Robust Modelling and Simulation
Robust Modelling and Simulation

Author: Idalia Flores De La Mota

Publisher: Springer

Published: 2017-03-28

Total Pages: 173

ISBN-13: 3319533215

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This book presents for the first time a methodology that combines the power of a modelling formalism such as colored petri nets with the flexibility of a discrete event program such as SIMIO. Industrial practitioners have seen the growth of simulation as a methodology for tacking problems in which variability is the common denominator. Practically all industrial systems, from manufacturing to aviation are considered stochastic systems. Different modelling techniques have been developed as well as mathematical techniques for formalizing the cause-effect relationships in industrial and complex systems. The methodology in this book illustrates how complexity in modelling can be tackled by the use of coloured petri nets, while at the same time the variability present in systems is integrated in a robust fashion. The book can be used as a concise guide for developing robust models, which are able to efficiently simulate the cause-effect relationships present in complex industrial systems without losing the simulation power of discrete-event simulation. In addition SIMIO’s capabilities allows integration of features that are becoming more and more important for the success of projects such as animation, virtual reality, and geographical information systems (GIS).

Modelling and Simulation of Sheet Metal Forming Processes
Modelling and Simulation of Sheet Metal Forming Processes

Author: Marta C. Oliveira

Publisher: MDPI

Published: 2020-04-22

Total Pages: 254

ISBN-13: 3039285564

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The numerical simulation of sheet metal forming processes has become an indispensable tool for the design of components and their forming processes. This role was attained due to the huge impact in reducing time to market and the cost of developing new components in industries ranging from automotive to packing, as well as enabling an improved understanding of the deformation mechanisms and their interaction with process parameters. Despite being a consolidated tool, its potential for application continues to be discovered with the continuous need to simulate more complex processes, including the integration of the various processes involved in the production of a sheet metal component and the analysis of in-service behavior. The quest for more robust and sustainable processes has also changed its deterministic character into stochastic to be able to consider the scatter in mechanical properties induced by previous manufacturing processes. Faced with these challenges, this Special Issue presents scientific advances in the development of numerical tools that improve the prediction results for conventional forming process, enable the development of new forming processes, or contribute to the integration of several manufacturing processes, highlighting the growing multidisciplinary characteristic of this field.

Process Modelling and Simulation
Process Modelling and Simulation

Author: César de Prada

Publisher: MDPI

Published: 2019-09-23

Total Pages: 298

ISBN-13: 3039214551

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Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Robust Model Predictive Control for Large-Scale Manufacturing Systems subject to Uncertainties
Robust Model Predictive Control for Large-Scale Manufacturing Systems subject to Uncertainties

Author: Jens Tonne

Publisher: kassel university press GmbH

Published: 2018-01-19

Total Pages: 251

ISBN-13: 3737604487

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Large scale manufacturing systems are often run with constant process parameters although continuous and abrupt disturbances influence the process. To reduce quality variations and scrap, a closed-loop control of the process variables becomes indispensable. In this thesis, a modeling and control framework for multistage manufacturing systems is developed, in which the systems are subject to abrupt faults, such as component defects, and continuous disturbances. In this context, three main topics are considered: the development of a modeling framework, the design of robust distributed controllers, and the application of both to the models of a real hot stamping line. The focus of all topics is on the control of the product properties considering the available knowledge of faults and disturbances.

Discrete Choice Methods with Simulation
Discrete Choice Methods with Simulation

Author: Kenneth Train

Publisher: Cambridge University Press

Published: 2009-07-06

Total Pages: 399

ISBN-13: 0521766559

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This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

Vehicle-Manipulator Systems
Vehicle-Manipulator Systems

Author: Pål Johan From

Publisher: Springer Science & Business Media

Published: 2013-10-02

Total Pages: 402

ISBN-13: 1447154630

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Furthering the aim of reducing human exposure to hazardous environments, this monograph presents a detailed study of the modeling and control of vehicle-manipulator systems. The text shows how complex interactions can be performed at remote locations using systems that combine the manipulability of robotic manipulators with the ability of mobile robots to locomote over large areas. The first part studies the kinematics and dynamics of rigid bodies and standard robotic manipulators and can be used as an introduction to robotics focussing on robust mathematical modeling. The monograph then moves on to study vehicle-manipulator systems in great detail with emphasis on combining two different configuration spaces in a mathematically sound way. Robustness of these systems is extremely important and Modeling and Control of Vehicle-manipulator Systems effectively represents the dynamic equations using a mathematically robust framework. Several tools from Lie theory and differential geometry are used to obtain globally valid representations of the dynamic equations of vehicle-manipulator systems. The specific characteristics of several different types of vehicle-manipulator systems are included and the various application areas of these systems are discussed in detail. For underwater robots buoyancy and gravity, drag forces, added mass properties, and ocean currents are considered. For space robotics the effects of free fall environments and the strong dynamic coupling between the spacecraft and the manipulator are discussed. For wheeled robots wheel kinematics and non-holonomic motion is treated, and finally the inertial forces are included for robots mounted on a forced moving base. Modeling and Control of Vehicle-manipulator Systems will be of interest to researchers and engineers studying and working on many applications of robotics: underwater, space, personal assistance, and mobile manipulation in general, all of which have similarities in the equations required for modeling and control.

Modeling, Control, and Optimization of Natural Gas Processing Plants
Modeling, Control, and Optimization of Natural Gas Processing Plants

Author: William A. Poe

Publisher: Gulf Professional Publishing

Published: 2016-09-09

Total Pages: 302

ISBN-13: 0128029811

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Modeling, Control, and Optimization of Natural Gas Processing Plants presents the latest on the evolution of the natural gas industry, shining a light on the unique challenges plant managers and owners face when looking for ways to optimize plant performance and efficiency, including topics such as the various feed gas compositions, temperatures, pressures, and throughput capacities that keep them looking for better decision support tools. The book delivers the first reference focused strictly on the fast-growing natural gas markets. Whether you are trying to magnify your plants existing capabilities or are designing a new facility to handle more feedstock options, this reference guides you by combining modeling control and optimization strategies with the latest developments within the natural gas industry, including the very latest in algorithms, software, and real-world case studies. - Helps users adapt their natural gas plant quickly with optimization strategies and advanced control methods - Presents real-world application for gas process operations with software and algorithm comparisons and practical case studies - Provides coverage on multivariable control and optimization on existing equipment - Allows plant managers and owners the tools they need to maximize the value of the natural gas produced

Robust Model-Based Fault Diagnosis for Dynamic Systems
Robust Model-Based Fault Diagnosis for Dynamic Systems

Author: Jie Chen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 370

ISBN-13: 1461551498

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There is an increasing demand for dynamic systems to become more safe and reliable. This requirement extends beyond the normally accepted safety-critical systems of nuclear reactors and aircraft where safety is paramount important, to systems such as autonomous vehicles and fast railways where the system availability is vital. It is clear that fault diagnosis (including fault detection and isolation, FDI) has been becoming an important subject in modern control theory and practice. For example, the number of papers on FDI presented in many control-related conferences has been increasing steadily. The subject of fault detection and isolation continues to mature to an established field of research in control engineering. A large amount of knowledge on model-based fault diagnosis has been ac cumulated through the literature since the beginning of the 1970s. However, publications are scattered over many papers and a few edited books. Up to the end of 1997, there is no any book which presents the subject in an unified framework. The consequence of this is the lack of "common language", dif ferent researchers use different terminology. This problem has obstructed the progress of model-based FDI techniques and has been causing great concern in research community. Many survey papers have been published to tackle this problem. However, a book which presents the materials in a unified format and provides a comprehensive foundation of model-based FDI is urgently needed.

Improving Fish Stock Assessments
Improving Fish Stock Assessments

Author: National Research Council

Publisher: National Academies Press

Published: 1998-02-27

Total Pages: 194

ISBN-13: 0309174406

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Ocean harvests have plateaued worldwide and many important commercial stocks have been depleted. This has caused great concern among scientists, fishery managers, the fishing community, and the public. This book evaluates the major models used for estimating the size and structure of marine fish populations (stock assessments) and changes in populations over time. It demonstrates how problems that may occur in fisheries dataâ€"for example underreporting or changes in the likelihood that fish can be caught with a given type of gearâ€"can seriously degrade the quality of stock assessments. The volume makes recommendations for means to improve stock assessments and their use in fishery management.

Applied Simulation Modeling
Applied Simulation Modeling

Author: Andrew F. Seila

Publisher: Cengage Learning

Published: 2003

Total Pages: 504

ISBN-13:

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APPLIED SIMULATION MODELING provides the student with both a conceptual introduction to the concepts of simulation modeling and practical experience with real examples using popular commercial simulation packages ARENA and @Risk. The coverage includes Risk Simulation, Dynamic Systems, and Discrete Event Simulation models. Throughout the text, the authors show readers how they can use simulation in the context of decision making. Practical examples from Operations Management, Manufacturing, Health Care, and Finance are included throughout to give students an appreciation for the wide scope of application and the robust nature of simulation modeling. Special student editions of ARENA and @Risk are packaged with the text.