| Author | : Anna Burduk,Dariusz Mazurkiewicz |
| Publisher | : Springer |
| Release Date | : 2017-08-16 |
| ISBN 10 | : 3319644653 |
| Pages | : 470 pages |
The volume presents a collection of 44 peer-reviewed articles from the First International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM 2017). ISPEM 2017 was organized by the Faculty of Mechanical Engineering, Wrocław University of Science and Technology and was held in Wrocław (Poland) on 28–29 September 2017. The main topics of the conference included the possibility of using widely understood intelligent methods in production engineering. New solutions for innovative plants, research results and case studies taking into account advances in production and maintenance from the point of view of Industry 4.0 were presented and discussed—with special attention paid to applications of intelligent systems, methods and tools in production engineering, maintenance, logistics, quality management, information systems, and product development. The volume is divided into two parts: 1. Intelligent Systems in Production Engineering 2. Intelligent Systems in Maintenance This book is an excellent reference resource 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.
| 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 | : Soundar T. Kumara,Allen L. Soyster,Rangasami Laksminarayana Kashyap |
| Publisher | : Inst of Industrial Engineers |
| Release Date | : 1988 |
| ISBN 10 | : |
| Pages | : 686 pages |
| 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.
| Author | : N.A |
| Publisher | : N.A |
| Release Date | : 1991 |
| ISBN 10 | : |
| Pages | : 329 pages |
| 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 | : Hongzan Bin |
| Publisher | : John Wiley & Sons |
| Release Date | : 2001-12-21 |
| ISBN 10 | : 9781860583674 |
| Pages | : 480 pages |
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 | : Jie Zhang |
| Publisher | : John Wiley & Sons |
| Release Date | : 2017-05-09 |
| ISBN 10 | : 1118890094 |
| Pages | : 440 pages |
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.
| 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.
| Author | : Yogendra Narayan Pandey,Ayush Rastogi,Sribharath Kainkaryam,Srimoyee Bhattacharya,Luigi Saputelli |
| Publisher | : Apress |
| Release Date | : 2020-11-03 |
| ISBN 10 | : 9781484260937 |
| Pages | : 300 pages |
Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will Learn Understanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.
| 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.