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.
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.

Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Optimization
120
Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Optimization
120Related collections and offers
Product Details
ISBN-13: | 9789819726608 |
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Publisher: | Springer Nature Singapore |
Publication date: | 05/16/2024 |
Edition description: | 2024 |
Pages: | 120 |
Product dimensions: | 6.10(w) x 9.25(h) x (d) |