Patent classifications
G05B23/021
Data processing method, data processing device, and non-transitory computer-readable recording medium having recorded thereon data processing program
A data processing method includes a period setting step of obtaining a rising period, a stable period, and a falling period with respect to time series data obtained in a substrate processing apparatus, an evaluation value calculation step of obtaining an evaluation value in the rising period, an evaluation value in the stable period, and an evaluation value in the falling period as an evaluation value of the time series data. In the period setting step, a period from when a control signal changes until the time series data falls within a first range including a target level is obtained as the rising period, a period from when the control signal changes until the time series data falls within a second range including an initial level is obtained as the falling period, and a period between the rising period and the falling period is obtained as the stable period.
PIPING AND INSTRUMENTATION DIAGRAM EXTRACTION TO HUMAN-MACHINE INTERFACE STATIC GRAPHICS
Techniques to facilitate extraction of display objects for human-machine interface (HMI) displays are disclosed herein. In at least one implementation, a selection of a user-defined area is received that identifies at least a portion of a piping and instrumentation diagram (P&ID) associated with an industrial automation environment. The user-defined area of the P&ID is analyzed to identify at least one object within the user-defined area of the P&ID. The at least one object identified within the user-defined area of the P&ID is extracted to generate a static graphic object. Edit instructions are received that describe at least one modification to a visual appearance of the static graphic object. The edit instructions are applied to the static graphic object to generate an HMI graphic object comprising the at least one modification to the visual appearance of the static graphic object.
Irrigation motor and gearbox temperature monitoring and control system
A control system for monitoring a motor and wheel drive gearbox of an irrigation system drive train. The control system includes a motor sensor for sensing an operating state of the motor and a gearbox sensor for sensing an operating state of the wheel drive gearbox. If the motor operating state exceeds a motor operating state threshold or changes too quickly, or if the wheel drive gearbox operating state exceeds a wheel drive gearbox operating state threshold or changes too quickly, the control system operates the drive train at a reduced capacity or in a modified mode such that the operating state is not exceeded or does not change too quickly.
MONITORING OF DEVICE OPERATION BY GROUPING
Monitoring of operations of different types of devices to determine when the devices have varied from usual operation. The devices might be connected, directly or through a proxy, to a cloud service, and may be innumerable devices (such as Internet of Things devices) of a variety of different types. The operations of any number of such devices are measured. Based on the measurements, the devices are grouped based on the operational similarity. Then, standard operational characteristics are then defined for each group of devices. The operational characteristics for the devices are monitored so as to detect when a particular device has varied from this defined standard operation. When a variance is detected, an alert is provided to that effect.
AIR CONDITIONER AND METHODS OF OPERATION HAVING A LEARNING EVENT
An air conditioner, as provided herein, may include a cabinet, an outdoor heat exchanger, an indoor heat exchanger, a compressor, an internal temperature sensor, and a controller. The controller may be configured to initiate a conditioning operation. The conditioning operation may include detecting a learning condition at the air conditioner, identifying a first operating mode, and initiating a learning event at the first operating mode. The conditioning operation may further include measuring performance during the learning event, recording a baseline variable based on the measured performance during the learning event, and measuring performance at the first operating mode. The conditioning operation may still further include recording an operational variable based on the measured performance at the first operating mode, comparing the operational variable of the first operating mode to the baseline variable of the first operating mode, determining a fault state based on the comparison, and recording the fault state.
Automated pipeline chemical batch treatment
A method of automated pipeline chemical batch treatment includes receiving treatment information at a control system of a pipeline. If the treatment information includes an instruction to activate a pump system, the method includes transmitting an activation signal from the control system to the pump system in accordance with the treatment information. The activation signal causes the pump system to pump one or more chemicals from a chemical feed system into the pipeline. If the treatment information includes an instruction to deactivate the pump system, the method includes transmitting a deactivation signal from the control system to the pump system in accordance with the treatment information, wherein the deactivation signal causes the pump system to stop pumping one or more chemicals from the chemical feed system into the pipeline.
Automatic Inspection System
When the learning process is performed and the learning result is set in the wireless slave device, the time required for installing the wireless slave device is increased. Further, when data including the state of the inspection target object detected by the wireless slave device is transmitted as it is, the data size is increased, and the power consumption of the wireless slave device is also increased. A wireless slave device transmits a state of an inspection target object to a setting device as learning data, obtains, as an analysis result, a degree of difference between the state of the inspection target object and the normal state of the inspection target object based on a learning result set by the setting device, and wirelessly transmits data including the analysis result to the wireless master device. The setting device transfers the learning data received from the wireless slave device to the analysis management device and sets the learning result transmitted from the analysis management device in the wireless slave device. The analysis management device extracts a characteristic value characterizing the state of the inspection target object from the learning data transferred from the setting device and transmits the extracted characteristic value to the setting device as a learning result.
SCALING TOOL
The present application generally pertains to scaling of a production process to produce a chemical, pharmaceutical and/or biotechnological product and/or of a production state of a respective production equipment. Particularly, there is provided a computer-implemented method of scaling a production process to produce a chemical, pharmaceutical and/or biotechnological product, the scaling being from a source scale to a target scale, wherein the production process is defined by a plurality of steps specified by one or more process parameters controlling an execution of the production process, the method comprising: (a) retrieving: parameter evolution information that describes the time evolution of the process parameter(s); a plurality of recipe templates, wherein a recipe comprises the plurality of steps defining the production process, and wherein a recipe template is a recipe in which at least one of the process parameters specifying the plurality of steps is a parameter being variable and having no predetermined value at the outset; (b) receiving: a source setup specification of a source setup to be used for executing the production process at the source scale, the source setup specification comprising the source scale value: a target setup specification of a target setup to be used for executing the production process at the target scale, the target setup specification comprising the target scale value; a source recipe defining the production process at the source scale: at least one acceptability function defining conditions for the values of the process parameter(s) at the source scale and/or at the target scale; (c) simulating the execution of the production process at the source scale using the source setup specification, the source recipe and the parameter evolution information: (d) determining, from the simulation, one or more source trajectories for the process parameters), wherein a trajectory corresponds to a time-based profile of values recordable during the simulated execution of the production process; (e) performing a target determination step comprising: selecting a recipe template pertinent to the production process out of the plurality of recipe templates; providing an input value for the at least one variable parameter in the selected recipe template; simulating the execution of the production process at the target scale using the target setup specification, the selected recipe template, the input value for the at least one variable parameter and the parameter evolution information; determining, from the simulation, one or more target trajectories for the process parameters; comparing the source trajectory(ies) and the target trajector
Information storage system and apparatus
An information storage system and apparatus relate to the field of automatic control technologies in order to resolve a problem that there is little information for diagnosing a fault that is stored using a freeze frame. The system includes at least one subcontroller configured to obtain a parameter value corresponding to a parameter, and send the parameter and the parameter value corresponding to the parameter to a management controller, the management controller configured to send the received parameter and the received parameter value corresponding to the parameter to a vehicle-intelligent device, and the vehicle-intelligent device is configured to receive and store the parameter and the parameter value corresponding to the parameter, where each subcontroller is coupled to at least one executor, and the management controller is coupled to each subcontroller of the at least one subcontroller.
AUTOMATED PIPELINE CHEMICAL BATCH TREATMENT
A method of automated pipeline chemical batch treatment includes receiving treatment information at a control system of a pipeline. If the treatment information includes an instruction to activate a pump system, the method includes transmitting an activation signal from the control system to the pump system in accordance with the treatment information. The activation signal causes the pump system to pump one or more chemicals from a chemical feed system into the pipeline. If the treatment information includes an instruction to deactivate the pump system, the method includes transmitting a deactivation signal from the control system to the pump system in accordance with the treatment information, wherein the deactivation signal causes the pump system to stop pumping one or more chemicals from the chemical feed system into the pipeline.