Product infant failure risk modeling based on quality variation propagation and functional failure dependency

Abstract

Product infant failure is the most crucial part of product quality risk that critically affects customer satisfaction. However, most of manufacturers lack sufficient understanding of the formation mechanism of product infant failure and quantitative infant failure risk modeling technology. These issues cause the inefficiency of warranty policy in preventing and controlling infant failure risk. Therefore, first, on the basis of the reverse mapping process of axiomatic design, an infant failure risk formation chain, that is, “process quality variation—physical defect—functional vulnerability—infant failure,” is proposed in this study by considering quality variation propagation and functional failure dependency to determine the inherent formation and dependent enlarging process of the risk. Second, on the basis of the risk formation chain, the infant failure risk is modeled from inherent risk and dependent risk. Specifically, the inherent infant failure risk is computed based on the stream of quality variation in production, whereas the dependent infant failure risk is computed by a Bayesian network by considering the functional failure dependency. Finally, a case study of an illustrative electromechanical system is introduced to verify the applicability of the proposed method. Result shows that the proposed method has a better performance in infant failure risk modeling.

Conceptual Scheme Decision Model for Mechatronic Products Driven by Risk of Function Failure Propagation

“…Stone et al [7] proposed a function failure design method, and constructed a morphological matrix of function-failure modes, using historical failure data to identify functions with a higher risk of failure; Huang et al [37] used load-strength theory for reliability design at the conceptual design stage. Subsequently, to better assess of the risk of the CS when the function fails, Chen et al [38] analyzed the failure risk based on the functional failure dependency and realized the quantitative risk assessment of the function failure; Yontay and Pan [39] used Bayesian network model to calculate the conditional probability between function and component failure and focused on the core function for risk analysis.…”

Modeling and Analysis of the Reliability of Machining Process of Diesel Engine Blocks Based on PFMECA

“…He et al [6] presented an approach to model the manufacturing system reliability dynamically based on their operation data of process quality and output data of product reliability, and introduced the product qualified probability to quantify the impacts of quality variation in manufacturing process on the reliability of manufacturing system. Chen et al [7] proposed a way to determine the inherent formation and dependent enlarging process of the risk by considering quality variation propagation and functional failure dependency. It modeled from inherent risk and dependent risk on the basis of the risk formation chain.…”