Methods and systems that monitor an actuator state of wear. One or more observations are made as to one or more extremum positions of the actuator to determine a reference extremum position when the actuator is not worn. As the actuator becomes worn, the difference between a present extremum position and the reference is used to monitor actuator wear. Actuator wear may be observed to identify or predict a need for maintenance or replacement, and/or may be used in determining health impacts of control system solutions.

A machine maintenance action can be detected at a location using acoustic analysis of the machine to detect a probable maintenance action. Acoustic data is received at a computer from a plurality of microphones at a location. The acoustic data is analyzed with respect to a database of specifications for the machine, and the analysis of the acoustic data includes correlating the acoustic data to the specifications of the machine stored in the database. A first measured parameter for the machine is determined as outside a first specification of the machine, and indicates a first measurement variation from the first specification of the machine. The first measurement variation is assessed to determine a reason for the first measurement variation in relation to an identified part. An alert is sent to a device with a recommendation or action regarding the identified part, based on the reason for the first measurement variation.

A machine maintenance action can be detected at a location using acoustic analysis of the machine to detect a probable maintenance action. Acoustic data is received at a computer from a plurality of microphones at a location. The acoustic data is analyzed with respect to a database of specifications for the machine, and the analysis of the acoustic data includes correlating the acoustic data to the specifications of the machine stored in the database. A first measured parameter for the machine is determined as outside a first specification of the machine, and indicates a first measurement variation from the first specification of the machine. The first measurement variation is assessed to determine a reason for the first measurement variation in relation to an identified part. An alert is sent to a device with a recommendation or action regarding the identified part, based on the reason for the first measurement variation.

A computer-implemented method, a system, and at least one computer-readable storage device are provided. A measured value related to operation of a device is periodically received for each respective reporting period. If the measured value indicates unhealthy operation of the device, a distance of the measured value from a predetermined abnormal threshold is determined and stored in a data store. Based on the determined distance, a number of most recent reporting periods included in a window is determined. All stored distances determined from measured values received before the window of the most recent reporting periods are deleted from the data store. An occurrence of a device failure is determined based on the stored distances in the data store after the deleting. In response to determining the occurrence of the device failure, an action is performed.

Example implementations described herein are directed to systems and methods for extracting signal in presence of strong noise for industrial Internet of Things (IoT) system especially for monitoring systems of consumable items such as lathe machines, coolers and so on. Example implementations can utilize a sawtooth mother Wavelet instead of usual wavelet analysis to cleanse the incoming sensor data, thereby allowing for the converting sensor data to feature values despite having heavy noise interference.

Example implementations described herein are directed to systems and methods for extracting signal in presence of strong noise for industrial Internet of Things (IoT) system especially for monitoring systems of consumable items such as lathe machines, coolers and so on. Example implementations can utilize a sawtooth mother Wavelet instead of usual wavelet analysis to cleanse the incoming sensor data, thereby allowing for the converting sensor data to feature values despite having heavy noise interference.

A method of controlling a machine tool comprising the steps of: providing a data memory containing, for at least one specific working axis of the plurality of working axes, a plurality of data tuples each assigning a load value to a position value relative to the specific working axis, selecting a first data tuple and a second data tuple whose load values are different, and generating at least one control command for the machine tool, wherein the control command is adapted to perform a first tolerance measurement at a first position value and a second tolerance measurement at a second position value, and wherein, based on a first result of the first tolerance measurement and a second result of the second tolerance measurement, information about wear of a part of the machine tool is output. A corresponding device is also be disclosed.

A method of controlling a machine tool comprising the steps of: providing a data memory containing, for at least one specific working axis of the plurality of working axes, a plurality of data tuples each assigning a load value to a position value relative to the specific working axis, selecting a first data tuple and a second data tuple whose load values are different, and generating at least one control command for the machine tool, wherein the control command is adapted to perform a first tolerance measurement at a first position value and a second tolerance measurement at a second position value, and wherein, based on a first result of the first tolerance measurement and a second result of the second tolerance measurement, information about wear of a part of the machine tool is output. A corresponding device is also be disclosed.

A system is disclosed. The system may include a data-gathering apparatus disposed on a tooling. The data-gathering apparatus may include a sensor configured to detect one or more events produced by the tooling, and a data store configured to store event data. The event data may be based on the one or more detected events. The system may include a client apparatus configured to receive user input, communicate the user input to an external device, receive data from the external device, and display at least a portion of the received data on a display of the client apparatus. The system may include a server in data communication with the data-gathering apparatus and the client apparatus. The server may be configured to receive the event data, process the event data, and send at least a portion of the processed data to the client apparatus.

A system is disclosed. The system may include a data-gathering apparatus disposed on a tooling. The data-gathering apparatus may include a sensor configured to detect one or more events produced by the tooling, and a data store configured to store event data. The event data may be based on the one or more detected events. The system may include a client apparatus configured to receive user input, communicate the user input to an external device, receive data from the external device, and display at least a portion of the received data on a display of the client apparatus. The system may include a server in data communication with the data-gathering apparatus and the client apparatus. The server may be configured to receive the event data, process the event data, and send at least a portion of the processed data to the client apparatus.