A cell control apparatus comprises an operation information acquisition unit which acquires operation information of manufacturing machine, a failure prediction unit which predicts a failure time of the manufacturing machine based on the operation information of the manufacturing machine, and a replacement time acquisition unit which acquires a replacement time of the component from a component management apparatus. When the failure time is earlier than the replacement time, the cell control apparatus performs a control for reducing an operation load of the manufacturing machine on which a failure of the component is predicted so that the failure time is later than the replacement time.

A method and system for automatically generating interactive wiring diagram in an industrial automation environment are disclosed. The method includes acquiring real-time data associated with devices commissioned in a plant from one or more sensing units disposed at the respective devices. The method also includes determining connections between the devices in the plant based on the acquired real-time data using a lookup table. The method includes generating a wiring diagram of the plant based on the determined connections between the devices. The wiring diagram represents the devices located in the plant and physical connections between the devices. The method includes dynamically generating interactive wiring diagrams by superimposing the wiring diagram with the device connectivity status information associated with respective connections between the devices.

Example embodiments of the present disclosure relate to devices, methods, apparatuses and computer readable storage media of timing synchronization and anomaly detection mechanism. The method comprises: receiving, from a first device, measurement data of an object with data identification information, the first device served by the network device: determining timing information about the measurement data, the timing information indicating a transmission time of the measurement data from the first device: and transmitting the measurement data with the data identification information and the timing information to a wireless controller of the network device for anomaly detection analysis on the object. Using the timing information from the base station as a stable reference time helps to achieve timing synchronization among multiple IoT sensors or field devices. Further, by means of intelligent edge computing, anomaly events occurred or to be occurred at the field devices can be detected in a timely manner.

Methods, apparatus, systems and articles of manufacture are disclosed to improve boundary excursion detection. An example apparatus to improve boundary excursion detection includes a metadata extractor to parse a first control stream to extract embedded metadata, a metadata label resolver to classify a boundary term of the extracted embedded metadata, a candidate stream selector to identify candidate second control streams that include a boundary term that matches the classified boundary term of the first control stream, and a boundary vector calculator to improve boundary excursion detection by calculating a boundary vector factor based on respective ones of the candidate second control streams that include the classified boundary term.

A manufacturing line includes a receiving unit that receives sensor data indicative of a measured value by a sensor provided near a manufacturing device constituting a manufacturing line, a sensor determining unit that determines whether the measured value indicated by the sensor data exceeds a first sensor threshold value indicative of a predetermined range, and a notifying unit that sends a sensor abnormality notification, which notifies a user of the client terminal that the manufacturing device malfunctions, in a case where the sensor determining unit determines that the measured value exceeds the first sensor threshold value.

An operation monitoring device includes an analytical data obtaining unit for obtaining analytical data that contain history information of a machine; a non-operation reason analysis unit for analyzing the state of the machine by classifying the state of the machine for every predetermined time as either of an operating state and a plurality of kinds of non-operating states, based on the analytical data, the operating state being a state in which the machine is operating, and the non-operating states being classified based on a reason for non-operation; a storage unit for storing an analysis result storage database that stores the result of analysis; a display unit for presenting to a user the result of the analysis; and a correction unit for correcting the result of the analysis according to an instruction from the user.

A numerical controller for controlling a machine tool based on a processing program is disclosed. One numerical controller includes: a detecting unit that detects a factor which causes malfunction of the numerical controller; a storing unit that stores information of a block of the processing program which is being executed and information of the factor in association with each other; and a display unit that displays information of the detected factor on a location corresponding to a display location of the block of the processing program.

A method for determining a location of a disturbance in a power system is provided. The method includes receiving data from a plurality of sensors distributed across the power system; determining, with one or more processors, for each sensor, an extremum of the data corresponding to the sensor; interpolating, with the one or more processors, the extrema; and presenting, on one or more display units, a location corresponding to a global maximum of the interpolated extrema as the location of the disturbance. The method may further include, if a difference between the largest extremum and each of remaining extremum is greater than a predetermined threshold, skipping the interpolating step and the presenting step, and presenting a location of the sensor corresponding to the largest extremum as the location of the disturbance.

The present invention concerns a method and a system for detecting malfunctions in an apparatus and/or defects in a workpiece processed by said apparatus. The method provides for acquiring a sound signal emitted by an apparatus during an operation cycle of the same, then comparing the sound signal with a plurality of audio tracks stored in a memory area for determining a malfunction of the apparatus and/or a defectiveness of the workpiece processed by the apparatus based on the result of said comparison. The operation cycle is subdivided into a plurality of work phases and during the acquisition of the sound signal a work phase of said plurality of work phases is identified. Each audio track of the plurality of stored audio tracks comprises an audio component relating to acquired sound signals, and additional information data comprising at least one identifier of the work phase executed by the apparatus during the acquisition of the sound signals of the audio component. The plurality of audio tracks used for the comparison with the sound signal is a group of audio tracks of the plurality of audio tracks whose identifier of the work phase of the apparatus corresponds to the identified work phase. The identification data of the audio tracks additionally comprise at least one identifier of a plurality of components activated during the phase to which the audio component refers, and it is further provided for a) identifying a plurality of components activated during the identified work phase, b) on the basis of the plurality of activated components, identifying a set of comparison phases among the plurality of phases of the operation cycle, and c) identifying as defective at least one component between the plurality of components activated during the work phase and/or the workpiece, on the basis of the audio tracks relating to the set of comparison phases identified and/or on the basis of sound signals acquired during the identified comparison phases.

A cell controller includes a plurality of sensors for detecting the state of a plurality of manufacturing machines, a state storing unit for storing the state of each manufacturing machine, a breakdown information acquiring unit for acquiring breakdown information of each manufacturing machine, an input unit for inputting recovery operation information when each manufacturing machine stops, a recovery operation information storing unit for storing the recovery operation information of each manufacturing machine, and a correlation data generating unit. The correlation data generating unit generates correlation data obtained by correlating the breakdown information acquired by the breakdown information acquiring unit with the recovery operation information stored by the recovery operation information storing unit in each manufacturing machine, and transmits the same to the database. These configurations enable an operator to easily acquire, when a manufacturing machine in a manufacturing cell stops, a recovery operation most appropriate to the manufacturing machine.