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Advanced Multiresponse Process Optimisation
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Book Synopsis Advanced Multiresponse Process Optimisation by : Tatjana V. Šibalija
Download or read book Advanced Multiresponse Process Optimisation written by Tatjana V. Šibalija and published by Springer. This book was released on 2015-07-25 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi’s quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.
Book Synopsis Efficient Optimization of the Multi-Response Problem in the Taguchi Method Through Advanced Data Envelopment Analysis (DEA) Formulations Integration by : Stelios K. Georgantzinos
Download or read book Efficient Optimization of the Multi-Response Problem in the Taguchi Method Through Advanced Data Envelopment Analysis (DEA) Formulations Integration written by Stelios K. Georgantzinos and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research presents a novel approach for effectively addressing the multi-response problem in the Taguchi Method, a pervasive issue in the production process and productivity index improvement efforts. We achieved this by integrating the Taguchi Method with DEA, transforming experimental trials into Decision Making Units (DMUs) and response variables into inputs and outputs. Subsequently, advanced DEA formulations, like simultaneous DEA and super-efficiency models, were employed to compute the relative and cross efficiencies of the DMUs, leading to a specific combination of multiple control factors at different levels. This method preserves the benefits of the Taguchi Design of Experiments (DoE) while providing an optimal solution for improving multiple quality responses. The Addictive Model for Factor Effects confirmed that our proposed combination delivers superior improvement results when compared to empirical and previous studies' solutions, while also reducing computational effort. The study's findings offer significant implications for advanced manufacturing practices, especially those requiring multi-response optimization.
Book Synopsis Optimization of Dual and Multiple Response Processes by : Shu-Kai Simon Fan
Download or read book Optimization of Dual and Multiple Response Processes written by Shu-Kai Simon Fan and published by . This book was released on 1996 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advanced Optimization for Process Systems Engineering by : Ignacio E. Grossmann
Download or read book Advanced Optimization for Process Systems Engineering written by Ignacio E. Grossmann and published by Cambridge University Press. This book was released on 2021-03-25 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique text covering basic and advanced concepts of optimization theory and methods for process systems engineers. With examples illustrating key concepts and algorithms, and exercises involving theoretical derivations, numerical problems and modeling systems, it is ideal for single-semester, graduate courses in process systems engineering.
Book Synopsis Optimization of Advanced Manufacturing Processes by : Sandip Kunar
Download or read book Optimization of Advanced Manufacturing Processes written by Sandip Kunar and published by CRC Press. This book was released on 2024-11-29 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization for advanced manufacturing processes in fabrication is becoming increasingly important around the world across a range of industries because of its improved productivity, capabilities, efficacy, and sustainability characteristics. This new book explains how to optimize various industrial systems and processes utilizing new significant statistical and evolutionary methodologies. Statistical, multi-criteria decision-making, and evolutionary strategies for single- and multi-objective optimization are covered here, with relevant theoretical details, salient characteristics, implementation processes, effectiveness studies, and results in manufacturing. The chapters present a variety of advanced manufacturing processes and optimization techniques. Processes are described with basic explanations, characteristics, and applications in various technological and biomedical domains. The chapters address the processes prediction of mechanical properties, design and development of tools, impact of power supply, increasing machining precision and efficiency, genetic algorithm optimization, additive manufacturing, and much more. Providing a comprehensive study of advanced manufacturing processes, this volume is a valuable reference for engineers and R&D researchers involved in optimization for advanced manufacturing processes as well as for academics and postgraduate-level students in mechanical engineering, manufacturing engineering, and machining processes.
Book Synopsis Process Optimization by : Enrique del Castillo
Download or read book Process Optimization written by Enrique del Castillo and published by Springer Science & Business Media. This book was released on 2007-09-14 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers several bases at once. It is useful as a textbook for a second course in experimental optimization techniques for industrial production processes. In addition, it is a superb reference volume for use by professors and graduate students in Industrial Engineering and Statistics departments. It will also be of huge interest to applied statisticians, process engineers, and quality engineers working in the electronics and biotech manufacturing industries. In all, it provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization, and more.
Book Synopsis Optimizing Process Robust Design Via Dual Response Optimization by : Ram Arad
Download or read book Optimizing Process Robust Design Via Dual Response Optimization written by Ram Arad and published by . This book was released on 2002 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimization of Process Flowsheets through Metaheuristic Techniques by : José María Ponce-Ortega
Download or read book Optimization of Process Flowsheets through Metaheuristic Techniques written by José María Ponce-Ortega and published by Springer. This book was released on 2018-07-19 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.
Book Synopsis Optimization of Manufacturing Processes by : Kapil Gupta
Download or read book Optimization of Manufacturing Processes written by Kapil Gupta and published by Springer. This book was released on 2019-06-25 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data-Driven Optimization of Manufacturing Processes by : Kalita, Kanak
Download or read book Data-Driven Optimization of Manufacturing Processes written by Kalita, Kanak and published by IGI Global. This book was released on 2020-12-25 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Integrated Process Design and Operational Optimization Via Multiparametric Programming by : Baris Burnak
Download or read book Integrated Process Design and Operational Optimization Via Multiparametric Programming written by Baris Burnak and published by . This book was released on 2020-09-04 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers. In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.
Book Synopsis Optimization in Chemical Engineering by : Suman Dutta
Download or read book Optimization in Chemical Engineering written by Suman Dutta and published by Cambridge University Press. This book was released on 2016-03-11 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, optimization of chemical processes is performed using both classical and advanced algorithms.
Book Synopsis Socio-Inspired Optimization Methods for Advanced Manufacturing Processes by : Apoorva Shastri
Download or read book Socio-Inspired Optimization Methods for Advanced Manufacturing Processes written by Apoorva Shastri and published by Springer Nature. This book was released on 2020-08-11 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses comprehensively the advanced manufacturing processes, including illustrative examples of the processes, mathematical modeling, and the need to optimize associated parameter problems. In addition, it describes in detail the cohort intelligence methodology and its variants along with illustrations, to help readers gain a better understanding of the framework. The theoretical and statistical rigor is validated by comparing the solutions with evolutionary algorithms, simulation annealing, response surface methodology, the firefly algorithm, and experimental work. Lastly, the book critically reviews several socio-inspired optimization methods.
Book Synopsis Probability-Based Multi-objective Optimization for Material Selection by : Maosheng Zheng
Download or read book Probability-Based Multi-objective Optimization for Material Selection written by Maosheng Zheng and published by Springer Nature. This book was released on 2022-08-12 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology, orthogonal experimental design, and uniform experimental design, are all performed; the conditions of the material performance utility with desirable value and robust assessment are included; the discretization treatment of complicated integral in the evaluation is presented. The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone. This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.
Book Synopsis Supply Chain Optimisation by : Alexandre Dolgui
Download or read book Supply Chain Optimisation written by Alexandre Dolgui and published by Springer Science & Business Media. This book was released on 2006-06-18 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects recent results in supply chain optimisation. It presents new approaches and methods based on operations research, artificial intelligence and advanced computing techniques for design of production systems, supply and inventory management, production planning and scheduling, location, transportation and logistics, and simulation in supply flow optimisation. The text presents a wide spectrum of optimisation problems taking into account supply chain paradigms, which are pivotal to improving productivity.
Book Synopsis Nature-Inspired Optimization in Advanced Manufacturing Processes and Systems by : Ganesh M. Kakandikar
Download or read book Nature-Inspired Optimization in Advanced Manufacturing Processes and Systems written by Ganesh M. Kakandikar and published by CRC Press. This book was released on 2020-12-15 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization in Advanced Manufacturing Processes and Systems Subject Guide: Engineering—Industrial and Manufacturing The manufacturing system is going through substantial changes and developments in light of Industry 4.0. Newer manufacturing technologies are being developed and applied. There is a need to optimize these techniques when applied in different circumstances with respect to materials, tools, product configurations, and process parameters. This book covers computational intelligence applied to manufacturing. It discusses nature-inspired optimization of processes and the design and development in manufacturing systems. It explores all manufacturing processes, at both macro and micro levels, and offers manufacturing philosophies. Nonconventional manufacturing, real industry problems and case studies, research on generative processes, and relevance of all this to Industry 4.0, is also included. Researchers, students, academicians, and industry professionals will find this reference title very useful.
Book Synopsis Advanced Engineering Optimization Through Intelligent Techniques by : R. Venkata Rao
Download or read book Advanced Engineering Optimization Through Intelligent Techniques written by R. Venkata Rao and published by Springer. This book was released on 2019-07-09 with total page 861 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises select peer-reviewed papers presented at the International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2018. The book combines contributions from academics and industry professionals, and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, automobile, electrical, chemical, computer and electronics engineering. Different optimization techniques and algorithms such as genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), particle swarm optimization (PSO), artificial bee colony (ABC) algorithm, artificial immune algorithm (AIA), teaching-learning-based optimization (TLBO) algorithm and many other latest meta-heuristic techniques and their applications are discussed. This book will serve as a valuable reference for students, researchers and practitioners and help them in solving a wide range of optimization problems.
