A directed failure causality network (DFCN) based method for function components risk prioritization under interval type-2 fuzzy environment. (August 2019)

• Record Type: Journal Article
• Authors: Ma, Hongzhan; Chu, Xuening; Wang, Weizhong; Liu, Xinwang; Xue, Deyi
• Is Part Of: Advanced engineering informatics. Volume 41(2019)
• Publication Date: 2019-08
• Subjects: Interval type-2 fuzzy set -- Directed failure causality network -- Failure risk prioritization -- Product redesign; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2019.100920
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: Presenting a new components risk prioritizing method for product redesign. Developing a directed failure causality network considering failure causalities. Considering both internal and external failure causalities in the network. Applying the interval type-2 fuzzy set to deal with fuzzy uncertainty. Developing an interval type-2 fuzzy permanent function as internal risk index. Abstract: Failure risk prioritization of function components plays a key role in the process to redesign a mechanical product. However, the failure causality relationships (FCRs) among failure modes of components are often ignored in the existing design risk assessment methods, leading to inaccurate risk prioritization results. A failure mode in one component can be the cause of a failure mode in another component, and a failure mode with low chance of failure may result in another failure mode with high chance of failure through propagation among failure modes. Thus, the ultimate effects of each failure mode should be determined by considering the effects of failure propagations. In this research, a directed failure causality network (DFCN) model considering FCRs is proposed to describe the FCRs and to predict risks of the designed product. In addition, uncertainties of linguistic terms in evaluation are also considered in the developed model, because linguistic terms are more suitable and natural than quantitative numbers for design engineers to assess design risks based on their knowledge. To describe these uncertainties, interval type-2 fuzzy set is employed to model the designers' subjective linguistic terms for determining the weights of edges and weights of vertices in the DFCN. A case study for failure risk prioritization of components in redesign of a large tonnage crawler crane (LTCC) is implemented to demonstrate the effectiveness of the proposed method.