Patent Description:
<CIT> describes systems and methods for detection of anomaly events or error events within a process environment by implementing a hybrid of centralized classifier models and edge node based classifier models. It is described that this involves (i) receiving a first set of information from a first set of field devices located within a process control environment, (ii) transmitting a first input vector generated based on the first set of information, to a first anomaly detector implemented within an edge node configured to provide gateway access to said process control environment, wherein said first anomaly detector implements a first classifier model, (iii) responsive to the first anomaly detector detecting a anomaly event based on the transmitted first input vector, transmitting a second input vector to a second anomaly detector implemented within a cloud based server, and (iv) generating a anomaly event alert responsive to at least one of the first anomaly detector and the second anomaly detector detecting an anomaly event.

A mid-sized industrial plant needs to manage thousands of devices (field devices) producing lots of data. As some of this data needs to be processed fast, latency becomes a challenge. Thus, data processing is moved to computing nodes, so-called edge devices, that are placed on-premise, close to the devices generating the data.

Edge device can range from for example an embedded PC to a datacentre that is operated on the premises. Advantages of edge computing in addition to low latency and high bandwidth are, amongst others, improved availability and ease of managing privacy and security as confidential data can be kept on the plant. This opens the door for the deployment of device/asset monitoring applications, e.g., for predictive maintenance, on edge devices. Such applications may follow simple rule-based approaches but can also be more advanced and involve complex models, e.g., pretrained machine-learning and AI models.

In asset monitoring scenarios, there are usually multiple parties involved: different device providers, the automation system provider, and the plant owners/operators. The device providers know best how to monitor the provided devices, but the monitoring itself is done on the plant (industrial environment) where the device instance operates as part of a specific process. Thus, there needs to be a possibility to deploy a third-party asset monitoring algorithm to the edge device and use it as part of a configurable asset monitoring workflow. Such an asset monitoring workflow across company borders is, on one hand, complicated by different parties using different formats for specifying the involved assets, input data, and the computed monitoring results. On the other hand, the exchanged monitoring algorithm and its interfaces are not necessarily easy to integrate by different parties. This even holds if the monitoring algorithm is provided in-house as interfaces can be increasingly complex when dealing with different kinds of devices to be monitored. All this leads to expensive manual work that takes multiple days and results in an inflexible, error-prone integration that is difficult to be adapted and to be reused. Moreover, these tasks need to involve expert knowledge in software integration that the usual process engineers on a plant do not have.

Therefore, it would be advantageous to have an improved technique for the deployment of asset monitoring algorithms in edge computing environments. Such asset monitoring algorithms can be those developed by users or operators themselves, or algorithms provided by third parties.

Regarding the solution, there are specifications providing a structured asset specification for any physical or virtual asset, which consist of so-called submodels covering different aspects of the asset's lifecycle, like technical information, documentation or nameplate information.

In an aspect, there is provided an industrial field device monitoring system, wherein the system is configured to:.

In an example, the system is operating in a cloud computing environment.

In an example, the system is operating on one or more on-premise servers.

In an example, the system is operating on one or more off-premise servers.

Thus, the system can be on-premise or off-premise or "in the cloud".

In an example, the system is configured to provide the asset monitoring submodel to a generator to generate a configuration file to register the asset monitoring application at the edge device.

In an example, the system is configured to generate endpoints to access contents of the asset monitoring submodel, and wherein the endpoints comprise endpoints from the deployed asset monitoring application.

In an example, the generation of the workflow function comprises utilization of the endpoints from the deployed asset monitoring application.

In an example, the system is configured to register the asset monitoring submodel at the edge device.

In an example, the asset specification of the field device comprises device individual information for the field device. The generation of the workflow function can then comprise utilization of the device individual information for the field device.

In an example, the system is configured to register the asset specification of the field device at the edge device.

In a second aspect, there is provided an industrial field device monitoring system, wherein the system comprises an edge device, and wherein the system is configured to:.

In an example, parts of the system other than the edge device can be operating in a cloud computing environment.

In an example, parts of the system other than the edge device can be operating on one or more on-premise servers.

In an example, parts of the system other than the edge device can be operating on one or more off-premise servers.

In an example, the edge device can continuously invoke the workflow function exposed by the asset monitoring application with the data received from the field device
In an example, the system is configured to register the asset monitoring submodel at the edge device.

In an example, the asset specification of the field device comprises one or more asset specification submodels. The system is configured to generate a new asset specification submodel based on the information downloaded, deployed and/or registered to the edge device.

In a third aspect, there is provided an industrial field device monitoring method, comprising:.

In a fourth aspect, there is provided an industrial field device monitoring method, comprising:.

According to another aspect, there is provided a computer program element controlling one or more of the systems as previously described which, if the computer program element is executed by a processor, is adapted to perform the methods as previously described.

According to another aspect, there is provided a computer readable medium having stored a computer element as previously described.

The computer program element can for example be a software program but can also be a FPGA, a PLC or any other appropriate digital means.

<FIG> relate to industrial field device monitoring systems and methods.

An exemplar industrial field device monitoring system is configured to:.

According to an example, the system is configured to provide the asset monitoring submodel to a generator to generate a configuration file to register the asset monitoring application at the edge device.

According to an example, the system is configured to generate endpoints to access contents of the asset monitoring submodel. The endpoints comprise endpoints from the deployed asset monitoring application.

According to an example, the generation of the workflow function comprises utilization of the endpoints from the deployed asset monitoring application.

According to an example, the system is configured to register the asset monitoring submodel at the edge device.

According to an example, the asset specification of the field device comprises device individual information for the field device. The generation of the workflow function can then comprise utilization of the device individual information for the field device.

According to an example, the system is configured to register the asset specification of the field device at the edge device.

In an example, the workflow function maps field device signals of the data generated by the field device to a function signature.

An exemplar industrial field device monitoring system comprises an edge device, and the system is configured to:.

In an example, the edge device can continuously invoke the workflow function exposed by the asset monitoring application with the data received from the field device.

In an example, the system is configured to generate endpoints to access contents of the asset monitoring submodel. The endpoints comprise endpoints from the deployed asset monitoring application.

According to an example, the asset specification of the field device comprises one or more asset specification submodels. The system is configured to generate a new asset specification submodel based on the information downloaded, deployed and/or registered to the edge device.

An exemplar industrial field device monitoring method comprises:.

It is to be noted that the downloading the asset specification of a field device to an edge device and receiving the asset monitoring submodel can occur in two steps or can occur in one step. For example, a monitoring submodel can be embedded into the download of the asset specification/field device specification.

In an example, the method comprises providing the asset monitoring submodel to a generator to generate a configuration file to register the asset monitoring application at the edge device.

In an example, the method comprises generating endpoints to access contents of the asset monitoring submodel, and the endpoints comprise endpoints from the deployed asset monitoring application.

In an example, the generating the workflow function comprises utilizing the endpoints from the deployed asset monitoring application.

In an example, the method comprises registering the asset monitoring submodel at the edge device.

In an example, the asset specification of the field device comprises device individual information for the field device. The generating the workflow function can then comprise utilizing the device individual information for the field device.

In an example, the method comprises registering the asset specification of the field device at the edge device.

In an example, the method comprises continuously invoking by the edge device the workflow function exposed by the asset monitoring application with the data received from the field device.

In an example, the asset specification of the field device comprises one or more asset specification submodels. The method can then comprise generating a new asset specification submodel based on the information downloaded, deployed and/or registered to the edge device.

Thus, systems and methods for deployment and integration of asset monitoring applications based on standardized asset specifications have been developed.

The ability to deploy asset monitoring algorithms to an industrial plant in the new manner provides improved quality in predicting device health. An asset monitoring workflow across company borders is complicated due to different parties using different formats for specifying the involved assets, input data, and monitoring results. Also, the exchanged monitoring algorithm and its interfaces are not easy to integrate by different parties. This leads to expensive, time-taking, and error-prone manual work. This has been addressed in the new systems and methods described here, that provide methods and systems to support integrating and deploying third-party monitoring algorithms on the plant. The systems and methods combine standardized asset specifications, an edge ecosystem with applications running on edge devices, functions and container orchestration systems. Thereby, this approach implements a collaborative asset monitoring scenario with information exchange across company borders. The major benefits are minimized time, effort, and skills needed for deployment of third-party asset monitoring applications on an industrial plant.

Continuing with the figures, the industrial field device monitoring systems and methods are described in further detail, with respect to specific embodiments.

The system (see <FIG> that shows a system architecture) contains an Edge device, and additional services deployed in the cloud: An Edge Management Portal to manage edge devices and their applications, a Container Orchestration System to manage the containers running the implementations of the edge applications, and an Edge Function Workflow Manager to specify workflows composed from runnable functions invoked from the applications.

The edge device is connected to the devices to be monitored. The devices to be monitored can also be termed field devices. The edge device contains an Asset Specification Server to provide access to the contents of asset specifications on the edge, an Asset Specification Registry to locate the asset specifications, and a Computation Engine to schedule the actual functions running on the edge and accessing the asset specifications.

An example of the system does not need to include the edge device.

The method for deploying and integration asset monitoring applications consists of four main phases (see <FIG> that shows steps of the method for deploying and integration third-party asset monitoring applications). It is executed as follows:.

Following Industry <NUM> principles, along with the device, the device provider provides the asset specification of the device to the plant operator. An asset specification provides information on an asset and operations to interact with it in a standardized way. The asset specification is structured by aspects (e.g., lifecycle phases) in various submodels. In addition, the device provider provides an asset monitoring algorithm tailored to the provided device or its type in the form of a software container. The interface and metadata of that algorithm is specified in an asset monitoring submodel that the device provider provides to be added to the standardized asset specification.

Furthermore, the plant operator has the device to be monitored connected to an edge device to collect the data and to serve as a platform to deploy software components accessing this data. This data can contain device parameters or its operational values.

The plant operator uses the Edge Management Portal and the Asset Specification Server to download the asset specification of the device received from the device provider to the edge device. The Asset Specification Server takes care of providing endpoints to access the contents of the asset specification submodels and registers them at the Asset Specification Registry.

The plant operator feeds the asset monitoring submodel received from the device provider to the Edge Management Portal, which uses a generator to generate configuration files to register the asset monitoring application in the portal and to deploy it via the Container Orchestration System to the edge device (since the monitoring application is packaged as a software container). There, it will provide endpoints to access the contents of the asset monitoring submodel and register it at the Asset Specification Registry. The asset monitoring application is specific to the device type. Its functions can be invoked for multiple device instances (see deployment of monitoring function).

The edge's Computation Engine is required to be able to invoke the function exposed by the asset monitoring application with the data streamed in from device instances (the device instance to be monitored or also further devices delivering relevant data to assess the condition of the device to be monitored) as input parameters. Thus, the plant operator provides the system with the relevant device instance IDs. In addition to these IDs, the system takes the function's interface specification from the asset monitoring submodel as well as the endpoints from the deployed asset monitoring application, to generate a function workflow. As part of this workflow, the device signals are mapped to the asset monitoring function signature. The system can recommend such a mapping based on data types and semantic IDs, but it may be corrected or completed or refined by the process engineer in the next step. Afterwards, the function workflow can be started.

As the asset monitoring algorithm/function may access the asset specification (which may partially reference parts deployed on different systems and organizations), it has access to device data usually not being available on the edge, e.g., specific monitoring parameters, knowledge from other lifecycle phases stemming from other parties, like maintenance staff, or other kinds of context information.

The monitoring results calculated by the asset monitoring function can be provided to a third party (e.g., back to the device provider). For this purpose, the asset specification server can be used to transform the internal representation of the information on the edge into a submodel the standardized asset specification (see <FIG>).

The asset specifications' modularity enables the operator to select only specific submodels to be created, i.e., he can control which data will become part of the standardized asset specification to leave the plant and which not. The exchange of the asset submodels with another party can be managed either by file transfer or by allowing secured and party-specific live access to the asset specification server on the edge device (e.g., using role-based access control).

Thus, the new industrial field device monitoring systems and methods provide a method and system to support the process engineer in integrating and deploying monitoring algorithms on the edge devices installed on the plant. The system expects the properties of the monitored asset to be specified in an interoperable format and the monitoring algorithm to be available as a software-container with an invokable interface that is specified as part of the asset specification.

The system integrates standardized asset specification infrastructure into an edge ecosystem to deploy and run applications and functions on edge devices. It combines standardized asset specifications with edge applications, functions and software container orchestration systems for the purpose of integrating third-party and other monitoring applications. Thereby, it implements a collaborative asset monitoring scenario with information exchange across company borders. In addition, it provides a platform for asset monitoring applications incorporating information from multiple lifecycle phases and additional context information.

The method uses the system to turn a standardized asset specification and the monitoring algorithm provided by a third party into a runnable function and to deploy and run it on an edge device, accessing information from the asset specification and returning the results in an interoperable format.

The major benefits are minimized time, effort, and skills needed for deployment of asset monitoring applications on the edge device. At the same time, asset monitoring applications are enabled to make use of additional asset information, which increases the prediction quality and thereby the reliable operation of the devices and, hence, the plant.

Thus, in summary the new technology relates to:.

In another exemplary embodiment, a computer program or computer program element is provided that is characterized by being configured to execute the method steps of the method according to one of the preceding embodiments, on an appropriate processor or system.

Moreover, it may be configured to operate the components of the above described system.

This exemplary embodiment of the invention covers both, a computer program that right from the beginning uses the invention and computer program that by means of an update turns an existing program into a program that uses the invention.

Claim 1:
An industrial field device monitoring system, wherein the system is configured to:
download an asset specification of a field device to an edge device, wherein the field device is located in an industrial environment, wherein the field device is configured to generate data relating to an asset of the industrial environment, wherein the edge device is located in the industrial environment, and wherein the edge device is configured to receive the data generated by the field device;
receive an asset monitoring submodel for the field device, wherein the asset monitoring submodel specifies an interface specification and algorithm of an asset monitoring application for the field device;
deploy the asset monitoring application for the field device to the edge device, wherein the deployment comprises utilization of the asset monitoring submodel; and
generate a workflow function exposed by the asset monitoring application, wherein the generation of the workflow function comprises utilization of the asset specification of the field device and the interface specification of the asset monitoring submodel.