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Robust design and assessment of product and production by means of probabilistic multi-objective optimization

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Robust design and assessment of product and production by means of probabilistic multi-objective optimizationby Maosheng Zheng, Jie Yu.
作者:	Zheng, Maosheng.
其他作者:	Yu, Jie.
出版者:	Singapore :Springer Nature Singapore :2024.
面頁冊數:	x, 120 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Engineering design.
電子資源:	https://doi.org/10.1007/978-981-97-2661-5
ISBN:	9789819726615$q(electronic bk.)

Robust design and assessment of product and production by means of probabilistic multi-objective optimization
Zheng, Maosheng.

Robust design and assessment of product and production by means of probabilistic multi-objective optimization[electronic resource] /by Maosheng Zheng, Jie Yu. - Singapore :Springer Nature Singapore :2024. - x, 120 p. :ill., digital ;24 cm.

Intrinsic Essence of Robust Design -- Relevant Contents of System Theory and Probability Theory -- Concise Description of Probabilistic Multi-objective Optimization from Viewpoint of System Theory -- Robust Design of a Single Objective as Dual Sub-objectives Optimization -- Robust Design and Assessment of Product and Production with Multiple Objectives -- Robust Design with Sequential Uniform Algorithm for Optimization by Means of PMOO -- Robust Design and Assessment of Product and Production with Fuzzy Number -- Concluding Remarks.

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 robust design of above two independent responses sufficiently, 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 robust designs 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.

ISBN: 9789819726615$q(electronic bk.)

Standard No.: 10.1007/978-981-97-2661-5doiSubjects--Topical Terms:

190286
Engineering design.

LC Class. No.: TA174

Dewey Class. No.: 620.0042

Robust design and assessment of product and production by means of probabilistic multi-objective optimization
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520 $a 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 robust design of above two independent responses sufficiently, 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 robust designs 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.
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