBN 10||: 0128223855|
|Pages||: 322 pages|
Applications of Artificial Intelligence Techniques in the Petroleum Industry gives engineers a critical resource to help them understand the machine learning that will solve specific engineering challenges. The reference begins with fundamentals, covering preprocessing of data, types of intelligent models, and training and optimization algorithms. The book moves on to methodically address artificial intelligence technology and applications by the upstream sector, covering exploration, drilling, reservoir and production engineering. Final sections cover current gaps and future challenges. Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering Helps readers increase their existing knowledge on intelligent data modeling, machine learning and artificial intelligence, with foundational chapters covering the preprocessing of data and training on algorithms Provides tactics on how to cover complex projects such as shale gas, tight oils, and other types of unconventional reservoirs with more advanced model input
|Author||: Takushi Tanaka,Moonis Ali,Setsuo Ohsuga|
|Publisher||: CRC Press|
|Release Date||: 1997-01-30|
|ISBN 10||: 9789056995249|
|Pages||: 808 pages|
This work represents a broad spectrum of new ideas in the field of applied artificial intelligence and expert systems, and serves to disseminate information regarding intelligent methodologies and their implementation in solving various problems in industry and engineering. Many innovative artificial intelligence (AI) systems have emerged as the result of engineering machines to think like humans and perform intelligent functions. However, only recently have intelligent systems been applied to solve real life problems.
Innovation in all aspects of mechanical engineering and management Computer Aided Production Engineering is a compilation of papers presented at the 17th International CAPE Conference in 2001. Featuring the work of leading innovators from academia and industry, this book explores the forefront of mechanical engineering technology and practices to provide insight for today and direction for tomorrow. Broad in scope yet rich in detail, these papers cover topics ranging from supply chain management, nontraditional processes, and quality control, to machining processes, concurrent design and engineering, rapid prototyping, virtual reality applications, and much more.
|Author||: Zhou, Zude,Wang, Huaiqing,Lou, Ping|
|Publisher||: IGI Global|
|Release Date||: 2010-03-31|
|ISBN 10||: 1605668656|
|Pages||: 407 pages|
"This book focuses on the latest innovations in the process of manufacturing in engineering"--Provided by publisher.
|Author||: Anna Burduk,Edward Chlebus,Tomasz Nowakowski,Agnieszka Tubis|
|Release Date||: 2018-07-31|
|ISBN 10||: 3319974904|
|Pages||: 785 pages|
The book presents a collection of 103 peer-reviewed articles from the Second International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM 2018). The conference was organized by the Faculty of Mechanical Engineering and CAMT (Centre for Advanced Manufacturing Technologies), Wrocław University of Science and Technology and was held in Wrocław (Poland) on 17–18 September 2018. The conferences topics included the possibility of using a wide range of intelligent methods in production engineering, presenting and discussing new solutions for innovative plants, research findings and case studies demonstrating advances in production and maintenance from the point of view of Industry 4.0 – particularly applications of intelligent systems, methods and tools in production engineering, maintenance, logistics, quality management, information systems and product development. The book is divided into two parts: the first includes papers related to intelligent systems in production engineering, while the second is dedicated to special sessions focusing on: 1. Computer Aided methods in Production Engineering 2. Mining 4.0 and Intelligent Mining Transportation 3. Modelling and Simulation of Production Processes 4. Multi-Faceted Modelling of Networks and Processes 5. Product Design and Product Manufacturing in Industry 4.0 This book is an excellent source of information for scientists in the field of manufacturing engineering and for top managers in production enterprises.
|Author||: BBVL. Deepak,DRK Parhi,Pankaj C. Jena|
|Publisher||: Springer Nature|
|Release Date||: 2020-03-13|
|ISBN 10||: 9811526966|
|Pages||: 1100 pages|
This book gathers selected research articles from the International Conference on Innovative Product Design and Intelligent Manufacturing System (ICIPDIMS 2019), held at the National Institute of Technology, Rourkela, India. The book discusses latest methods and advanced tools from different areas of design and manufacturing technology. The main topics covered include design methodologies, industry 4.0, smart manufacturing, and advances in robotics among others. The contents of this book are useful for academics as well as professionals working in industrial design, mechatronics, robotics, and automation.
This book constitutes the refereed proceedings of the 17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004, held in Ottawa, Canada, in May 2004. The 129 revised full papers presented were carefully reviewed and selected from 208 submissions. The papers are organized in topical sections on neural networks, bioinformatics, data mining, general applications, autonomous agents, intelligent systems, knowledge processing and NLP, intelligent user interfaces, evolutionary computing, fuzzy logic, human-roboter interaction, computer vision and image processing, machine learning and case-based reasoning, heuristic search, security, Internet applications, planning and scheduling, constraint satisfaction, e-learning, expert systems, applications to design, machine learning, and image processing.
|Author||: Lyes Benyoucef,Bernard Grabot|
|Publisher||: Springer Science & Business Media|
|Release Date||: 2010-05-10|
|ISBN 10||: 9781849961196|
|Pages||: 508 pages|
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.
After an introductory chapter explaining recent applications of fuzzy sets in IE, this book explores the seven major areas of IE to which fuzzy set theory can contribute: Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and Ergonomics, Manufacturing Systems and Technology Management, Optimization Techniques, and Statistical Decision-making. Under these major areas, every chapter includes didactic numerical applications.
At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.
This book constitutes the refereed proceedings of the 21st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2008, held in Wroclaw, Poland, in June 2008. The 75 revised full papers presented were carefully reviewed and selected from 302 submissions. The papers are organized in topical sections on computer vision, fuzzy system applications, robot and manufacturing, data mining and KDS, neural networks, machine learning, natural language processing, internet application and education, heuristic search, application systems, agent-based system, evolutionary and genetic algorithms, knowledge management, and other applications. The book concludes with 15 contributions from the following special sessions: knowledge driven manufacturing systems, joint session on adaptive networked systems and fuzzy knowledge bases, and software agents and multi-agent systems.
|Author||: Farayi Musharavati|
|Release Date||: 2010-09|
|ISBN 10||: 1599423596|
|Pages||: 200 pages|
To date, reconfigurable manufacturing systems (RMSs) are among the most effective manufacturing styles that can offer manufacturers an alternative way of facing up to the challenges of continual changes in production requirements within the global, competitive and dynamic manufacturing environments. However, availability of optimal process plans that are suitable for reconfigurable manufacturing is one of the key enablers - yet to be fully unlocked - for realizing the full benefits of true RMSs. To unlock the process planning key and advance the state of art of reconfigurable manufacturing in the manufacturing industry, a number of questions need to be answered: (i) what decision making models and (ii) what computational techniques, can be applied to provide optimal manufacturing process planning solutions that are suitable for logical reconfiguration in manufacturing systems? To answer these questions, you must understand how to model reconfigurable manufacturing activities in an optimization perspective. You must also understand how to develop and select appropriate optimization techniques for solving process planning problems in manufacturing systems. To this end, Process Planning Optimization in Reconfigurable Manufacturing Systems covers: the design and operation of RMSs, optimal process planning modelling for reconfigurable manufacturing and the design and implementation of heuristic algorithm design techniques. The author explores how to: model optimization problems, select suitable optimization techniques, develop optimization algorithms, comparatively analyze the performance of candidate metaheuristics and how to investigate the effects of optimal process planning solutions on operating levels in manufacturing systems. This book delineates five alternative heuristic algorithm design techniques based on simulated annealing, genetic algorithms and the boltzmann machine that are tasked to solve manufacturing process planning optimization problems in RMSs. After reading this book, you will understand: how a reconfigurable manufacturing system works, the different types of manufacturing optimization problems associated with reconfigurable manufacturing, as well as the conventional and intelligent techniques that are suitable for solving process planning optimization problems. You will also be able to develop and implement effective optimization procedures and algorithms for a wide spectrum of optimization problems in design and reconfigurable manufacturing."
This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013. The total of 71 papers selected for the proceedings were carefully reviewed and selected from 185 submissions. The papers focus on the following topics: auctions and negotiation, cognitive modeling, crowd behavior modeling, distributed systems and networks, evolutionary algorithms, knowledge representation and reasoning, pattern recognition, planning, problem solving, robotics, text mining, advances in recommender systems, business process intelligence, decision support for safety-related systems, innovations in intelligent computation and applications, intelligent image and signal processing, and machine learning methods applied to manufacturing processes and production systems.
This handbook focuses on a series of concepts, models and technologies which can be used to improve current practice in life cycle engineering in manufacturing companies around the world. Experts on the main issues relating to life cycle engineering have produced a superb collection of chapters. All the contributing authors are researchers and engineers in the fields of manufacturing paradigms, enterprise integration, product life cycle and technologies for life cycle engineering. Academics and researchers will find this book to be a valuable reference tool. The book illustrates those key factors that ensure successful enterprise and product life cycle integration. Due to the book being developed as a joint industry and university project, its approach should be helpful to both practising professionals and academics. An overview of life cycle engineering concepts, models, methodologies and practices that have been proved to significantly improve the integration and productivity of manufacturing companies have been clearly explained in this handbook. This book will be essential for engineers, designers, product support personnel dealing with enterprise engineering projects. It will also be of immense use to lecturers and senior lecturers working in the fields of enterprise integration, product development, concurrent engineering and integrated manufacturing systems.
This book constitutes the refereed proceedings of the 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, held in Loughborough, UK in June 2003. The 81 revised full papers presented were carefully reviewed and selected from more than 140 submissions. Among the topics addressed are soft computing, fuzzy logic, diagnosis, knowledge representation, knowledge management, automated reasoning, machine learning, planning and scheduling, evolutionary computation, computer vision, agent systems, algorithmic learning, tutoring systems, financial analysis, etc.
|Author||: Cengiz Kahraman,Mesut Yavuz|
|Publisher||: Springer Science & Business Media|
|Release Date||: 2010-05-19|
|ISBN 10||: 3642120512|
|Pages||: 605 pages|
Production engineering and management involve a series of planning and control activities in a production system. A production system can be as small as a shop with only one machine or as big as a global operation including many manufacturing plants, distribution centers, and retail locations in multiple continents. The product of a production system can also vary in complexity based on the material used, technology employed, etc. Every product, whether a pencil or an airplane, is produced in a system which depends on good management to be successful. Production management has been at the center of industrial engineering and management science disciplines since the industrial revolution. The tools and techniques of production management have been so successful that they have been adopted to various service industries, as well. The book is intended to be a valuable resource to undergraduate and graduate students interested in the applications of production management under fuzziness. The chapters represent all areas of production management and are organized to reflect the natural order of production management tasks. In all chapters, special attention is given to applicability and wherever possible, numerical examples are presented. While the reader is expected to have a fairly good understanding of the fuzzy logic, the book provides the necessary notation and preliminary knowledge needed in each chapter.