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Research Papers: Design Automation

Resilience Allocation for Early Stage Design of Complex Engineered Systems

[+] Author and Article Information
Nita Yodo

Department of Industrial and
Manufacturing Engineering,
Wichita State University,
Wichita, KS 67206
e-mail: nxyodo1@wichita.edu

Pingfeng Wang

Associate Professor
Department of Industrial and
Manufacturing Engineering,
Wichita State University,
Wichita, KS 67206
e-mail: pingfeng.wang@wichita.edu

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received December 19, 2015; final manuscript received June 10, 2016; published online July 18, 2016. Assoc. Editor: Xiaoping Du.

J. Mech. Des 138(9), 091402 (Jul 18, 2016) (10 pages) Paper No: MD-15-1833; doi: 10.1115/1.4033990 History: Received December 19, 2015; Revised June 10, 2016

The continuous pursuits of developing a better, safer, and more sustainable system have pushed systems to grow in complexity. As complexity increases, challenges consequently arise for system designers in the early design stage to take account of all potential failure modes in order to avoid future catastrophic failures. This paper presents a resilience allocation framework for resilience analysis in the early design stage of complex engineering systems. Resilience engineering is a proactive engineering discipline that focuses on ensuring the performance success of a system by adapting to changes and recovering from failures under uncertain operating environments. Utilizing the Bayesian network (BN) approach, the resilience of a system could be analyzed and measured quantitatively in a probabilistic manner. In order to ensure that the resilience of a complex system satisfies the target resilience level, it is essential to identify critical components that play a key role in shaping the top-level system resilience. Through proper allocation of resilience attributes to these critical components, not only target could resilience requirements be fulfilled, global cascading catastrophic failure effects could also be minimized. An electrical distribution system case study was used to demonstrate the developed approach, which can also be used as a fundamental methodology to quantitatively evaluate resilience of engineered complex systems.

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Figures

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Fig. 1

Various levels of resiliency in a system over time

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Fig. 2

Resilience allocation for engineering systems

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Fig. 3

General BN structure for resilience quantification

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Fig. 4

Basic system structures

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Fig. 5

Flowchart of the resilience allocation framework

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Fig. 6

General electric power distribution structure

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Fig. 7

2015 Kansas net electricity generation in December 2015 [50]

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Fig. 8

BN model for electric distribution system

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Fig. 9

Critical components observed

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Fig. 10

Resilience level when there were failures observed for distribution center 1

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Fig. 11

Resilience allocation structure for electric distribution system

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