A Token-FCM based risk assessment method for complex engineering designs

TL;DR

This paper introduces a novel Token-FCM risk assessment method that models dynamic causal-effect relations in complex engineering designs, enhancing accuracy through fuzzy sets and group decision-making, demonstrated on an engine design case.

Contribution

It proposes a new Token-FCM approach combining fuzzy cognitive maps with token mechanisms for dynamic risk assessment in complex engineering systems.

Findings

Effective risk assessment demonstrated on engine design case

Enhanced modeling of dynamic causal relations in engineering risks

Improved accuracy through fuzzy sets and group decision-making

Abstract

Engineering design risks could cause unaffordable losses, and thus risk assessment plays a critical role in engineering design. On the other hand, the high complexity of modern engineering designs makes it difficult to assess risks effectively and accurately due to the complex two-way, dynamic causal-effect risk relations in engineering designs. To address this problem, this paper proposes a new risk assessment method called token fuzzy cognitive map (Token-FCM). Its basic idea is to model the two-way causal-risk relations with the FCM method, and then augment FCM with a token mechanism to model the dynamics in causal-effect risk relations. Furthermore, the fuzzy sets and the group decision-making method are introduced to initialize the Token-FCM method so that comprehensive and accurate risk assessments can be attained. The effectiveness of the proposed method has been demonstrated by a real example of engine design for a horizontal directional drilling machine.