The invention regards a system reliability or failure predicting apparatus and method that incorporates known information about system component failure into a system model and uses the model with or without other acquired system data to predict the probability of system failure. An embodiment of the method includes using probabilistic methods to create a system failure model from the failure models of individual system components, predicting the failure of the system based on the component models and system data, ranking the sensitivity of the system to the system variables, and communicating a failure prediction.
Methods, systems, and articles of manufacture consistent with the present invention provide for predicting system failure based on pattern recognition of subcomponent exposure to failure. A dataset is generated that has at least one exposure level to failure of a computer-based system and a corresponding rule identifier of a rule used to calculate the exposure level. The rule asynchronously receives information about the computer-based system and calculates the exposure level based on the received information. The generated dataset is compared to a previously generated dataset by comparing the at least one exposure level of the dataset to an at least one exposure level with the same rule identifier in the previously generated dataset, where the previously generated dataset is associated with a known problem with the computer-based system. A probability of a problem with the computer-based system is calculated based on a number of exposure levels in the generated dataset matching exposures levels in the previously generated dataset.
A method, a software product and a system for distinguishing effects due to bifurcation from effects due to design variable changes in finite element analysis is disclosed. According to one aspect of the invention, 1) a plurality of design experiments is analyzed with finite element analysis (FEA) software; 2) a metamodel is constructed from the FEA responses using the least squares fitting technique; 3) any FEA response that is not predicted by the metamodel is classified as outlier, which is the high likelihood candidate for bifurcation; and 4) verification of the bifurcation is then to be confirmed. The method is implemented in a design and probabilistic analysis software product.
Methods, systems, and articles of manufacture consistent with the present invention provide for managing exposure to failure for computer-based systems. Information about a computer-based system is asynchronously received. An exposure level to failure of the computer-based system is calculated based on the received information. A stability of the computer-based system is determined based on the exposure level. A stability indication is output responsive to the determined stability.
Methods, systems, and articles of manufacture consistent with the present invention provide for managing and predicting risk for computer-based systems. Information about a computer-based system is asynchronously received. A risk level at which the computer-based system operates is calculated based on the received information.
An integrated circuit is designed to improve yield when manufacturing the integrated circuit, by obtaining a design element from a set of design elements used in designing integrated circuits. A variant design element is created based on the obtained design element, where a feature of the obtained design element is modified to create the variant design element. A yield to area ratio for the variant design element is determined. If the yield to area ratio of the variant design element is greater than a yield to area ratio of the obtained design element, the variant design element is retained to be used in designing the integrated circuit.
