Active Robust Optimization Optimizing For Robustness Of Changeable Products


Download Active Robust Optimization Optimizing For Robustness Of Changeable Products PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Active Robust Optimization Optimizing For Robustness Of Changeable Products book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.

Download

Active Robust Optimization: Optimizing for Robustness of Changeable Products


Active Robust Optimization: Optimizing for Robustness of Changeable Products

Author: Shaul Salomon

language: en

Publisher: Springer

Release Date: 2019-07-06


DOWNLOAD





This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a “changeable product,” the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these ‎with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.

Active Robust Optimization: Optimizing for Robustness of Changeable Products


Active Robust Optimization: Optimizing for Robustness of Changeable Products

Author: Shaul Salomon

language: en

Publisher:

Release Date: 2019


DOWNLOAD





This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a "changeable product," the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.

Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Optimization


Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Optimization

Author: Maosheng Zheng

language: en

Publisher: Springer Nature

Release Date: 2024-05-15


DOWNLOAD





This book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment. It aims to provide a new idea and novel way to robust design and assessment of product and production and relevant problems. Robust design and assessment of product and production is attractive to both customer and producer since the stability and insensitivity of a product’s quality to uncontrollable factors reflect its value. Taguchi method has been used to conduct robust design and assessment of product and production for half a century, but its rationality is criticized by statisticians due to its casting of both mean value of a response and its dispersion into one index, which doesn’t characterize the issue of simultaneous optimization of above two independent sub-responses sufficiently for robust design, so an appropriate approach is needed. The preference or role of a response in the evaluation is indicated by using preferable probability as the unique index. Thus, the rational approach for robust design and assessment of product and production is formulated by means of probabilistic multi-objective optimization, which reveals the simultaneous optimization of both mean value of a response and its dispersion in manner of joint probability. Besides, defuzzification and fuzzification measurements are involved as preliminary approaches for robust assessment, the latter provides miraculous treatment for the 'target the best' case flexibly.