A preventive maintenance system of a machine tool capable of making determination of presence of an abnormality mechanically and automatically, which has conventionally been performed on the basis of the feeling of an operator and detecting an abnormality more accurately in an earlier stage is provided. The preventive maintenance system includes: a vibration detection unit attached to a mechanism of a machine tool to detect vibration; a sound detection unit that detects acoustic waves produced when a work is machined by the machine tool; a servo motor current value detection unit that detects a current value of a servo motor; an abnormality determination unit that compares the vibration, the acoustic waves, and the current value of the servo motor during operation of the machine tool with vibration data, acoustic wave data, and current value data in a normal state set in advance to determine presence of an abnormality in the mechanism of the machine tool; and a detection start/end command setting unit that adds commands for a detection start point and a detection end point of at least one of the vibration, the acoustic waves, and the current value of the servo motor to a machining program.

Systems and methods for data collection for an industrial heating process are disclosed. The system according to one embodiment can include a plurality of data collectors, including a swarm of self-organized data collector members, wherein the swarm of self-organized data collector members organize to enhance data collection based on at least one of capabilities and conditions of the data collector members of the swarm, and wherein the plurality of data collectors is coupled to a plurality of input channels for acquiring collected data relating to the industrial heating process, and a data acquisition and analysis circuit for receiving the collected data via the plurality of input channels and structured to analyze the received collected data using a neural network to monitor a plurality of conditions relating to the industrial heating process.

A numerical control device for performing movement control of a machining tool by a fixed cycle includes a main control unit that issues a machining command to a machining device based on a machining program, a machining program analysis unit that pre-reads and analyzes the machining program, a machining state measurement unit that measures a physical quantity indicating a machining state during machining, and a start position determination unit that determines an overlap control start position based on the measured physical quantity, and the main control unit executes overlap control when determining that the machining tool reaches the overlap control start position.

A managing apparatus includes: a data collecting unit that collects at least quality information on a workpiece having been machined by a first machine tool and operational information on other machine, an analyzing unit that performs an analysis for determining correlation between the quality information on a workpiece having been machined by the first machine tool and the operational information on the other machine, an operation plan making unit that makes an operation plan, based on the correlation determined by the analyzing unit, for imposing a restriction on an operation of the other machine to reduce vibrations to be transmitted to the first machine tool during high-precision machining performed by the first machine tool, and an operation instruction providing unit that provides an operation instruction to the other machine based on the operation plan made by the operation plan making unit.

In one embodiment, a device in a network receives a machine learning encoder and decoder trained by a supervisory service. The service trains the encoder and decoder using vibration measurement data sent to the service by a plurality of devices. The device trains, based on the received encoder, a classifier to determine whether vibration measurement data is indicative of a behavioral anomaly. The device receives vibration measurement data captured by a particular set of one or more vibration sensors of a monitored system. The device evaluates, using the trained decoder, the received vibration measurement data to determine whether the data is indicative of a structural anomaly in the monitored system. The device evaluates, using the trained classifier, the received vibration measurement data to determine whether the data is indicative of a behavioral anomaly in the monitored system.

Processing data during polygon processing is stored in the processing data storage unit 17. The position detection unit 18 detects a cut-start position A and a cut-end position B of a workpiece based on a change in the processing data. The position detection unit 18 detects a processing surface based on the cut-start position A and the cut-end position B.

Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.

A vibration analysis apparatus includes: a storage unit storing a regression equation indicating correspondence between rotation speed change of a rotation mechanism and a peak occurrence frequency of acceleration of vibration, for each acceleration peak; an analysis unit extracting a peak occurrence frequency of acceleration of vibration for each acceleration peak, based on vibration data of the rotation mechanism and calculating, for each acceleration peak, a waveform area of the acceleration peak by integrating the acceleration peak over a specific frequency section; and an anomaly determination unit determining whether operational anomaly occurs in the rotation mechanism for each acceleration peak. The analysis unit tracks, in accordance with the regression equation, change in peak occurrence frequency due to rotation speed change when vibration of the rotation mechanism is analyzed, and calculates, for each second acceleration peak, the waveform area of the second acceleration peak corresponding to the second vibration frequency tracked.

Methods and systems for sensor fusion in a production line environment are disclosed. An example system for data collection in an industrial production environment may include an industrial production system comprising a plurality of components, and a plurality of sensors each operatively coupled to at least one of the components; a sensor communication circuit to interpret a plurality of sensor data values in response to a sensed parameter group; and a data analysis circuit to detect an operating condition of the industrial production system based at least in part on a portion of the sensor data values; and a response circuit to modify a production related operating parameter of the industrial production system in response to the detected operating condition.

A method and a robot controller for controlling a robot arm, where the robot arm comprises a plurality of robot joints connecting a robot base and a robot tool flange, where each of the robot joints comprises an output flange movable in relation to a robot joint body and a joint motor configured to move the output flange in relation to the robot joint body. The robot arm is controlled based on vibrational properties of at least one external object connected to the robot arm, where the vibrational properties are received via an external object installation interface by generating control signals for said robot arm based on a target motion and the received vibrational properties of the at least one external object, the control signal comprises control parameters for said joint motor.