Risk assessment on multimodal transport network based on quality function deployment

Abstract

As a necessary work before risk prevention and control, risk assessment has become increasingly important in multimodal transport networks. On the basis of the idea of quality function deployment (QFD), this paper combines fuzzy G1 method, two-tuple linguistic representation model, and dynamic intuitionistic fuzzy multi-attribute evaluation method to propose a new method for risk assessment. QFD is innovatively used to create an overall framework, which includes the basic importance rating of risk factors, the correlation between risk factors and network failures, the importance rating of network failures, and the comprehensive importance rating of risk factors. The comprehensive importance rating is regarded as an indicator to verify, improve, and modify the basic importance rating, which can make up for the disadvantage of the existing risk assessment methods in proving the credibility of the results. Its result is the key to judging the degree of influence of risk factors on network operation. This paper takes the multimodal transport network in the Sichuan-Tibet region of China as an example for analysis. The results are analyzed and discussed to prove the validity and advancement of the proposed method.

Hypergraph and network flow-based quality function deployment

“…The fuzzy approach of QFD has been applied in several fields [40] , which perspective allows to cope with uncertainties associated with inputs while translating customer voice into engineering specifications [41] . The fuzzy QFD approach has been utilized, for example, in the enhancement of electric vehicles' market competitiveness [42] , in risk assessment on multimodal transport network [43] , in sustainable design of consumer electronics products [41] , or in planning for sustainable stakeholder engagement based on the assessment of conflicting interests in projects by utilizing cascade of houses approach [44] . Furthermore, a method based on picture fuzzy linguistic sets and evaluation based on distance from average solution has been developed to improve the efficiency and effectiveness of QFD in prioritizing engineering characteristics [45] .…”

Applying Integrated QFD-MCDM Approach to Strengthen Supply Chain Agility for Mitigating Sustainable Risks

“…He et al (2021) developed a hybrid approach to Kano-DEMATEL-QFD that achieved optimal resilient solutions for maximum customer satisfaction and SSCR mitigation at a minimum investment cost [152]. Guo et al (2021) proposed a new risk assessment method by combining QFD with the fuzzy G1 method, dual tuple language representation model and dynamic intuitionistic fuzzy MCDM to judge the impact of risk factors on network operation [153]. Hsu et al (2021) discussed the risk mitigation methods that can maximize the resilience of sustainable supply chains for garment companies based on QFD combined with MCDM [15].…”