An integrated QFD and FMEA approach to identify risky components of products

Abstract

Identifying risk components is crucial to improve product quality. Failure mode and effects analysis as a useful risk assessment method has become a prevalent application in product design. However, the critical data, which contain failure causality relationships (FCRs) between failure modes, importance correlations among risk factors, and customer requirements of the product component, are not considered. This study develops an integrated approach for identifying risky components considering customer requirements and FCRs. First, a quality function deployment is established to characterize the customer requirements under fuzzy assessment semantics. Second, the FCRs between and within the product components are characterized by a directed network model. In this network, the failure modes are modelled as vertices, and the causality relationships between the failure modes are modelled as directed edges. The values of the directed edges are characterized by weighted risk priority numbers, and the weight of risk factors is optimized by a nonlinear programming model. Then, the interactive relationships among failure modes between and within product components are characterized by the internal failure effect and external failure effect. Finally, a real-world case application of wheel loader is conducted to demonstrate the validity and feasibility of the proposed approach. The results have shown that the proposed method is more effective in identifying risk components.