A review of possibilistic approaches to reliability analysis and optimization in engineering design

  • Authors:

  • Li-Ping He;Hong-Zhong Huang;Li Du;Xu-Dong Zhang;Qiang Miao

  • Affiliations:

  • School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning, China;School of Mechatronics Eng., University of Electronic Science and Technology of China, Chengdu, Sichuan, China;School of Mechatronics Eng., University of Electronic Science and Technology of China, Chengdu, Sichuan, China;School of Mechatronics Eng., University of Electronic Science and Technology of China, Chengdu, Sichuan, China;School of Mechatronics Eng., University of Electronic Science and Technology of China, Chengdu, Sichuan, China

  • Venue:
  • HCI'07 Proceedings of the 12th international conference on Human-computer interaction: applications and services
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

A variety of analysis strategies and design methodologies are widely applied to accommodate uncertainties in engineering design. Generally there exist two different types of uncertainties in practice, aleatory uncertainty and epistemic uncertainty. When data and information are very limited, the probabilistic methodology may not be appropriate. Among several alternative tools, possibility theory is proved to be a computationally efficient and stable tool to handle incomplete information. In this paper, we first introduce two issues concerned with possibilistic approaches: reliability analysis and design optimization. Then the type of uncertainties in these issues are explained with emphasis on the epistemic uncertainty. After that, this paper presents both theoretical development and computational improvement of possibility theory in recent years. More details are given to reveal the capability and characteristics of quantified uncertainty from different aspects. In the end, future research directions are summarized.