Data Driven Scheduling Of Semiconductor Manufacturing Systems
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Data-Driven Scheduling of Semiconductor Manufacturing Systems by Li Li,Qingyun Yu,Kuo-Yi Lin,Yumin Ma,Fei Qiao Pdf
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.
Advances in Production Management Systems. Production Management for Data-Driven, Intelligent, Collaborative, and Sustainable Manufacturing by Ilkyeong Moon,Gyu M. Lee,Jinwoo Park,Dimitris Kiritsis,Gregor von Cieminski Pdf
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.
Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems by Ann-Louise Andersen,Rasmus Andersen,Thomas Ditlev Brunoe,Maria Stoettrup Schioenning Larsen,Kjeld Nielsen,Alessia Napoleone,Stefan Kjeldgaard Pdf
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.
Production Planning and Control in Semiconductor Manufacturing by Tin-Chih Toly Chen Pdf
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.
Dynamics in Logistics by Michael Freitag,Hans-Dietrich Haasis,Herbert Kotzab,Jürgen Pannek Pdf
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 by Mangey Ram Pdf
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
Agent-Directed Simulation and Systems Engineering by Levent Yilmaz,Tuncer Ören Pdf
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.
Production and Operations Analysis by Susmita Bandyopadhyay Pdf
The aim of this book is to cover various aspects of the Production and Operations Analysis. Apart from the introduction to basic understanding of each topic, the book will also provide insights to various conventional techniques as well as, various other mathematical and nature-based techniques extracted from the existing literature. Concepts like smart factories, intelligent manufacturing, and various techniques of manufacturing will also be included. Various types of numerical examples will also be presented in each chapter and the descriptions will be done in lucid style with figures, point-wise descriptions, tables, pictures to facilitate easy understanding of the subject.
Springer Handbook of Automation by Shimon Y. Nof Pdf
This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.
Decentralized Scheduling of Discrete Production Systems with Limited Buffers by Zimmermann, Olaf Pdf
Modern production systems have become more flexible and agile. For them, a suitable control and planning method is needed. Agent-based systems offer the required characteristics. The contributions of these work are a remodeling of the Shifting Bottleneck heuristic to include limited buffers, the development of a decentralized multi-agent system for production planning, and the adaptation of the heuristic to the agent system. It concludes with evaluations of real-world production systems.
Material Engineering and Mechanical Engineering by Huiyu Zhou Pdf
The aim of proceeding of International Conference on Material Engineering and Mechanical Engineering [MEME2015] is to provide a platform for researchers, engineers, and academicians, as well as industrial professionals, to present their research results and applications developed for Material Engineering and Mechanical Engineering. It provides an opportunities for the delegates to exchange new ideas and application experiences, to enhance business or research relations and to find global partners for future collaboration. The object is to strengthen national academic exchanges and cooperation in the field, promote the rapid development of machinery, materials science and engineering application, effectively improve China's machinery, materials science and engineering applications in the field of academic status and international influence. Contents:Mechanics:Basic Mechanics and Research MethodsThermodynamicsDynamics and VibrationBiomechanicsVarious MechanicsMaterial Science and Material Processing Technology:CompositeNano MaterialsSteelCeramicsPolymer Readership: Graduate students and researchers in the field of mechanics engineering and materials engineering.
Handbook of Dynamic Data Driven Applications Systems by Frederica Darema,Erik P. Blasch,Sai Ravela,Alex J. Aved Pdf
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes by Zhiwei Gao,Michael Z. Q. Chen,Dapeng Zhang Pdf
The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors.
Recent Advances in Data Mining of Enterprise Data by T. Warren Liao,Evangelos Triantaphyllou Pdf
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as OC enterprise dataOCO. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making. Sample Chapter(s). Foreword (37 KB). Chapter 1: Enterprise Data Mining: A Review and Research Directions (655 KB). Contents: Enterprise Data Mining: A Review and Research Directions (T W Liao); Application and Comparison of Classification Techniques in Controlling Credit Risk (L Yu et al.); Predictive Classification with Imbalanced Enterprise Data (S Daskalaki et al.); Data Mining Applications of Process Platform Formation for High Variety Production (J Jiao & L Zhang); Multivariate Control Charts from a Data Mining Perspective (G C Porzio & G Ragozini); Maintenance Planning Using Enterprise Data Mining (L P Khoo et al.); Mining Images of Cell-Based Assays (P Perner); Support Vector Machines and Applications (T B Trafalis & O O Oladunni); A Survey of Manifold-Based Learning Methods (X Huo et al.); and other papers. Readership: Graduate students in engineering, computer science, and business schools; researchers and practioners of data mining with emphazis of enterprise data mining."
