There is provided a technique that includes: a main controller configured to execute a process recipe including a plurality of steps to perform a predetermined process on a substrate so as to acquire device data when executing the process recipe; and a storage part configured to store the acquired device data, wherein the main controller is configured to: acquire the device data in a predetermined specific step among the steps constituting the process recipe; calculate a value of the acquired device data in the specific step; compare the calculated value with a value of the device data in the specific step calculated at a time of previous execution of the process recipe; and generate an alarm when the calculated value shows a predefined tendency.

A diaphragm pump, includes a case, a diaphragm dividing a space in the case into a first space and a second space, a liquid feed flow path including an inflow path to introduce a liquid to be fed into the first space and an outflow path to discharge the liquid to be fed from the first space, a drive unit including a compression/decompression device that repeatedly causes displacement of the diaphragm by repeating compression and decompression of a driving fluid filling the second space, and a valve mechanism to open and close the inflow path and the outflow path. The drive unit includes a pressure release mechanism to release pressure of the driving fluid after the driving fluid is compressed or decompressed by the compression/decompression device.

Disclosed is a status monitoring and fault diagnosis system for a plunger pump, including a monitoring and fault diagnosis device. The monitoring and fault diagnosis device monitors and diagnoses a hydraulic end assembly of a plunger pump. The monitoring and fault diagnosis device further monitors and diagnoses a power end assembly and/or a reduction gearbox assembly. Beneficial effects: The diagnosis system monitors and diagnoses not only a hydraulic end assembly, but also a power end assembly and/or a reduction gearbox assembly, that is, an equipment fault can be accurately predetermined in time for an entire plunger pump, so that high-pressure, large-displacement, and continuous operation requirements on fracturing sites at present are better satisfied, and on-demand maintenance is adopted instead of regular examination and maintenance, thereby saving labor, time, and materials to achieve economic efficiency.

The present disclosure relates generally to alternating tangential flow (ATF) perfusion pumping methods, including novel methods for generating positive and negative pressure at the point of use, and more particularly, to apparatuses, systems and methods for use of the same.

An automatic self-driving pump system features a pump/motor/drive detector and an automatic self-driving and control design/setup module. In operation, the pump/motor/drive detector receives sensed signaling containing information about a pump/drive for operating in a hydronic pump system, e.g., stored in and sensed from a signature chip or barcode installed that can be scanned by a scanner, and provides corresponding database signaling containing information about parameters for providing automatic pump control design, setup and run to control the pump/drive for operating in the hydronic pump system, based upon the sensed signaling received. The automatic self-driving and control design/setup module receives the corresponding database signaling, and provides control signaling containing information for providing the automatic pump control design, setup and run to control the pump/drive for operating in the hydronic pump system, based upon the corresponding database signaling received.

A system for monitoring a hydraulic fracturing pump includes a first sensor configured to measure a discharge fluid pressure of the pump, a second sensor configured to sense a displacement of a crankshaft of the pump, a processor communicatively coupled to the first and second sensors and configured to analyze the sensor data and determine a cycle count, duty cycle, and operating hour value for the positive displacement pump, and a display coupled to the processor configured to display the cycle count, duty cycle, and operating hour value.

There is provided a technique that includes: a controller configured to execute a process recipe including a plurality of steps to perform a predetermined process on a substrate. The controller acquires device data, which includes at least one of a current value, a rotational speed, and a back pressure of a pump, in a specific step among the plurality of steps and compares an acquired value of the device data with a previously acquired value of the device data. The controller generates a notification if at least one of the following conditions is met: the acquired value for the current value is larger than the previously acquired value for the current value, the acquired value for the back pressure is larger than the previously acquired value for the back pressure, and the acquired value for the rotational speed is smaller than the previously acquired value for the rotational speed.

An abnormality diagnosis method is targeted at a hydraulic device which includes a hydraulic pump and a driven device driven by the hydraulic pump. The method includes calculating a frequency distribution with regard to a deviation between a normal value of an output parameter corresponding to an operation condition and an actual measurement value of the output parameter using a prediction model, and determining the presence of an abnormality if an average of the deviation exceeds a threshold. If the presence of the abnormality is determined, a factor of the abnormality is estimated based on the range of the deviation where a waveform peak of the frequency distribution exists.

This disclosure relates to methods and apparatus for monitoring a remote system. In one arrangement, a plurality of measurement data units are obtained. Each measurement data unit represents a time series of measurements made by a sensor system at the remote system. A first trained machine learning model is used to identify a subset of the measurement data units that have a higher average probability of corresponding to an abnormal state of the remote system than the other measurement data units. Data representing the identified measurement data units is sent over a communications network to a central data processing system. An abnormal state of the remote system is detected by using a second trained machine learning model at the central data processing system to process the data representing the identified measurement data units.

A pumping system includes a pump array of multiple pump-engine assemblies. Each pump-engine assembly comprises a pump and a gas turbine engine driving the pump. A manifold is coupled to the pumps. A master controller is coupled to each of the pump-engine assemblies either directly or via one or more intermediate controllers. The master controller and any intermediate controllers are collectively programmed to respond to user input including a desired hydraulic output at the manifold by automatically calculating and applying inputs to the individual pump-engine assemblies to provide the desired hydraulic output.