Some implementations of the disclosure are directed to tapping input/output (I/O) data from an industrial control system (ICS) or applying the tapped I/O data to a learned model to perform predictive or prescriptive maintenance. In one implementation, a method comprises: tapping I/O data from a controller of an ICS while the controller executes first control code to control one or more devices of the ICS; transmitting the tapped I/O data over a network to a second system; and executing, via the second system, second control code comprising an original or modified version of all or a subset of the first control code of the ICS, wherein the second control code executes in response to receiving the tapped I/O data. The output of executing the second control code may be provided to a model to predict a future event involving the ICS or to prescribe maintenance of the ICS.

Systems and methods provide techniques for performing predictive maintenance data analysis based on telemetry data. In one embodiments, a method includes at least operations configured to obtain a training telemetry data object, determine a training input data object based on the training telemetry data object, obtain a maintenance data object, and generate a trained predictive maintenance convolutional neural network based on the training input data object and the maintenance data object. The trained predictive maintenance convolutional neural network can be utilized to generate maintenance predictions for a monitored system. The maintenance prediction can include data objects with visual explanatory capabilities, such as data objects that describe heatmaps over input telemetry data.

An actuator for controlling a flow regulation device. The actuator includes a drive device coupled to the flow regulation device and a motor coupled to the drive device and operable to move the drive device. The actuator further includes a processing circuit configured to receive a first measurement of a characteristic, control the actuator to reposition the flow regulation device in a first direction, receive a second measurement of the characteristic, determine an installation error associated with at least one of the actuator and the flow regulation device based on the first measurement and the second measurement.

A method and system for reliability reporting for electrical hardware can involve analyzing stress data referenced to a predicted reliability of electrical hardware, the stress data including real-time stress information related to the electrical hardware. Reliability data associated with the electrical hardware based on the real-time information and the predicted reliability of the electrical hardware can be calculated. The reliability data can be presented in a graphical user interface that displays indicators of the reliability data including runtime data associated with the electrical hardware.

Predictive maintenance methods and systems, including a method of applying transfer entropy techniques to find a causal link between parameters; a method of applying quality weighting to context data based on a priori knowledge of the accuracy of the context data; a method of detecting a maintenance action from parameter data by detecting a step and a process capability improvement; a method of managing unattended alerts by considering cost/benefit of attending to one or more alerts over time and assigning alert expiry time and/or ranking the alerts accordingly; a method of displaying components of a complex system in a functional way enabling improvements in system diagnostics; a method of determining the time of an event indicator in time series parameter data; a method of classifying an event associated with a fault condition occurring within a system; and a method of determining whether an event recorded in parameter data is attributable to an external factor.

A control system for evaluating residual operating life of a machine component of a machine tool includes a sensor and a control system. The sensor is disposed on the machine tool and is configured to sense movement of the machine component. The control device is configured to calculate a length of time based on a sense signal received from the sensor and sampled at a time point right after the machine component is freshly oiled, and to enable output of an alarm when determining that the length of time thus calculated is smaller than a predetermined length.

The present invention discloses methods and systems for improving asset operation based on identification of significant changes in sensor combinations in related events. Methods include the steps of: providing an asset representation of an asset having an alert-aggregation system; creating a calculated indicator listing having at least one calculated indicator in the asset configured to calculate, predict, or estimate an indicated asset behavior; incorporating the calculated indicator listing into a set of entity connections by associating listing elements in the calculated indicator listing, thereby producing the interconnected representation; associating the identified asset behavior with at least one relevant object and/or at least one relevant process that is impairing the asset from optimally performing, conducting, and/or achieving the identified asset behavior; and generating at least one hint associated with at least one relevant object and/or at least one relevant process that is impairing the identified asset behavior.

A system for rule management, predictive maintenance and quality assurance of a process using automatic rule formation comprising a plurality of sensors capable of being attached to at least one machine for measuring at least one information about the process and machine operation. The system comprises a server connected to the sensors over a wireless communication network and running a reconfigurable rule management program for identifying and processing the particular process and machine information related to at least one process received from the plurality of sensors. A controller in communication with the server capable of controlling the process based on a rule set by the rule engine. The rule engine automatically detects the normal process data, classifies the received data based on the dynamic rule formed by the rule engine and finds anomalies in the process or machine operation for predictive maintenance and process quality assurance.

A valve state grasping system, a display device and a rotary valve, a valve state grasping program, a recording medium, and a valve state grasping method that enable efficient valve system monitoring and accumulation of information. The system includes a valve V, a sensor unit, a server including a database, a terminal device including a display unit, and a system control unit. The database includes a position information unit, a history information unit, and an inference information unit. The position information unit includes unique information and pipe attachment information, and the history information unit includes at least measurement information and diagnosis information. The system control unit accumulates information of the position information unit and information of the history information unit in association with each other and outputs predetermined inference information from the inference information unit based on information of the position information unit and information of the history information unit.

A computer-implemented method of maintaining a transport system in a manufacturing facility including: measuring one or more pose-related properties of a plurality of transportation devices at a plurality of manufacturing stations in the manufacturing facility, at which manufacturing stations one or more workpieces are processed; determining a statistical characteristic for each of the plurality of transportation devices based on the pose-related properties; determining a sequence for maintaining one or more transportation devices based on the statistical characteristics; and optionally performing one or more maintenance procedures based on the sequence.