In a data obtaining step, a data obtaining unit may obtain certain data at a plurality of sampling times. The data may include measurement information regarding the amount of wear of the cutting tool and measurement information regarding a physical quantity of the cutting tool during cutting. In a clustering step, a clustering unit may cluster a plurality of pieces of the obtained data on the basis of the measurement information regarding the physical quantity included in each of the plurality of pieces of data. In a model creation step, a model creation unit may create, for each of clusters on the basis of the measurement information regarding the physical quantity and the measurement information regarding the amount of wear included in the data, a model for obtaining estimation information regarding the amount of wear from new measurement information regarding the physical quantity.

In the technical field of industrial automation, a fault diagnosis method and apparatus for a numerical control machine tool are disclosed which can improve the efficiency of diagnosing faults of numerical control machine tools by utilizing feedback information provided by users. In a fault diagnosis method of an embodiment, the fault diagnosis apparatus receives a fault symptom to be diagnosed from a user terminal, diagnoses the fault for the fault symptom to be diagnosed, returns a fault diagnosis result to the user terminal, receives feedback on the fault diagnosis result from the user terminal, and adjusts the diagnosis policy for the fault symptom to be diagnosed according to the fault diagnosis result if the feedback of the user on the fault diagnosis result indicates that the fault has been cleared.

A non-transitory computer-readable medium includes instructions that, when executed, cause one or more processors to perform operations. The operations include receiving a first request to access a digital representation that is assigned to an asset of an industrial automation system and includes code specific to operating, maintaining, or diagnosing the asset. The operations also include verifying a security access for the first request, providing the computing device access to the digital representation, receiving an input to modify the code from the computing device and, performing one or more simulations based on the modified code by utilizing the digital representation. Additionally, the operations include sending one or more simulation results to the computing device, receiving, from the computing device, a second request for pushing the modified code to the asset, and in response to receiving the second request, causing the modified code to be sent to the asset.

A behavior recognition device for recognizing behaviors of a semiconductor manufacturing apparatus includes a storage device and a control unit. The storage device is configured to store log data of the semiconductor manufacturing apparatus. The control unit is cooperatively connected to the storage device, and configured to build a transition state model based on the log data to analyze behaviors related to wafer transfer sequences and manufacturing operations of the semiconductor manufacturing apparatus.

Systems and methods for controlling chlorinators for pools and spas are provided. A controller communicates with a processor positioned within a replaceable cell cartridge of a chlorinator, to allow for remote control and diagnosis of the chlorinator and/or cell cartridge. The cell cartridge stores, in non-volatile memory on board the cartridge, one or more parameters associated with the cartridge. The controller can obtain this information from the processor of the cell cartridge, and can use same to configure operation of the chlorinator. Information relating to remaining cell life can be updated by the controller and stored in the non-volatile memory of the cell cartridge. Electrical and software-based mechanisms are provided for ensuring operation of only compatible cell cartridges with the chlorinator. A system for remotely diagnosing errors associated with the chlorinator is also provided.

An information processing apparatus executes a simulation of a state of a process which is being performed in a semiconductor manufacturing apparatus, by using a simulation model of the semiconductor manufacturing apparatus. The information processing apparatus includes: a physical sensor data acquisition unit that acquires physical sensor data measured in the semiconductor manufacturing apparatus that is performing the process according to process parameters; a simulation execution unit that executes the simulation by the simulation model according to the process parameters, thereby outputting virtual sensor data; a simulation result determination unit that performs a pre-detection of a part of the semiconductor manufacturing apparatus that needs to be replaced, based on a difference between the physical sensor data and the virtual sensor data; and a part order unit that orders the part of the semiconductor manufacturing apparatus based on a result of the pre-detection.

An equipment failure diagnosis apparatus, an equipment failure diagnosis method, a smart factory system, and an application agent configured to generate a virtual abnormal signal based on a normal signal data stored in the database, determine whether an equipment signal is an abnormal signal based on a virtual abnormal signal data for the virtual abnormal signal, and output a determination result information. Accordingly, the present disclosure can quickly and accurately diagnose a failure of equipment in a factory, even under conditions where labeling data is not present or insufficient.

The subject is to provide a technique of dealing with an internal state of a controller in an edge device by cooperation between an edge device and a computer such as a cloud server, and to generalize data communication for the cooperation and reduce an amount of data communication. Provided is a distributed system including an edge device and a diagnostic data computer. The edge device includes an in-edge controller including at least a processing unit, and a system element to be monitored by the in-edge controller. The processing unit diagnoses presence or absence of an abnormality in the processing unit due to an abnormality occurring in the system element, generates first diagnostic data indicating presence or absence of the abnormality of the processing unit, converts the first diagnostic data into second diagnostic data indicating a type of the abnormality of the processing unit, and transmits the second diagnostic data to the diagnostic data computer.

A machine control device includes: a diagnostic test time calculation unit that calculates a scheduled execution time of a diagnostic test; a program execution time prediction unit that predicts a predicted ending time of a program before executing the program; a diagnostic test execution determination unit that determines whether to execute the diagnostic test at a predetermined time, by determining whether the predicted ending time of the program exceeds the scheduled execution time of the diagnostic test, and a diagnostic test execution unit that executes the diagnostic test, in which, in a case in which the predicted ending time of the program exceeds the scheduled execution time of the diagnostic test, the diagnostic test execution determination unit instructs the diagnostic test execution unit to execute the diagnostic test prior to the scheduled execution time of the diagnostic test before executing the program.

Disclosed is an approximate physical simulation integrated debugging method based on digital twinning, which includes the following steps of: a production line simulation model building step, a twinning step, a system debugging step, a hardware-in-the-loop debugging step, and a device-in-the-loop debugging step. The approximate physical simulation integrated debugging system based on digital twinning includes a production line simulation model building module, a twinning module, a system debugging module, a hardware-in-the-loop debugging module, and a device-in-the-loop debugging module. According to the approximate physical simulation integrated debugging method and system based on digital twinning, since a local component twin after being successfully debugged is replaced with an entity component, when a problem occurs after replacement, only the local component twin needs to be debugged and optimized again, thus saving time and reducing cost.