A method of monitoring an electrical machine, wherein the method includes: a) obtaining temperature measurement values of the temperature at a plurality of locations of the electrical machine, b) obtaining estimated temperatures at the plurality of locations given by a thermal model of the electrical machine, the thermal model including initial weight parameter values, c) minimizing a difference between the temperature measurement values and the estimated temperatures by finding optimal weight parameter values, d) storing the initial weight parameter values to thereby obtain a storage of used weight parameter values, and updating the optimal weight parameter values as new initial weight parameter values, and repeating steps a)-d) over and over during operation of the electrical machine.

An abnormal irregularity cause identifying device includes a process data acquisition unit that reads, from a storage device storing process data, the pieces of process data, an abnormality determination unit that calculates an abnormality degree representing an extent of an irregularity of process data of the pieces of process data read by the process data acquisition unit, and a cause diagnosis unit that determines, for each of the pieces of process data output by the corresponding one of the plurality of sensors, whether the abnormality degree calculated by the abnormality determination unit satisfies a predetermined criterion by using causal relation information defining a combination of a causal relation between a cause and the irregularity, which appears as an influence resulting from the cause, of the process data output by each of the plurality of sensors in a hierarchical manner along time series.

An industrial integrated development environment (IDE) supports collaborative tools that allow multiple designers and programmers to remotely submit design input to the same automation system project in parallel while maintaining project consistency. The industrial IDE also permits localized development of system projects, and provides an infrastructure for intelligently brokering between conflicting edits submitted to common portions of the system project. Project edits submitted to the IDE system, both applied and unapplied, are stored as edit records, allowing edits to be selectively undone or applied either manually or as part of a rollback to a milestone version.

According to an embodiment, an information processing device includes one or more processors configured to: extract a first subgraph indicating a connection relation of a first node that matches with a schema in which a connection relation between nodes is defined, among first nodes included in a first graph indicating a connection relation of the first nodes each associated with an attribute; determine a template that is output by a first model by inputting input information based on the first subgraph to the first model, the first model being learned to input the input information based on a subgraph indicating a connection relation between the nodes and to output the template of a formula; and set one of the attributes associated with the first nodes as the variable to be used in the determined template to generate the formula.

An approach for providing solutions to ad in the process recovery in manufacturing systems to resume manufacturing activity is disclosed. The outcome of the approach can include the following advantages, minimizing waste, reducing cost of recovery, and increasing efficiency in a manufacturing process. The approach includes collecting initial factory data; identifying and categorizing one or more shop floor activities; determining initial recovery process; creating a digital twin copy of the factory; performing one or more initial simulation scenarios; generating factory improvement plan; and executing factory improvement plan.

The invention relates to an industrial process controller comprising at least three field devices coupled to one another by means of a data link, with the field devices controlling and/or monitoring an industrial process, wherein the field devices are configured to store a block chain, wherein the block chain comprises a plurality of blocks, and wherein the blocks store use data. The process controller is characterized in that the field devices are configured to delete one or more blocks from the block chain and to adapt the block chain to the change caused by the deletion.

This invention describes a method for detecting a misconfiguration of a machine function of a first industrial machine (M1). A set (N) of second industrial machines (MS) from said several other industrial machines (MO) is created by identifying a predetermined feature of the first industrial machine (M1) in several other industrial machines (MO). A first configuration value is created, which relates to the machine function of the first industrial machine (M1), and a second configuration value is created which relates to the machine function of the second industrial machines (MS). Depending on a relation of the first configuration value to the second configuration value a deviation value is determined by a configuration anomaly detection module (CADM). For detecting the misconfiguration of the first industrial machine (M1) the deviation value is compared with a predetermined threshold value.

Methods and systems for detecting and correcting anomalies includes generating historical binary codes from historical time series segments. The historical time series segments are each made up of measurements from respective sensors. A latest binary code is generated from a latest time series segment. It is determined that the latest time series segment represents anomalous behavior, based on a comparison of the latest binary code to the historical binary codes. The sensors are ranked, based on a comparison of time series data of the sensors in the latest time series segment to respective time series data of the historical time series, to generate a sensor ranking. A corrective action is performed responsive to the detected anomaly, prioritized according to the sensor ranking.

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 production management system is capable of detecting an abnormal tendency in a production line device forming a production line and finding out a trouble of the production line device at an early stage. The production management system includes a weighing device and a packaging device which are production line devices, an inspection device, and a host computer. The production line devices, the inspection device, and the host computer are configured to communicate with each other via a network. The inspection device transmits inspection result information in the own device to the host computer. The weighing device and the packaging device transmit processing result information in the own devices to the host computer. The host computer detects the abnormal tendency of the production line device based on the inspection result information and/or the processing result information and outputs an alarm.