Scheduling in Industry 4.0 and Cloud Manufacturing
Scheduling in Industry 4.0 and Cloud Manufacturing

Author: Boris Sokolov

Publisher: Springer Nature

Published: 2020-06-08

Total Pages: 274

ISBN-13: 3030431770

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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.

Simulation-based Optimization of Energy Efficiency in Production
Simulation-based Optimization of Energy Efficiency in Production

Author: Anna Carina Römer

Publisher: Springer Nature

Published: 2021-02-11

Total Pages: 221

ISBN-13: 3658329718

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The importance of the energy and commodity markets has steadily increased since the first oil crisis. The sustained use of energy and other resources has become a basic requirement for a company to competitively perform on the market. The modeling, analysis and assessment of dynamic production processes is often performed using simulation software. While existing approaches mainly focus on the consideration of resource consumption variables based on metrologically collected data on operating states, the aim of this work is to depict the energy consumption of production plants through the utilization of a continuous simulation approach in combination with a discrete approach for the modeling of material flows and supporting logistic processes. The complex interactions between the material flow and the energy usage in production can thus be simulated closer to reality, especially the depiction of energy consumption peaks becomes possible. An essential step towards reducing energy consumption in production is the optimization of the energy use of non-value-adding production phases.

Simio and Simulation: Modeling, Analysis, Applications
Simio and Simulation: Modeling, Analysis, Applications

Author: Jeffrey S. Smith

Publisher: Createspace Independent Publishing Platform

Published: 2017-05-04

Total Pages: 0

ISBN-13: 9781542933117

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"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." --

Scheduling Algorithms
Scheduling Algorithms

Author: Peter Brucker

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 336

ISBN-13: 3662030888

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Besides scheduling problems for single and parallel machines and shop scheduling problems, the book covers advanced models involving due-dates, sequence dependent change-over times and batching. A discussion of multiprocessor task scheduling and problems with multi-purpose machines is accompanied by the methods used to solve such problems, such as polynomial algorithms, dynamic programming procedures, branch-and-bound algorithms and local search heuristics, and the whole is rounded off with an analysis of complexity issues.

Simulation-Based Optimization
Simulation-Based Optimization

Author: Abhijit Gosavi

Publisher: Springer

Published: 2014-10-30

Total Pages: 530

ISBN-13: 1489974911

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Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

Reconfigurable Manufacturing Systems and Transformable Factories
Reconfigurable Manufacturing Systems and Transformable Factories

Author: Anatoli I. Dashchenko

Publisher: Springer Science & Business Media

Published: 2007-06-08

Total Pages: 763

ISBN-13: 3540293973

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Dear reader! In your hand you have the second book from the series “XXI Century Techno- gies. ” The first book under the title “Manufacturing Technologies for Machines of the Future” was published by “Springer” in 2003. This book is aimed at solving one of the basic problems in the development of modern machine-building – working out of technologies and manufacturing equipment which would promote the continuous development and improvement of the final product design, rapidly “adaptable” to the requirements of the market as for the quantity, quality, and variety of products manufactured with the lowest cost and minimum time and labor of the product process. In this book the problems of theory and practice of development in the reconfigurable manufacturing systems and transformable factories for various machine-building branches with a focus on automotive industry are discussed. The problems concerning the development of a new class of production systems which in comparison to the flexible manufact- ing systems are composed of a far less quantity of machine-tools (reduced cost of production) are discussed. In comparison to the conventional automated lines (dedicated systems) they make it possible to rapidly transform the equipment for new products manufacturing. The book has some advantages concerning the art of scientific ideas and the presentation of developments.

Planning and Scheduling Optimization
Planning and Scheduling Optimization

Author: Farouk Yalaoui

Publisher: Mdpi AG

Published: 2021-11-05

Total Pages: 344

ISBN-13: 9783036523378

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Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development.

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain
Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

Author: Biswajit Sarkar

Publisher: MDPI

Published: 2020-04-23

Total Pages: 618

ISBN-13: 303928522X

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The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment.

High-Performance Simulation-Based Optimization
High-Performance Simulation-Based Optimization

Author: Thomas Bartz-Beielstein

Publisher: Springer

Published: 2019-06-01

Total Pages: 298

ISBN-13: 3030187640

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This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. That’s where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems.

Conditional Monte Carlo
Conditional Monte Carlo

Author: Michael C. Fu

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 411

ISBN-13: 1461562937

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Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied. Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry.