A control system for a gas turbine includes a processor. The processor configured to access one or more operating parameters of the gas turbine. The operating parameters are configured to specify how the gas turbine operates. The processor is configured to predict a rate of degradation to one or more parts of a compressor of the gas turbine due to one or more effects on the parts by operating the gas turbine according to the one or more operating parameters. The processor is configured to send an alert to an electronic device based at least in part on the rate of degradation of the compressor.

A system for adaptable trend detection for component condition indicator data includes a sensor operable to measure an operating condition of a vehicle and generate a sensor signal associated with the operating condition and a data server operable to acquire a current condition indicator of a condition indicator set according to the sensor signal, and to determine whether a trend in the condition indicator set is indicated according to at least the current condition indicator, at least one previous condition indicator of the condition indicator set and a volatility of at least a portion of the condition indicator set. The data server is further operable to provide an alert in response to determining that the trend is indicated.

A self-aware machine platform is implemented through analyzing operational data of machining tools to achieve machine tool damage assessment, prediction and planning in manufacturing shop floor. Machining processes are first identified by matching similar processes through an ICP algorithm. Machining processes are further clustered by Hotelling's T-squared statistics. Degradation of the machining tool is detected through a trend of the operational data within a cluster of machining processes by a monotonicity test, and the remaining useful life of the machining tool is predicted through a particle filter by extrapolating the trend under a first-order Markov process. In addition, process anomalies across machines are detected through a combination of outlier detection methods including SOMs, multivariate regression, and robust Mahalanobis distance. Warnings and recommendations are flexibly provided to manufacturing shop floor based on policy choice.

An information provision apparatus whereby information regarding a malfunction or problem that occurred during the use of a prescribed model of home appliance can be shared with users using the same model of home appliance. A device (20) has the following: a presentation-information reception unit (21) that receives presentation information generated by a server (10) and stores the presentation information in a prescribed storage unit; and a presentation unit (22) that presents the presentation information to the user of the device (20), the presentation information having been read out from the aforementioned storage unit. The presentation information indicates malfunctions or problems that occurred in devices that are the same model as the abovementioned device (20) and were being used by other users.

Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve defining and deploying aggregate, predictive models and corresponding workflows, defining and deploying individualized, predictive models and/or corresponding workflows, and dynamically adjusting the execution of model-workflow pairs.

Disclosed herein are systems, devices, and methods related to assets and predictive models and corresponding workflows that are related to the operation of assets. In particular, examples involve defining and deploying aggregate, predictive models and corresponding workflows, defining and deploying individualized, predictive models and/or corresponding workflows, and dynamically adjusting the execution of model-workflow pairs.

A distributed analytics system to control an operation of a monitored system, and method of operation thereof, including an architect subsystem and an edge processing device. The edge subsystem includes an edge processing device associated with the monitored system. The architect subsystem is configured to deploy an analytic model to the edge processing device based on characteristics of the monitored system. The edge processing device is configured to receive the analytic model and independently perform predictive and prescriptive analytics on dynamic input data associated with the monitored system, provide control signals to the monitored system according to the predictive and prescriptive analytics, and provide information to the architect subsystem, including monitored system responses to the control signals. The architect subsystem is configured to modify the analytic model to improve system performance of the monitored system.

An anomality prediction system, which predicts an anomality of a machine, includes: one or more memories; and one or more processors configured to: obtain a state variable including at least one of output data from at least one sensor that detects a state of at least one of the machine or a surrounding environment, internal data of control software controlling the machine, or computational data obtained based on at least one of the output data or the internal data; generate, by inputting the obtained state variable into a machine learning model, a degree of anomality of the machine based on output from the machine learning model; and notify information based on the generated degree of anomality, wherein the notified information includes at least one of the generated degree of anomality at one or more time points, or one or more levels of anomality based on the generated degree of anomality.

An information provision apparatus whereby information regarding a malfunction or problem that occurred during the use of a prescribed model of a home appliance can be shared with users using the same model of the home appliance. A device (20) has the following: a presentation-information reception unit (21) that receives presentation information generated by a server (10) and stores the presentation information in a prescribed storage unit; and a presentation unit (22) that presents the presentation information to the user of the device (20), the presentation information having been read out from the aforementioned storage unit. The presentation information indicates malfunctions or problems that occurred in devices that are the same model as the above-mentioned device (20) and were being used by other users.

A time synchronization signal for time series data collected from multiple controlling devices of a PID process is provided. An assistance device concurrently transmits a time confirmation signal to respective controlling devices in a predetermined time confirmation cycle, and the controlling devices forcibly output time confirmation data for synchronizing control data related to the respective controlling devices with each other as a manipulation variable in one control cycle immediately after receiving the time confirmation signal. The time confirmation data is an irregular value that is not outputted as a value of the manipulation variable in a control cycle during a steady control state.