Siemens Aktiengesellschaft

Vidyabhushana Hande

P V Sudev Nair

Sudev Nair

Chethan Ravi B R

Vinay Ramanath

Ankit Vijaysing Ghoti

A system and method for determining optimal computing configuration for executing a computing operation includes defining one or more constrains of a given computing operation to be executed. The method further includes implementing a knowledge graph to determine at least one suitable combination of computing hardware and computing software based on the given computing operation and the defined one or more constrains therefor. The method further includes quantitatively estimating an energy requirement and qualitatively estimating an energy consumption pattern of the determined at least one suitable combination. The method further includes performing a life cycle assessment for execution of the given computing operation utilizing the determined at least one suitable combination of computing hardware and computing software based on the quantitative estimation of the energy requirement and the qualitative estimation of the energy consumption pattern, to determine an optimal combination of computing hardware and computing software therefor.

Method and system for determining optimal computing configuration for executing computing operation

Systems, methods, and control units for diagnosis and life prediction of one or more electro-mechanical system are provided. One method includes receiving sensor data from a plurality of sensors associated with operation of the electro-mechanical system. The method includes determining at least one system response associated with at least one failure mode of the electro-mechanical system from the sensor data, wherein the sensor data is indicative of the at least one failure mode of the electro-mechanical system. The method further includes receiving at least one simulated response associated with the at least one failure mode of the electro-mechanical system, wherein the at least one failure mode is simulated on a system model of the electro-mechanical system. The method includes generating a hybrid model of the electro-mechanical system in real-time based on the at least one system response and the at least one simulated response, wherein the hybrid model combines the at least one system response and the at least one simulated. The method also includes generating a diagnosis of the electro-mechanical system based on the hybrid model, wherein the diagnosis includes identification of one or more failures in the electro-mechanical system and wherein the one or more failures indicates initiation of degradation of the one or more electro-mechanical system. The method includes predicting a life trend of the electro-mechanical system based on the diagnosis.

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Bengaluru, India

Vidyabhushana Hande