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.

A computer implemented method of operating a diagnostic instrument such that maintenance processes do not conflict with operator activity is presented. A maintenance process conflicts with operator activity if the probability of use of the diagnostic instrument is above a usage probability threshold. The probability of use of the diagnostic instrument is determined based on detected presence and/or movement of an operator in the proximity of the diagnostic instrument and/or operation of the diagnostic instrument.

A machining simulation device includes a cutting condition extraction unit, a tool type determine unit, a load calculation unit configured to calculate a spindle load, a load determination unit configured to determine whether the calculated spindle load is within a predetermined maximum load, an adjustment amount calculation unit configured to calculate an adjustment amount of the cutting condition when the calculated spindle load is determined not to be within the predetermined maximum load, and a display unit configured to display a result of the determination.

The present disclosure is directed toward a diagnostic method for a spindle arm of a machine. The method includes rotating the spindle arm of the machine at a first rotational speed, and acquiring, from an accelerometer, data indicative of a vibrational response of the spindle arm operating at the first rotational speed. The accelerometer is disposed along the spindle arm. The method further includes converting the vibrational response to a frequency based response to obtain a first frequency response, determining whether an amplitude of the first frequency response exceeds a diagnostic threshold, and performing a designated correction on the machine in response to the frequency response exceeding the diagnostic threshold.

A diagnosis device includes a first acquiring unit acquires, from a target device, context information corresponding to a current operation; a second acquiring unit acquires detection information output from a detecting unit that detects a physical quantity that changes according to operations performed by the target device; a first transmitting unit transmits the acquired context information to a learning device; a second transmitting unit transmits the acquired detection information to the learning device; a third acquiring unit acquires a model corresponding to the transmitted context information, from the learning device that determines whether any pieces of context information are identical or similar to each other and combines models generated from pieces of the detection information corresponding to the pieces of identical or similar context information; and a first determining unit determines whether an operation performed by the target device is normal by using the detection information and the model.

Power systems and methods of controlling power systems are disclosed. The system may include a power plant system (PPS) including a component and at least one computing device in communication with the PPS. The computing device(s) may be configured to control the PPS by performing processes including determining if an operational anomaly for the component occurred during operation of the PPS. In response to determining that the operational anomaly did not occurr, the computing device(s) may also perform processes including determining a first operational reliability of the component. In response to determining the operational anomaly occurred, the computing device(s) may also perform processes including determining a second operational reliability of the component based on the determined operational anomaly. Additionally, the computing device(s) may perform processes including adjusting operation of the PPS in response to the first operational reliability or the second operational reliability exceeding a predetermined operational reliability threshold.

Embodiments of the disclosure provide for intelligent model integration within a process simulation system. Some embodiments receive data associated with the operation of a plant, determine, using at least one specially configured algorithm and based on the received data, at least one qualifying dataset determined qualified to train an intelligent model, train the intelligent model using the at least one qualifying dataset, and deploy the trained intelligent model for use.

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.

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.

A field device for measuring information associated with each of equipments installed in a plant includes: a measurer configured to measure running condition of the equipment, and to output measurement information representing result of the measurement; a diagnoser configured to diagnose the running condition of the equipment represented by the measurement information in accordance with predetermined first diagnosis rule, to diagnose result diagnosed in accordance with the first diagnosis rule in accordance with predetermined second diagnosis rule, and to output diagnosis result information representing result diagnosed in accordance with the second diagnosis rule as result of diagnosing the running condition of the equipment; wherein the second diagnosis rule is configured to be set condition for confirming influence of an external factor to the running condition of the equipment.