Download Free Data Driven Scheduling Of Semiconductor Manufacturing Systems Book in PDF and EPUB Free Download. You can read online Data Driven Scheduling Of Semiconductor Manufacturing Systems and write the review.

This book systematically discusses the intelligent scheduling problem of complex semiconductor manufacturing systems from theory to method and then to application. The main contents include data-driven scheduling framework of semiconductor manufacturing system, data preprocessing of semiconductor manufacturing system, correlation analysis of performance index of semiconductor production line, intelligent release control strategy, dynamic dispatching rules simulating pheromone mechanism, and load balancing dynamic scheduling of semiconductor production line, performance index-driven dynamic scheduling method of semiconductor production line, scheduling trend of semi-conductor manufacturing system in big data environment. This book aims to provide readers with valuable reference and assistance in the theoretical methods, techniques, and application cases of semiconductor manufacturing systems and their intelligent scheduling.
This book has resulted from the activities of IFAC TC 5.2 “Manufacturing Modelling for Management and Control”. The book offers an introduction and advanced techniques of scheduling applications to cloud manufacturing and Industry 4.0 systems for larger audience. This book uncovers fundamental principles and recent developments in the theory and application of scheduling methodology to cloud manufacturing and Industry 4.0. The purpose of this book is to present recent developments in scheduling in cloud manufacturing and Industry 4.0 and to systemize these developments in new taxonomies and methodological principles to shape this new research domain. This book addresses the needs of both researchers and practitioners to uncover the challenges and opportunities of scheduling techniques’ applications to cloud manufacturing and Industry 4.0. For the first time, it comprehensively conceptualizes scheduling in cloud manufacturing and Industry 4.0 systems as a new research domain. The chapters of the book are written by the leading international experts and utilize methods of operations research, industrial engineering and computer science. Such a multi-disciplinary combination is unique and comprehensively deciphers major problem taxonomies, methodologies, and applications to scheduling in cloud manufacturing and Industry 4.0.
The two-volume set IFIP AICT 535 and 536 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2018, held in Seoul, South Korea, in August 2018. The 129 revised full papers presented were carefully reviewed and selected from 149 submissions. They are organized in the following topical sections: lean and green manufacturing; operations management in engineer-to-order manufacturing; product-service systems, customer-driven innovation and value co-creation; collaborative networks; smart production for mass customization; global supply chain management; knowledge based production planning and control; knowledge based engineering; intelligent diagnostics and maintenance solutions for smart manufacturing; service engineering based on smart manufacturing capabilities; smart city interoperability and cross-platform implementation; manufacturing performance management in smart factories; industry 4.0 - digital twin; industry 4.0 - smart factory; and industry 4.0 - collaborative cyber-physical production and human systems.
This book features state-of-the-art contributions from two well-established conferences: Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2020) and Mass Customization and Personalization Conference (MCPC2020). Together, they focus on the joint design, development, and management of products, production systems, and business for sustainable customization and personalization. The book covers a large range of topics within this domain, ranging from industrial success factors to original contributions within the field.
This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.
Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume.
The two volume set LNAI 8481 and 8482 constitutes the refereed conference proceedings of the 27th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014, held in Kaohsiung, Taiwan, in June 2014. The total of 106 papers selected for the proceedings were carefully reviewed and selected from various submissions. The papers deal with a wide range of topics from applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation and robotics, business and finance, medicine and biomedicine, bioinformatics, cyberspace and human-machine interaction.
Since 2007, the biennial International Conferences on Dynamics in Logistics (LDIC) offers researchers and practitioners from logistics, operations research, production, industrial and electrical engineering as well as from computer science an opportunity to meet and to discuss the latest developments in this particular research domain. From February 12th to 14th 2020 for the seventh time, LDIC 2020 is held in Bremen, Germany. Similar to its six predecessors, the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) organizes this conference. The spectrum of topics reaches from the dynamic modeling, planning and control of processes over supply chain management and maritime logistics to innovative technologies and robotic applications for cyber-physical production and logistics systems. LDIC 2020 provides a forum for the discussion of advances in that matter. The conference program consists of three invited keynote speeches and 51 papers selected by a severe double-blind reviewing process. Within these proceedings all the papers are published. By this, the proceedings give an interdisciplinary outline on the state of the art of dynamics in logistics as well as identify challenges and solutions for logistics today and tomorrow.
Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision-making, including mathematical and optimization techniques for dealing with large amounts of data in short periods. - Focuses on recent research in mathematics applications for Industry 4.0 - Provides insights on international and transnational scales - Identifies mathematics knowledge gaps for Industry 4.0 - Describes fruitful areas for further research in industrial mathematics, including forthcoming international studies and research
The only book to present the synergy between modeling and simulation, systems engineering, and agent technologies expands the notion of agent-based simulation to also deal with agent simulation and agent-supported simulation. Accessible to both practitioners and managers, it systematically addresses designing and building agent systems from a systems engineering perspective.