A diagnostic apparatus of the invention acquires normal data related to an operating state during normal operation of an industrial machine, stores the normal data, generates a learning model by learning based on the stored normal data, and performs an estimation process for normality or abnormality of an operation of the industrial machine using the learning model. The diagnostic apparatus of the invention further generates verification data including at least one piece of abnormal data based on the stored normal data to verify validity of the learning model on receiving a result of the estimation process using the learning model based on the verification data.

A system for remotely measuring the characteristics of water passing through a plumbing control device (PCD) includes a sensor within the interior of the PCD. The sensor is configured to measure characteristics of the water to obtain measured data. The sensor is also linked to a microcontroller of the PCD. An antenna board is linked, and configured to transmit power, to both the microcontroller and the sensor. A mobile device is configured to locate the antenna board. The mobile device transmits power to the antenna board which, in turn, transmits power to the microcontroller and the sensor. When power is not being transmitted from the antenna board, the microcontroller and the sensor are powered off.

A method for configuring an interface device connected to a control device and a field device, wherein the method includes receiving a first machine learning application having a plurality of logical components connected in a pipeline, where the first machine learning application serves to analyze a signal from the field device utilizing a first machine learning model, generating a plurality of code blocks utilizing a translator based on the plurality of logical components of the first machine learning application, connecting the plurality of code blocks in accordance with the pipeline of the first machine learning application to generate a first output from the signal from the field device, and deploying the connected code blocks on firmware of the interface device including creating a virtual port connectable to the control device, and where the virtual port serves to transmits the first output to the control device.

A method for providing output values with associated uncertainties for a flexible modular plant or machine comprising an arrangement of modular entities, wherein uncertainty information associated with an operation of the modular entity is assigned to a plurality of modular entities and input values are provided based on an operation of the modular entities, where a computing unit calculates an output value based on said input values, calculates an input value uncertainty for each input value based on the uncertainty information of the modular entity, and calculates at least one output value uncertainty associated with the output value based on propagation of uncertainty and using the input value uncertainties, and where the output value and the at least one output value uncertainty are output.

A system for remotely measuring the characteristics of water passing through a plumbing control device (PCD) includes a sensor within the interior of the PCD. The sensor is configured to measure characteristics of the water to obtain measured data. The sensor is also linked to a microcontroller of the PCD. An antenna board is linked, and configured to transmit power, to both the microcontroller and the sensor. A mobile device is configured to locate the antenna board. The mobile device transmits power to the antenna board which, in turn, transmits power to the microcontroller and the sensor. When power is not being transmitted from the antenna board, the microcontroller and the sensor are powered off.

A method for providing output values with associated uncertainties for a flexible modular plant or machine comprising an arrangement of modular entities, wherein uncertainty information associated with an operation of the modular entity is assigned to a plurality of modular entities and input values are provided based on an operation of the modular entities, where a computing unit calculates an output value based on said input values, calculates an input value uncertainty for each input value based on the uncertainty information of the modular entity, and calculates at least one output value uncertainty associated with the output value based on propagation of uncertainty and using the input value uncertainties, and where the output value and the at least one output value uncertainty are output.

A method and a user device (10) for adapting a signaling of the field device (100) that can be displayed via a signal display (102) of a field device (100) are proposed. For this purpose, an user device (10) is used to define a color tone of at least one display element (104) of the signal display (102) of the field device (100), an attribute is assigned to the defined color tone of the at least one display element (104) of the signal display (102), wherein the attribute represents a meaning of the determined color tone for indicating a state of the field device (100), and a control signal is transmitted from the user device (10) to the field device (100), wherein the control signal contains information regarding the determined color tone and regarding the attribute associated with the determined color tone.

A fault diagnosis apparatus for diagnosing a fault in a field device in a facility, includes: a processor that: acquires, from the field device, an alarm or a current output that represents abnormality in the field device; upon detecting first fault cause information corresponding to the alarm or to the current output in fault diagnosis information, specifies the first fault cause information as a cause of the fault in the field device; and notifies a user of the specified first fault cause information.

The present disclosure relates to a method for the application-specific setting of a field device, which is installed in a defined application in a process in automation engineering and determines or monitors at least one process variable of a medium, comprising: recording a diagnostic message which occurs or has occurred on the field device during a defined interval, analyzing which of the diagnostic messages are tolerable and/or plausible in the defined application, assigning an application-specific notice with regard to tolerability and/or plausibility to each diagnostic message that has arisen in the defined application, clearing the diagnostic message if this is classified as tolerable and/or plausible in the defined application, and using the application-specific setting of the field device, which clears the diagnostic message classified as tolerable and/or plausible.

A method for configuring an interface device connected to a control device and a field device, wherein the method includes receiving a first machine learning application having a plurality of logical components connected in a pipeline, where the first machine learning application serves to analyze a signal from the field device utilizing a first machine learning model, generating a plurality of code blocks utilizing a translator based on the plurality of logical components of the first machine learning application, connecting the plurality of code blocks in accordance with the pipeline of the first machine learning application to generate a first output from the signal from the field device, and deploying the connected code blocks on firmware of the interface device including creating a virtual port connectable to the control device, and where the virtual port serves to transmits the first output to the control device.