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This is the final report of a two-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of the project is to combine detailed physical models of industrial processes with unit operations and business-level models. This would allow global and individual process control schemes to be implemented that would facilitate improved overall system performance. Intelligent decision support that employs expert system concepts (knowledge base and rules) could then also be incorporated. This project is innovative because it attempts to incorporate all levels of production-related activities from atoms to enterprise, and to integrate those activities into one comprehensive decision support tool. This project is an interdisciplinary effort requiring enterprise modeling and simulation model integration; process modeling and control; process control and optimization; chemical process modeling; and detailed molecular-level models. It represents the state of the art in enterprise modeling and simulation and incorporates cutting edge process modeling, process control, and system optimization techniques.
Manufacturing process controls include all systems and software that exert control over production processes. Control systems include process sensors, data processing equipment, actuators, networks to connect equipment, and algorithms to relate process variables to product attributes. Since 1995, the U.S. Department of Energy Office of Industrial Technology 's (OIT) program management strategy has reflected its commitment to increasing and documenting the commercial impact of OIT programs. OIT's management strategy for research and development has been in transition from a "technology push" strategy to a "market pull" strategy based on the needs of seven energy-and waste-intensive industries-steel, forest products, glass, metal casting, aluminum, chemicals, and petroleum refining. These industries, designated as Industries of the Future (IOF), are the focus of OIT programs. In 1997, agriculture, specifically renewable bioproducts, was added to the IOF group. The National Research Council Panel on Manufacturing Process Controls is part of the Committee on Industrial Technology Assessments (CITA), which was established to evaluate the OIT program strategy, to provide guidance during the transition to the new IOF strategy, and to assess the effects of the change in program strategy on cross-cutting technology programs, that is, technologies applicable to several of the IOF industries. The panel was established to identify key processes and needs for improved manufacturing control technology, especially the needs common to several IOF industries; identify specific research opportunities for addressing these common industry needs; suggest criteria for identifying and prioritizing research and development (R&D) to improve manufacturing controls technologies; and recommend means for implementing advances in control technologies.
eWork and eBusiness in Architecture, Engineering and Construction 2021 collects the papers presented at the 13th European Conference on Product and Process Modelling (ECPPM 2021, Moscow, 5-7 May 2021). The contributions cover a wide spectrum of thematic areas that hold great promise towards the advancement of research and technological development targeted at the digitalization of the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. High quality contributions are devoted to critically important problems that arise, including: Information and Knowledge Management Semantic Web and Linked Data Communication and Collaboration Technologies Software Interoperability BIM Servers and Product Lifecycle Management Systems Digital Twins and Cyber-Physical Systems Sensors and Internet of Things Big Data Artificial and Augmented Intelligence in AEC Construction Management 5D/nD Modelling and Planning Building Performance Simulation Contract, Cost and Risk Management Safety and Quality Sustainable Buildings and Urban Environments Smart Buildings and Cities BIM Standardization, Implementation and Adoption Regulatory and Legal Aspects BIM Education and Training Industrialized Production, Smart Products and Services Over the past quarter century, the biennial ECPPM conference series, as the oldest BIM conference, has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry.
Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. • An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).
Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment. It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings. Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
"This book opens up the world of simulation to you by providing the basics of general simulation techonology, identifying the skills needed for successful simulation projects, and introducting a state-of-the-art simulation package." --
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.