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

2025-01-26

AI Summary

Modeling bidirectional dynamic causal risk relationships in complex engineering design remains challenging due to inherent nonlinearity, temporal evolution, and expert knowledge heterogeneity. Method: This paper proposes Token-FCM, a novel risk assessment method that (i) introduces a token-based mechanism to enhance the dynamic evolutionary modeling capability of Fuzzy Cognitive Maps (FCMs), and (ii) integrates fuzzy set theory with group decision-making—specifically the Delphi method and fuzzy comprehensive evaluation—to enable multi-source expert knowledge-driven risk quantification. Contribution/Results: Evaluated on an engine design case for horizontal directional drilling rigs, Token-FCM achieves a 23.6% improvement in risk identification accuracy. It significantly enhances interpretability and traceability of dynamic risk propagation paths. The approach establishes a new paradigm for dynamic risk modeling in complex engineering systems, balancing theoretical rigor with practical applicability.

Technology Category

• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty
• Knowledge Representation and Reasoning: Knowledge Engineering
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

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.

Problem

• Complex Engineering Design
• Risk Assessment
• Economic Loss Prevention

Innovation

• Token-FCM
• Fuzzy C-Means Clustering
• Risk Assessment in Engineering Design