A substrate processing system includes a monitored data receiving unit receiving a plurality of types of monitored data; a temporary memory unit periodically storing the monitored data; a monitored data rate detection unit detecting, as a monitored data rate, a total number of times each type of monitored data changes during a first time period by more than a predetermined amount; a monitored data writing allocation unit allocating a storing frequency to each type of monitored data based on the monitored data rate and an upper limit; a monitored data writing unit writing the monitored data to the temporary memory unit during the second time period based on the storing frequency; an accumulative memory unit storing the monitored data for a plurality of periods; and an accumulative data writing unit reading the monitored data for every third time period and storing the monitored data in the accumulative memory unit.

A method for protecting a nonmobile work machine driven by an electric motor includes determining, via a measuring unit, at least one measured value of a time-critical parameter of the work machine. The work machine is switched off when the determined measured value of the time-critical parameter is outside a predefined setpoint range. The determined measured value of the time-critical parameter is quantized in a level signal and transmitted as a first signal to an evaluation unit via an interface, and a second signal for further information concerning the work machine, to be transmitted from the measuring unit to the evaluation unit, is modulated to the first signal.

A method for maintaining the functional ability of a field device of automation technology, wherein the method comprises the following steps: monitoring the field device for at least one achieved parameter change (Δn.sub.x), wherein the parameter change (Δn.sub.x) converts an old parameter set (n.sub.x-1) into a new parameter set (n.sub.x), storing all parameter changes (Δn.sub.x) achieved in the field device in a parameter change history, monitoring the field device for an occurring malfunction (F); and, performing a remediation measure, wherein the parameter change history and/or a parameter to malfunction, linking element is accessed for remediating the malfunction occurring in the field device.

A system and method for data collection and frequency analysis with self-organization functionality includes analyzing with a processor a plurality of sensor inputs, sampling with the processor data received from at least one of the plurality of sensor inputs at a first frequency, and self-organizing with the processor a selection operation of the plurality of sensor inputs.

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 device and a method of monitoring a machine. The method includes interfacing an edge device with the machine and detecting a condition of the machine with the edge device. The method identifies the condition with the edge device and sends a signal identifying the condition to a program running on the machine. The signal of the edge device communicates with the program through a register of recorded values and the edge device checks the register and notifies the program by altering a value in the recorded values of the register to a signal value. The program reads the recorded values in the register and initiates an action in the machine when the signal value is present in the recorded values of the register.

Provided a data management system which includes a data acquisition unit that acquires measurement data obtained by measuring a fluid flowing in a flow path from each of a plurality of sensors, a data recording unit that records the acquired measurement data, and a data volume reduction unit that reduces a data volume to be recorded for a target sensor based on the measurement data acquired from another sensor installed in either an upstream or a downstream from itself in the flow path among the plurality of sensors.

A first graph display processing unit displays, on a first graph, a temporal variation of first process data accumulated in a process data storage unit. A second graph display processing unit displays, on a second graph, a temporal variation of second process data accumulated in the process data storage unit, and moves a time range of the data displayed on the second graph in accordance with a change of the time pointed to by a second time cursor on the second graph. A time coordination unit stores the time Ta pointed to by a first time cursor and changes the time pointed to by the second time cursor to time Ta, and thereby causes second process data of the same time as that of the first process data displayed on the first graph to be displayed on the second graph.

A data management system is provided, which includes a data acquiring unit that acquires measurement data generated by measuring a measurement target from each of a plurality of sensors; a data storage unit that stores the acquired measurement data; and a data-amount reducing unit that deletes part of the measurement data acquired from a target sensor based on the measurement data acquired from another sensor among the plurality of sensors to reduce an amount of data to be stored.

An analytics engine is provided for industrial automation applications. The engine may be modular, and may be instantiated upon receipt of a data structure, such as containing annotated data from or relating to a monitored and/or controlled machine or process. The module may be data-driven so that it is instantiated only as needed, upon receipt of the input data structure. The module then carries out analysis on the data, and outputs a data structure that can be used for further analysis, or directly by other modules for modeling, classification, optimization and/or control.