Abstract: A prognostics analysis software module is embedded in a programmable logic controller (PLC) software platform. During cycling of the PLC real-time operating program, data is read from sensors and written to a buffer only when the prognostics analysis software module is idle. The prognostics analysis software module is then activated by a system function block of the PLC software platform. Before determining any prognostic information, prediction models within the prognostics analysis software module are automatically trained using features extracted from the sensor data.

Abstract: A method for computer-aided analysis of an automation system, where the automation system executes a number of jobs, each job being performed repetitively, wherein the execution durations of a respective job of the number of jobs for several repetitions of the respective job is determined to produce a plurality of execution durations, a statistical analysis on the plurality of execution durations is performed to produce at least one statistical quantity valid for the plurality of execution durations, and an action is performed for protecting the automation system and/or for generating a warning if a condition indicating an incorrect execution of the respective job is fulfilled for at least one statistical quantity.

Abstract: A prognostics analysis software module is embedded in a programmable logic controller (PLC) software platform. During cycling of the PLC real-time operating program, data is read from sensors and written to a buffer only when the prognostics analysis software module is idle. The prognostics analysis software module is then activated by a system function block of the PLC software platform. Before determining any prognostic information, prediction models within the prognostics analysis software module are automatically trained using features extracted from the sensor data.

Abstract: A method for estimating a remaining useful life of a system includes monitoring sensor data from sensors deployed within a system. A plurality of features are extracted from the sensor data. Tree graphs are generated including mathematical operators and features as nodes and a advanced feature is produced from each of the tree graphs by transforming the tree graphs into equations. A recursive operation including analyzing a fitness of each of the advanced features, performing crossover/mutation on the tree graphs, producing advanced features from the altered tree graphs, and analyzing the fitness of the altered tree graphs to produce at least one final advanced feature is performed. A remaining useful life of the system is calculated based on the final advanced feature.