Integrated Reliable and Robust Design

Integrated Reliable and Robust Design
Author :
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Total Pages : 130
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ISBN-10 : OCLC:785221670
ISBN-13 :
Rating : 4/5 (70 Downloads)

Book Synopsis Integrated Reliable and Robust Design by : Gowrishankar Ravichandran

Download or read book Integrated Reliable and Robust Design written by Gowrishankar Ravichandran and published by . This book was released on 2011 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The objective of this research is to develop an integrated design methodology for reliability and robustness. Reliability-based design (RBD) and robust design (RD) are important to obtain optimal design characterized by low probability of failure and minimum performance variations respectively. But performing both RBD and RD in a product design may be conflicting and time consuming. An integrated design model is needed to achieve both reliability and robustness simultaneously. The purpose of this thesis is to integrate reliability and robustness. To achieve this objective, we first study the general relationship between reliability and robustness. Then we perform a numerical study on the relationship between reliability and robustness, by combining the reliability based design, robust design, multi objective optimization and Taguchi's quality loss function to formulate an integrated design model. This integrated model gives reliable and robust optimum design values by minimizing the probability of failure and quality loss function of the design simultaneously. Based on the results from the numerical study, we propose a generalized quality loss function that considers both the safe region and the failure region. Taguchi's quality loss function defines quality loss in the safe design region and risk function defines quality loss in the failure region. This integrated model achieves reliability and robustness by minimizing the general quality loss function of the design. Example problems show that this methodology is computationally efficient compared to the other optimization models. Results from the various examples suggest that this method can be efficiently used to minimize the probability of failure and the total quality loss of a design simultaneously"--Abstract, p. iii.


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