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Research Papers: Design Automation

Redundancy Allocation for Reliability Design of Engineering Systems With Failure Interactions

[+] Author and Article Information
Jing Wang

University of Michigan-Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
800 Dong Chuan Road,
Shanghai 200240, China
e-mail: wangjingsjtu@163.com

Mian Li

University of Michigan-Shanghai Jiao Tong
University Joint Institute,
Shanghai Jiao Tong University,
800 Dong Chuan Road,
Shanghai 200240, China
e-mail: mianli@sjtu.edu.cn

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received May 13, 2014; final manuscript received November 25, 2014; published online January 9, 2015. Assoc. Editor: David Gorsich.

J. Mech. Des 137(3), 031403 (Mar 01, 2015) (8 pages) Paper No: MD-14-1283; doi: 10.1115/1.4029320 History: Received May 13, 2014; Revised November 25, 2014; Online January 09, 2015

Optimal allocation of redundancies is one of the most important ways of improving system reliability. Generally, in these redundancy allocation problems, it is assumed that failures of components are independent. However, under this assumption failure rates can be underestimated since failure interactions can significantly affect the performance of systems. In this paper, we first propose an analytical model to describe the failure rates with failure interactions, followed by a modified analytical hierarchy process (MAHP) which is proposed to solve redundancy allocation problems with failure interactions. MAHP decomposes the system into several blocks and deals with those downsized blocks before diving deep into the most appropriate component for redundancy allocation. Being simple and flexible, MAHP provides an intuitive way to design a complex system and the explicit function of the entire system reliability is not required in the proposed approach. More importantly, with the help of the proposed analytical failure interaction model, MAHP can capture the effect of failure interactions. Results from case studies clearly demonstrate the applicability of the analytical model for failure interactions and MAHP for reliability design.

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Figures

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Fig. 1

Flowchart of AHP process

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Fig. 2

Component A with its redundancies treated as one component

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Fig. 3

Comparison matrix and criteria weights

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Fig. 4

Reliability and cost calculation, first round of MAHP

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Fig. 5

Comparison matrix under criterion reliability

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Fig. 6

Comparison matrix under criterion cost

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Fig. 7

Global scores during first round of MAHP

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Fig. 8

Reliability and cost after first round of MAHP

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Fig. 9

Global scores for second round of MAHP

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Fig. 10

Reliability and cost after second round of MAHP

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Fig. 11

Final system of series structure

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Fig. 12

Reliability and cost calculation, first round of MAHP

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Fig. 13

System and global score, second round of MAHP

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Fig. 14

System for the third round of MAHP

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Fig. 15

Series–parallel structure

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Fig. 16

Reliability, cost and global scores of two blocks before first round of MAHP

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Fig. 17

Global scores of components in block 2 in first round of MAHP

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Fig. 18

Final system scheme

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Fig. 19

Parallel–series structure

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Fig. 20

System before first round of MAHP

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Fig. 21

Global scores of components in block 1, first round of MAHP

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Fig. 24

System for the first round of MAHP

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