A processing apparatus includes a processing unit for processing the workpiece, a processing quality prediction unit connected with the processing unit electrically, a signal interpretation unit connected with the processing quality prediction unit electrically, and a control unit connected with both the processing unit and the signal interpretation unit electrically, wherein when the processing unit is processing the workpiece, the processing quality prediction unit detects the processing signal and sends the signal to the signal interpretation unit, wherein when the signal interpretation unit interprets the processing signal, if there is abnormality in the processing signal, the signal interpretation unit will immediately notify the control unit to stop the processing unit from operating. Therefore, by real-time monitoring the abnormality of the processing signal and stopping suspicious operation during processing, it allows operating personnel to deal with the abnormal condition, so as to greatly reduce the defect rate of the workpiece processing.

A method of providing a recommendation for optimizing operations of a set of industrial assets is disclosed. Digital twins of the set of industrial assets are generated. The digital twins include data structures representing states of each of a plurality of subsystems of the set of industrial assets over a time period. The states are estimated based on an application of simulations using cumulative damage models. The cumulative damage models model the effects of exogenous factors on the operation of the set of industrial assets over the time period. The digital twins are analyzed with respect to simulated operating performances to determine an optimized control of operations of the industrial assets. The optimized control of operations is calculated to jointly and severally to increase the specified operating performance criteria in time present and future of the industrial assets or decrease an economic risk associated with the operation of the industrial assets, within a specified probability. The recommendation is presented In a user interface for use in optimizing the operation of the industrial assets or automatically changing operating setpoints pertaining to the industrial assets.

A test system comprises a plurality of test devices which are connected to a plurality of machines and which perform a basic test, and a test management device which is connected to the plurality of test devices via a network. The test management device includes an additional test setting part which sets an additional test for determining a cause of an abnormality when determining that the machine has the abnormality. The test management device includes an adjustment part which sets the test device that performs the additional test. The adjustment part determines that the basic test planned to be performed by the test device that performs the additional test is performed by the other test device.

A method for operating an industrial automation system may include receiving, via a first module of a plurality of modules in a control system, a plurality of datasets via at least a portion of the plurality of modules. The plurality datasets may include raw values without context regarding the plurality datasets. The method may then include identifying a subset of the plurality of datasets that influences a value of a target variable by analyzing the data without regard to the context, modeling a behavior of the target variable over time based on the subset of the plurality of datasets, and adjusting one or more operations of an automation device based on the model.

A method for monitoring equipment and gathering consumption and diagnostic information can comprise receiving, at a server, a corrugate usage indicator. The corrugate usage indicator can comprise information relating to an amount of corrugate used by a first packaging system. The method can also comprise creating a usage profile for the first packaging system. The usage profile can comprise a corrugate usage profile. The corrugate usage profile can comprise an association between the amount of corrugate used by the first packaging system and the specifications and number of boxes created. Additionally, the method can comprise automatically generating, based upon the corrugate usage profile, a predicted time when a stock of corrugate associated with the first packaging system will be depleted.

Pulverizers are very critical equipment in overall functioning of a plant. They need to be controlled and monitored properly for the optimized operation of the pulverizers. A system and method for performance and health monitoring to optimize operation of a pulverizer is provided. The system comprises a digital twin that can mimic the performance of the pulverizer in real-time and assist the operators in decision making related to operation, maintenance and scheduling. The digital twin is configured to receives real-time sensor data from a plurality of data sources and provides real-time soft sensing of key health and performance parameters of the pulverizer. One more key aspect of the solution is the advisory system that alerts and recommends corrective actions in terms of parameters controlled through other equipment or changes in operation or design or changes in cleaning schedule.

The abnormality diagnosis system detects a failure sign of a device to be diagnosed. The abnormality diagnosis system includes: a diagnosis process search unit which searches for a suitable diagnosis processing procedure by comparing a plurality of diagnosis processing procedures, and outputs reconfiguration information corresponding to the suitable diagnosis processing procedure; and a diagnosis processing unit which has a reconfigurable processing unit and which uses the suitable diagnosis processing procedure found by the diagnosis process search unit to detect a failure sign of the device to be diagnosed by reconfiguring the processing unit on the basis of the reconfiguration information.

The present disclosure describes systems and methods for data collection in an industrial environment having self-organization functionality. A method can include analyzing a plurality of sensor inputs, sampling data received from the sensor inputs, and self-organizing at least one of (i) a storage operation of the data, (ii) a collection operation of sensors that provide the plurality of sensor inputs, and (iii) a selection operation of the plurality of sensor inputs. The method may further include receiving instructions directing a mobile data collector unit to operate sensors at a target, transmitting a communication to one or more other mobile data collector units regarding the instructions, and self-organizing a distribution of the mobile data collector unit.

A terminal insertion quality monitoring system includes an acceleration sensor disposed on a gripper of a terminal insertion equipment and configured to detect a dynamic acceleration of the gripper while using the gripper to insert a terminal into a housing, a control parameter acquisition device configured to acquire a plurality of control parameters of the terminal insertion equipment while inserting the terminal into the housing, and an artificial intelligence system adapted to classify the detected dynamic acceleration and the acquired control parameters into a plurality of different insertion modes by analyzing and calculating the detected dynamic acceleration and the acquired control parameters. The different insertion modes have a plurality of different grades of terminal insertion quality. The artificial intelligence system is configured to monitor a terminal insertion quality of the terminal according to the insertion mode to which the detected dynamic acceleration and the acquired control parameters correspond.

An apparatus for starting operation of a motor of an implantable blood pump including a memory storing one or more default parameters for at least one of controlling and monitoring the startup operation. A processor operatively coupled to the motor is included, the processor is configured to: commence the startup operation based on the one or more default parameters; detect an error during the startup operation; adjust at least one of the one or more default parameters in response to the detected error; store the at least one adjusted parameter in the memory; and commence subsequent startup operations based at least in part on the at least one adjusted parameter.