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Existing production systems are short of real-time performance status of production process active perception, resulting in the production abnormal conditions processed lag, leading to the frequency problems of deviations in production tasks execution and planning. To address this problem, in this research, an advanced identification technology is extended to the manufacturing field to acquire the...
Importance measures in reliability engineering are used to find the weak areas of a system. Traditional importance measures for binary systems and multi-state systems mainly concern reliability importance of an individual component, and seldom consider the reliability importance of the causal components. This paper constructs the failure importance analysis Bayesian networks (FIABN) to describe the...
A failure prediction Bayesian Networks model (FPBN) is brought forward by expanding the traditional Bayesian network (BN) methodology and tailored to deal with failure prediction problems. In the FPBN model, the classification of network nodes: failure detection nodes, failure cause nodes and failure mode nodes, and the algorithm to initialize orientations of network edges are illustrated. Moreover,...
It is very important for the complex equipment to analyze the importance distribution of failure cause, which can make maintenance experts find the weak point of the equipment for diagnosis and improvement. This paper presents the failure importance analysis models based on the failure importance analysis Bayesian network (FIABN) to calculate the failure causes and modes importance. We adopt the immune...
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