Analyzes the fabrication capacity versus workload from current work-in-process (WIP) in order to create a short-term scheduling system which balances WIP flows in observance of WIP targets and the output schedule. Research focuses only on the front end of the production of semiconductor wafers in order to develop an effective and optimal material/fabrication input schedule, a precise capacity utilization analysis, and a feasible and optimal material/fabrication output schedule.
Over the last fifty-plus years, the increased complexity and speed of integrated circuits have radically changed our world. Today, semiconductor manufacturing is perhaps the most important segment of the global manufacturing sector. As the semiconductor industry has become more competitive, improving planning and control has become a key factor for business success. This book is devoted to production planning and control problems in semiconductor wafer fabrication facilities. It is the first book that takes a comprehensive look at the role of modeling, analysis, and related information systems for such manufacturing systems. The book provides an operations research- and computer science-based introduction into this important field of semiconductor manufacturing-related research.
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.
No other book has been published giving a single-volume introduction and survey to production planning in distributed manufacturing networks. The published literature so far includes conference proceedings only.
This book concentrates on real-world production scheduling in factories and industrial settings. It includes industry case studies that use innovative techniques as well as academic research results that can be used to improve production scheduling. Its purpose is to present scheduling principles, advanced tools, and examples of innovative scheduling systems to persons who could use this information to improve their own production scheduling.
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 deals with 3D nanodevices such as nanowire and nanosheet transistors at 7 nm and smaller technology nodes. It discusses technology computer-aided design (TCAD) simulations of stress- and strain-engineered advanced semiconductor devices, including III-nitride and RF FDSOI CMOS, for flexible and stretchable electronics. The book focuses on how to set up 3D TCAD simulation tools, from mask layout to process and device simulation, including fabless intelligent manufacturing. The simulation examples chosen are from the most popular devices in use today and provide useful technology and device physics insights. In order to extend the role of TCAD in the More-than-Moore era, the design issues related to strain engineering for flexible and stretchable electronics have been introduced for the first time.
This book provides a methodological understanding of the theoretical and technical limitations to the longevity of Moore’s law. The book presents research on factors that have significant impact on the future of Moore’s law and those factors believed to sustain the trend of the last five decades. Research findings show that boundaries of Moore’s law primarily include physical restrictions of scaling electronic components to levels beyond that of ordinary manufacturing principles and approaching the bounds of physics. The research presented in this book provides essential background and knowledge to grasp the following principles: Traditional and modern photolithography, the primary limiting factor of Moore’s law Innovations in semiconductor manufacturing that makes current generation CMOS processing possible Multi-disciplinary technologies that could drive Moore's law forward significantly Design principles for microelectronic circuits and components that take advantage of technology miniaturization The semiconductor industry economic market trends and technical driving factors The complexity and cost associated with technology scaling have compelled researchers in the disciplines of engineering and physics to optimize previous generation nodes to improve system-on-chip performance. This is especially relevant to participate in the increased attractiveness of the Internet of Things (IoT). This book additionally provides scholarly and practical examples of principles in microelectronic circuit design and layout to mitigate technology limits of previous generation nodes. Readers are encouraged to intellectually apply the knowledge derived from this book to further research and innovation in prolonging Moore’s law and associated principles.
This book presents a comprehensive overview of recent developments in production planning. The monograph begins with an introductory chapter reviewing the need for these production planning models, that operate by determining time-phased releases of work into the facility or supply chain, relating these to the Manufacturing Planning and Control (MPC) and Advanced Planning and Scheduling (APS) frameworks, that form the basis of most academic research and industrial practice. The extensive body of work on Workload Control is also placed in this context, and proves the need for improved models with a discussion of the difficulties, these approaches encounter. The next two chapters present a detailed review of the state of the art in optimization models based on exogenous planned lead times, and examines the cases where these can take both integer and fractional values. The difficulties arising in estimating planned lead times are consistent with factory behavior which are highlighted, noting that many of these lead to non-convex optimization models. Attempts to address these difficulties by iterative multimodel approaches, that combine simulation and mathematical programming, are also discussed in detail. The next three chapters of the volume address the set of techniques developed using clearing functions, which represent the expected output of a resource in a planning period, as a function of the expected workload of the resource, during that period. The chapters on this subject propose a basic optimization model for multiple products, discuss the difficulties of this model and some possible solutions. It also reviews prior work, and discuss a number of alternative formulations of the clearing function concept with their respective advantages and disadvantages. Applications to lot sizing decisions and a number of other specific problems are also described. This volume concludes with an assessment of the state of the art described in the volume, and several directions for future work.
The production control of flexible manufacturing systems is a relevant component that must go along with the requirements of being flexible in terms of new product variants, new machine skills and reaction to unforeseen events during runtime. This work focuses on developing a reactive job-shop scheduling system for flexible and re-configurable manufacturing systems. Reinforcement Learning approaches are therefore investigated for the concept of multiple agents that control products including transportation and resource allocation.
