Advanced Modeling and Optimization of Manufacturing Processes

Advanced Modeling and Optimization of Manufacturing Processes
Author: R. Venkata Rao
Publsiher: Springer Science & Business Media
Total Pages: 388
Release: 2010-12-01
Genre: Technology & Engineering
ISBN: 9780857290151

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Advanced Modeling and Optimization of Manufacturing Processes presents a comprehensive review of the latest international research and development trends in the modeling and optimization of manufacturing processes, with a focus on machining. It uses examples of various manufacturing processes to demonstrate advanced modeling and optimization techniques. Both basic and advanced concepts are presented for various manufacturing processes, mathematical models, traditional and non-traditional optimization techniques, and real case studies. The results of the application of the proposed methods are also covered and the book highlights the most useful modeling and optimization strategies for achieving best process performance. In addition to covering the advanced modeling, optimization and environmental aspects of machining processes, Advanced Modeling and Optimization of Manufacturing Processes also covers the latest technological advances, including rapid prototyping and tooling, micromachining, and nano-finishing. Advanced Modeling and Optimization of Manufacturing Processes is written for designers and manufacturing engineers who are responsible for the technical aspects of product realization, as it presents new models and optimization techniques to make their work easier, more efficient, and more effective. It is also a useful text for practitioners, researchers, and advanced students in mechanical, industrial, and manufacturing engineering.

Optimization of Manufacturing Processes

Optimization of Manufacturing Processes
Author: Kapil Gupta,Munish Kumar Gupta
Publsiher: Springer
Total Pages: 237
Release: 2019-06-25
Genre: Technology & Engineering
ISBN: 9783030196387

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This book provides a detailed understanding of optimization methods as they are implemented in a variety of manufacturing, fabrication and machining processes. It covers the implementation of statistical methods, multi-criteria decision making methods and evolutionary techniques for single and multi-objective optimization to improve quality, productivity, and sustainability in manufacturing. It reports on the theoretical aspects, special features, recent research and latest development in the field. Optimization of Manufacturing Processes is a valuable source of information for researchers and practitioners, as it fills the gap where no dedicated book is available on intelligent manufacturing/modeling and optimization in manufacturing. Readers will develop an understanding of the implementation of statistical and evolutionary techniques for modeling and optimization in manufacturing.

Modeling and Optimization in Manufacturing

Modeling and Optimization in Manufacturing
Author: Catalin I. Pruncu,Jun Jiang
Publsiher: John Wiley & Sons
Total Pages: 338
Release: 2021-07-19
Genre: Technology & Engineering
ISBN: 9783527346943

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Discover the state-of-the-art in multiscale modeling and optimization in manufacturing from two leading voices in the field Modeling and Optimization in Manufacturing delivers a comprehensive approach to various manufacturing processes and shows readers how multiscale modeling and optimization processes help improve upon them. The book elaborates on the foundations and applications of computational modeling and optimization processes, as well as recent developments in the field. It offers discussions of manufacturing processes, including forming, machining, casting, joining, coating, and additive manufacturing, and how computer simulations have influenced their development. Examples for each category of manufacturing are provided in the text, and industrial applications are described for the reader. The distinguished authors also provide an insightful perspective on likely future trends and developments in manufacturing modeling and optimization, including the use of large materials databases and machine learning. Readers will also benefit from the inclusion of: A thorough introduction to the origins of manufacturing, the history of traditional and advanced manufacturing, and recent progress in manufacturing An exploration of advanced manufacturing and the environmental impact and significance of manufacturing Practical discussions of the economic importance of advanced manufacturing An examination of the sustainability of advanced manufacturing, and developing and future trends in manufacturing Perfect for materials scientists, mechanical engineers, and process engineers, Modeling and Optimization in Manufacturing will also earn a place in the libraries of engineering scientists in industries seeking a one-stop reference on multiscale modeling and optimization in manufacturing.

Modeling and Optimization of Advanced Manufacturing Processes

Modeling and Optimization of Advanced Manufacturing Processes
Author: Sumit Bhowmik,Jagadish,Kapil Gupta
Publsiher: Unknown
Total Pages: 135
Release: 2019
Genre: TECHNOLOGY & ENGINEERING
ISBN: 3030000370

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This book covers various multiple-criteria decision making (mcdm) methods for modeling and optimization of advanced manufacturing processes (AMPs). Processes such as non-conventional machining, rapid prototyping, environmentally conscious machining and hybrid machining are finally put together in a single book. It highlights the research advances and discusses the published literature of the last 15 years in the field. Case studies of real life manufacturing situations are also discussed.

Introduction to Computational Optimization Models for Production Planning in a Supply Chain

Introduction to Computational Optimization Models for Production Planning in a Supply Chain
Author: Stefan Voß,David L. Woodruff
Publsiher: Springer Science & Business Media
Total Pages: 239
Release: 2013-06-05
Genre: Business & Economics
ISBN: 9783540247647

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An easy-to-read introduction to the concepts associated with the creation of optimization models for production planning starts off this book. These concepts are then applied to well-known planning models, namely mrp and MRP II. From this foundation, fairly sophisticated models for supply chain management are developed. Another unique feature is that models are developed with an eye toward implementation. In fact, there is a chapter that provides explicit examples of implementation of the basic models using a variety of popular, commercially available modeling languages.

Data Driven Optimization of Manufacturing Processes

Data Driven Optimization of Manufacturing Processes
Author: Kalita, Kanak,Ghadai, Ranjan Kumar,Gao, Xiao-Zhi
Publsiher: IGI Global
Total Pages: 298
Release: 2020-12-25
Genre: Technology & Engineering
ISBN: 9781799872085

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All machining process are dependent on a number of inherent process parameters. It is of the utmost importance to find suitable combinations to all the process parameters so that the desired output response is optimized. While doing so may be nearly impossible or too expensive by carrying out experiments at all possible combinations, it may be done quickly and efficiently by using computational intelligence techniques. Due to the versatile nature of computational intelligence techniques, they can be used at different phases of the machining process design and optimization process. While powerful machine-learning methods like gene expression programming (GEP), artificial neural network (ANN), support vector regression (SVM), and more can be used at an early phase of the design and optimization process to act as predictive models for the actual experiments, other metaheuristics-based methods like cuckoo search, ant colony optimization, particle swarm optimization, and others can be used to optimize these predictive models to find the optimal process parameter combination. These machining and optimization processes are the future of manufacturing. Data-Driven Optimization of Manufacturing Processes contains the latest research on the application of state-of-the-art computational intelligence techniques from both predictive modeling and optimization viewpoint in both soft computing approaches and machining processes. The chapters provide solutions applicable to machining or manufacturing process problems and for optimizing the problems involved in other areas of mechanical, civil, and electrical engineering, making it a valuable reference tool. This book is addressed to engineers, scientists, practitioners, stakeholders, researchers, academicians, and students interested in the potential of recently developed powerful computational intelligence techniques towards improving the performance of machining processes.

Hybrid Modeling and Optimization of Manufacturing

Hybrid Modeling and Optimization of Manufacturing
Author: Ramón Quiza,Omar López-Armas,J. Paulo Davim
Publsiher: Springer Science & Business Media
Total Pages: 99
Release: 2012-02-16
Genre: Computers
ISBN: 9783642280849

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Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

Optimization Models and Concepts in Production Management

Optimization Models and Concepts in Production Management
Author: Bradimaarte
Publsiher: CRC Press
Total Pages: 364
Release: 1995-04-13
Genre: Mathematics
ISBN: 2884490205

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Optimization techniques in production management are becoming increasingly important for efficient and competitive manufacturing. This book presents a collection of tutorial papers by outstanding researchers on the application of optimization concepts. Topics introduced include hierarchical production planning and large scale scheduling, optimal production control, exact and heuristic algorithms for production scheduling and stochastic modelling.