System and method for monitoring product processing equipment in an industrial plant - Patents.com

Abstract

A system for monitoring a product processing device (20, 30) of an industrial plant is provided. The system comprises a first layer (100) having a plurality of sensors (110-150) configured to detect parameters of the product processing device (20, 30) of the industrial plant, a second layer (200) configured to implement a process control system based on data from the first layer (100), and a third layer (300) configured to implement an operational control system. The system further comprises at least one IoT edge unit (230, 310) in the second and / or third layer (200, 300) configured to receive data from the first and / or second layer (100, 200) and analyze the received data, and an IoT hub (700) configured to remotely control, manage, and / or monitor the at least one IoT edge unit (230, 310).

Description

[Technical field]

[0001] FIELD OF THEINVENTION The present invention relates to a system and method for monitoring product processing equipment in an industrial plant. [Background technology]

[0002] FIELD OF THEINVENTION Industrial plants, such as chemical production plants, are highly security-sensitive production environments. For example, chemical plants typically include multiple assets for producing chemical products. Such plants have multiple sensors distributed for data collection as well as monitoring or control purposes. Industrial production therefore results in huge amounts of data. Therefore, there is great interest in applying new techniques in cloud computing and big data analytics. However, unlike other manufacturing industries, process industries are subject to very high security standards. For this reason, computing infrastructures are usually highly compartmentalized with restrictive access to monitoring and control systems. Therefore, latency and availability considerations are against simply migrating current embedded control systems to cloud computing systems or data analytics systems, etc. Thus, bridging the gap between highly proprietary industrial manufacturing systems and cloud technologies is a challenge. Summary of the Invention [Means for solving the problem]

[0003] Summary of the Invention It is an object of the present invention to provide a system and method for monitoring industrial plant equipment, in particular product processing equipment of an industrial production (or product processing) plant, such as a chemical product processing or production plant, that allows for improved and robust communication with cloud applications.

[0004] According to one aspect of the present invention, a system for monitoring product processing equipment of an industrial plant is provided. The system comprises a first layer having a plurality of sensors configured to detect parameters of the equipment of the industrial plant. The system further comprises a second layer configured to implement a process control system based on data from the first layer. The system also comprises at least one Internet of Things IoT edge unit in the second or third layer for receiving data from the first or second layer and analyzing the received data. Further, an Internet of Things IoT hub is provided for remotely controlling, managing, and / or monitoring the IoT edge devices.

[0005] According to an embodiment of the invention, the system also comprises an interface coupled to the first and / or second processing layers, configured to receive data from the first and / or second layers and to pre-process the received data. The interface comprises or is implemented as an IoT Edge unit. The interface comprises an analyzer configured to add metadata to data from the multiple sensors. The interface is configured to analyze the received data and to output the processed data to a data sink, such as a central data sink. The interface is configured to allow only one-way data communication to the (central) data sink. In particular, the received data may be data received from the first and / or second layers or pre-processed received data. The IoT Edge unit constituted by or implementing the interface may be at least one of the at least one IoT Edge unit of the system.

[0006] The data sink may be implemented as a cloud-based data sink, for example a central data sink, such as a cloud server or a cloud-based service.

[0007] According to a further embodiment of the invention, the interface comprises an analyzer configured to analyze the received data and add metadata, a data buffer, a key performance indicator KPI calculator configured to determine at least one key performance indicator KPI based on the data in the buffer, and an upload selector configured to select data to be transferred from the received data to the data sink.

[0008] A KPI calculator allows to determine key performance indicators that can be transferred to the data sink. It is thus possible to significantly reduce the amount of data that needs to be transferred to the data sink without losing much information from the data. This also results in a significantly reduced amount of traffic between the interface and the data sink, which can be implemented as a cloud service. According to a further aspect of the invention, the metadata comprises time information, in particular timestamp or time shift information, and / or information about the respective sensor that detected the data.

[0009] If the metadata includes time information, it is also possible in a system for monitoring industrial plant equipment to compare data from different industrial plant equipment or from different sensors in or for the industrial plant equipment. Due to the sensor related metadata (sensor ID, sensor type, etc.) different types of sensors can be analyzed even if they are distributed across different industrial plants or different subdivisions of an industrial plant. The metadata can be compared with metadata and raw data, for example, in a data sink. According to a further aspect of the invention, the second layer comprises a condition monitoring system and / or a machine protection system. The interface is configured to analyze data from the content monitoring system and / or the machine protection system, add metadata to the output data, process the data to reduce the amount of data if necessary, and output the processed data to the data sink. In particular, the output data can be data output by the condition monitoring system and / or the machine protection system. In particular, the processed data can be output data, optionally provided together with metadata, if indicated by the analysis.

[0010] According to one aspect of the present invention, a method for monitoring the mentioned industrial plant equipment is provided. In a first layer, a plurality of sensors detect parameters of the equipment of the industrial plant. In a second layer, a process control system base is implemented based on data from the first layer. The system also comprises at least one Internet of Things IoT edge unit in the second or third layer for receiving data from the first or second layer and analyzing the received data. Further, an Internet of Things IoT hub is provided for remotely controlling, managing, and / or monitoring the IoT edge devices.

[0011] According to an embodiment of the present invention, an interface implemented as an IoT edge unit receives data from the first and / or second layers and pre-processes the received data. An analyzer in the interface adds metadata to the data from the multiple sensors. The received data is analyzed in the interface and the processed data is output to a data sink. The interface is configured to allow only one-way data communication to the data sink.

[0012] In one aspect of the invention, a system is provided for monitoring the mentioned industrial plant equipment. The system comprises a first layer with a plurality of sensors measuring parameters of components of the industrial plant. The system also comprises a second layer related to a process control system of the industrial plant. Data from sensors in the industrial plant are extracted and provided with metadata such as time information (timestamp) and / or information about the sensors (such as name, type, ID). The data and optionally the metadata are pre-processed to reduce the amount of data, if necessary. The data is then transferred to a cloud service where the data can be analyzed or further processed. In other words, existing data in the industrial plant is reused for analytical purposes. According to one aspect of the invention, a method is provided for pre-processing or preparing data for subsequent processing outside the first and second layers of the automation architecture. In particular, data from various sensors across the plant can be harmonized (with respect to time codes or time information and other metadata) and collected in a (central) location for further in-depth analysis.

[0013] According to an aspect of the invention, an industrial plant may comprise a control system for controlling the operation of elements of the industrial plant. The industrial plant comprises a number of sensors for monitoring equipment of the industrial plant. The industrial plant may also comprise a condition monitoring system CMS, a machine protection system MPS, and / or a process information management system PIMS. The monitoring system may use or share hardware of the control system of the industrial plant. It should be noted, however, that the monitoring system may only receive data from the control system (such as data from sensors, condition monitoring system, machine protection system, and / or process information management system). The monitoring system according to an aspect of the invention cannot and is not permitted to transmit data to sensors or other systems of the control system. Furthermore, the monitoring system cannot and is not permitted to affect the operation of the control system. The monitoring system according to an aspect of the invention simply uses data from sensors, condition monitoring system CMS, machine protection system MPS, process information management system PIMS for monitoring purposes. Thus, the respective data may first be used for the control of the industrial plant and then also be reused for monitoring purposes.

[0014] Although the monitoring system may share hardware with the control system, the operation of the monitoring system does not interact with or affect the industrial plant's control system.

[0015] According to one aspect of the invention, there is provided an industrial plant comprising at least one industrial plant equipment, a control system having a first layer having a plurality of sensors configured to detect parameters of the industrial plant equipment, and a second layer configured to implement a process control system based on data from the first layer, the plant also comprising a system for monitoring a product processing equipment as described above.

[0016] The present invention also relates to a method for monitoring a product processing device in an industrial plant by a monitoring system, the monitoring system having a first layer with a plurality of sensors for detecting parameters of the device, a second layer implementing a process control system based on data from the first layer, and a third layer implementing an operational control system, the third layer including the steps of: data being received from the first and / or second layers, and the received data being analyzed in at least one Internet of Things IoT edge unit in the second and / or third layers, the at least one Internet of Things IoT edge unit remotely controlling, managing and / or monitoring in or by an Internet of Things IoT hub.

[0017] According to one aspect of the invention, a computer program for monitoring a product processing apparatus, the computer program comprising code means for causing the system to carry out the method described above, when the program is executed on a computer controlling the system.

[0018] According to an embodiment of the present invention, the equipment monitored by the sensor may be a rotating machine such as a motor, a centrifuge, or the equipment may be a reciprocating pump, a compressor, etc. The equipment may also be a fractionation or distillation column, a chemical reactor, and / or a laboratory device. The equipment may also be a process plant, a flare stack, a combustion chamber, a filling plant, a packaging plant, or a dryer.

[0019] The control system of an industrial plant may be implemented as a pyramid according to the automation pyramid or the NAMUR pyramid.

[0020] The interface may be implemented as an edge unit (e.g., placed at the edge of the system to reduce data traffic with a data sink in the cloud) or may share the hardware resources of an edge unit.

[0021] Edge computing, performed for example by IoT edge units, refers to distributed computing power located in the vicinity of data sources. Thus, instead of locating computing power exclusively in the cloud, multiple IoT edge units can be provided in or near industrial plants. This is advantageous as it can reduce the required bandwidth towards the cloud and also reduce processing latency.

[0022] It is to be understood that the above-mentioned aspects, in particular the system for monitoring a product processing device according to claim 1, the method according to claim 9 and the computer program according to claim 10, have similar and / or identical preferred embodiments, in particular as defined in the dependent claims.

[0023] It is also to be understood that preferred embodiments or aspects of the invention may also be any combination with the dependent claims or with the respective independent claims of the above-mentioned embodiments or aspects.

[0024] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter. [Brief description of the drawings]

[0025] [Figure 1] FIG. 1 is a schematic diagram illustrating a system for monitoring an industrial plant. [Diagram 2] FIG. 2 is a schematic diagram of a portion of the system of FIG. 1. [Diagram 3] FIG. 2 illustrates a portion of the first and second layers of the system of FIG. 1. [Figure 4] FIG. 2 is a schematic block diagram of an interface according to an aspect of the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] Detailed Description In an industrial plant (e.g. a chemical plant), a large number of devices are typically used to produce a desired product, the parameters of which must be sensed and the devices are controlled by a control system based on the sensed parameters.

[0027] For example, industrial production of chemical processes usually starts with an upstream product, which is used to generate further downstream products. The value chain production through various intermediate products to the final product is highly constrained and based on separate infrastructures. This is a disadvantage for the introduction of new technologies such as the Internet of Things (loT), cloud computing, and big data analytics. Process industries are subject to very high standards, especially with regard to availability and security. Therefore, the computing infrastructure is usually unidirectional and isolated, with highly constrained access to the monitoring and control systems of the chemical plants. In general, chemical production plants are embedded in an isolated manner with different layers within the enterprise architecture to achieve functional separation between operational technology and information technology solutions. These layers are described in the automation pyramid or the NAMUR pyramid.

[0028] The industrial plant may be embodied as a chemical plant, a chemical processing plant, or a chemical product processing plant.

[0029] FIG. 1 is a schematic diagram illustrating a system for monitoring an industrial plant. A first layer 100 is related to a physical process in the plant 100. In the first layer 100, a number of sensors 110, 120 are arranged to measure or determine various parameters of the devices 20, 30 in the plant 100. Furthermore, the first layer 100 may be related to intelligent devices for sensing and manipulating the physical process, for example via process sensors, analyzers, and actuators. A second layer 200 is related to a process control system for the industrial plant 100 or a part of the industrial plant 100. The second layer 200 may comprise a number of processing units, such as a condition monitoring system CMS 210, a machine protection system MPS 220, and / or an analysis unit 230 that may perform analysis operations. The condition monitoring system CMS 210, the machine protection system MPS 220, and / or the analysis unit 230 use data from the sensors 110, 120 in the first layer 100 as inputs for performing their respective functions or processing operations. Thus, the second layer 200 is used to supervise, monitor and control the physical processes in the industrial plant. Real-time control and software, process information management systems PIMS, human machine interfaces HMI, supervisory and data acquisition SCADA software can also be part of the second layer 200.

[0030] The third layer 300 relates to operational control systems, i.e. manufacturing / production operations systems for managing the production workflow to produce the desired product. Here, a process information management system PIMS 330 may be provided. Furthermore, a condition monitoring system 320 and / or a further analysis unit 310 may be provided. Furthermore, batch management, manufacturing execution / operations management systems (MES / MOMS), laboratory, maintenance and plant performance management systems, data historians and related middleware may be further components of the third layer 300. The time frame for control and monitoring may be shifts, hours, minutes, seconds.

[0031] The analysis units 230, 310 may be implemented as Internet of Things IoT edge units. The analysis units 230, 310 each include an analysis component 231, 311, an IoT edge 232, 312, and a container 233, 313.

[0032] The analysis unit 310 may include an IoT edge unit 312, an analysis component 311, and a container 313.

[0033] Edge computing, for example performed by IoT Edge, refers to distributed computing power located in the vicinity of data sources. Thus, instead of locating computing power exclusively in the cloud, multiple edge units can be provided in or near industrial plants. This is advantageous because it can reduce the required bandwidth towards the cloud and also reduce processing latency.

[0034] According to the invention, at least one IoT Edge unit 230, 310 may be provided in the second and / or third layer 200, 300 (and also optionally in the fourth layer 400). These IoT Edge units 230, 310 may perform part of the required computing or processing. As an example, the interface 600 may be implemented as an IoT Edge unit 310 or as an IoT Edge unit 230.

[0035] By the IoT edge units 230, 310, some of the processing required in or for the fifth layer 500 (cloud) may be performed in the second layer, the third layer, or the fourth layer. In particular, data may be pre-processed before it is forwarded to the data sink 530. In this way, data traffic and latency may be improved.

[0036] Further, an Internet of Things (IoT) Hub 700 is provided, for example within the fifth layer 500. The IoT Hub 700 is coupled to each of the IoT Edge units 230, 310. Preferably, communication between the IoT Edge units 230, 310 and the IoT Hub 700 involves encrypted communication.

[0037] According to one aspect of the present invention, the IoT hub 700 is used to remotely control, manage, and / or monitor the IoT edge units 230, 310.

[0038] The IoT hub 700 may include a container deployment unit 710, a recovery unit 720, a service unit 730, a pipeline unit 740, and / or a test unit 750.

[0039] According to one aspect of the present invention, the container deployment unit 710 is used for the deployment of containers 233, 113 in the IoT edge units 230, 310. This may include managing and updating software packages in the containers. Furthermore, the container deployment unit 710 is responsible for software updates, encrypted communication with the IoT edge units 230, 310. Furthermore, the pipeline unit 740 may be responsible for the CI / CD pipeline. Moreover, the deployment of software in the containers may be automated. The IoT hub 700 may also be responsible for updating the respective containers 213, 313 regarding software time and version.

[0040] The test unit 750 of the IoT hub 700 may also be responsible for performing tests on the IoT edge units 230, 310. The tests may relate to the integrity of the IoT edge units 230, 310.

[0041] Moreover, the IoT Hub 700 may analyze the data input and output towards the IoT Edge unit, so that IO validation can be performed. Furthermore, the IoT Hub may adjust or harmonize the parameters received from the IoT Edge unit.

[0042] The IoT Hub 700 may also comprise a disaster recovery unit 720 responsible for backup strategies, automatic backup of the configuration of the IoT Edge units, redeployment of configuration of new and replaced hardware, and / or automatic provisioning of hardware.

[0043] The IoT hub 700 can monitor the containers and, in particular, the resources of the containers. Additionally, the IoT hub can monitor the hardware components of the IoT edge units. These hardware components can include CPU, RAM usage, storage monitoring, and I / O monitoring.

[0044] According to one aspect of the invention, a CI / CD (Continuous Integration / Continuous Delivery) pipeline is provided to deliver new versions of software in containers from the IoT hub 700 to the IoT edge units 230, 310.

[0045] In particular, the IoT hub 700 is coupled to the containers 233, 313 via encrypted communication links.

[0046] The fourth layer 400 relates to business logistics systems for managing business related activities of manufacturing operations. ERP is the main system and establishes the basic plant production schedule, material usage, shipment, inventory layers. Time frames can be months, weeks, days, shifts. The fifth layer 500 relates to cloud services 500. Cloud services 500 can comprise a data sink 530 that can be implemented as a cloud server or cloud service. Data sink 530 can be a central data sink or multiple distributed or mirrored data sinks.

[0047] The above layers may implement strict one-way communication protocols that do not allow data inflow to the first layer 100. In addition to such an automation structure or architecture, an external company network or the corporate external Internet may be provided, but is not coupled to the first, second and third layers due to security considerations. In this context, the challenge is to leverage the advantages of cloud computing and big data while still ensuring the established advantages of the existing architecture, namely high availability and reliability of the lower layer systems (first layer 100) and cybersecurity.

[0048] According to one aspect of the invention, an IoT edge unit is provided that functions as an interface 600, which can operate independently from the processing units 210, 220, 230 in the second layer 200, and allows data (output data) from the sensors 110, 120 or the processing units 210, 220, 230 in the second or third layer 300 to be used for analytical purposes. This data is not used to control or influence the operation of the existing automation architecture (first, second, third, fourth layers 100-400), but an improved interface 600 is provided to extract data and parameters from the devices 20, 30 of an industrial plant, process the data if necessary, and output the data to a data sink 530 in the fourth layer 400 or fifth layer 500. The interface 600 only allows one-way communication from the sensors to the data sink 530.

[0049] According to one aspect of the invention, the IoT edge unit functioning as the interface 600 may use or share existing hardware or services in the second or third layer 200, 300 to perform its operation. The interface 600 may be used to extract data from various sensors sensing parameters from various types of devices 20, 30 and / or from various processing units in the second or third layer 200, 300 and store the data in the data sink 530. However, before the data can be stored in the data sink 530, the data must be analyzed, pre-processed and / or possibly harmonized (e.g. with respect to their time information). The functionality and operation of the interface 600 is independent of the operation of the automation architecture.

[0050] The core process system provides process or asset specific data of an industrial plant, e.g., a chemical plant contextualizes the process or asset specific data of the chemical plant. Furthermore, the plant specific data of the (chemical) plant may be provided to the fifth layer via an interface layer. Here, plant specific data may refer to contextualized process or asset specific data. The process or asset specific data may include values, qualities, times, units of measure, asset identifiers.

[0051] Through contextualization, further context can be added, such as plant identifier, plant type, reliability indicators, or alarm limits of the plant. In a further step, the technical asset structure of one or more plants or sites and other asset management (e.g., asset networks) and even application context (e.g., model identifiers, third party exchanges) can be added.

[0052] The fifth layer 500 may be a computing or cloud environment that provides virtualized computing resources, such as data storage and computing power. Plant-specific data from one or more chemical plants may be provided to an external service. Such data may be provided in real time or on demand. Furthermore, data transfer to and / or from external services may be performed in real time or on demand. The fifth layer 500 may be used to store, contextualize, or aggregate plant-specific data from two or more chemical plants and / or to store historical data from two or more chemical plants. In this way, data storage may be externalized, the required on-premise storage capacity may be reduced, and historical transfer may be made redundant. The fifth layer 500 may comprise a data sink 530.

[0053] Additionally, the interface 600 and / or the fifth layer 500 may be configured to exchange data with third party management systems, e.g., via integration of third party external processing layers, enable visualization of data, enable computing process workflows, enable data calculations, enable APIs to access data, enable metadata for data storage, transfer, and calculations, provide an interactive plant data work environment for users, e.g., operators, and verify and improve data quality.

[0054] The fifth layer 500 may be configured as a centralized cloud computing platform. The fifth layer 500 may be configured as a manufacturing / production / processing data workspace with full data integration across multiple plants, including transport and streaming of manufacturing / production / processing data history, collection of all data from all edge components. In this way, full contextualization of all lower layer contexts may be integrated on the fifth layer 500 for multiple plants. In this way, the fifth layer 500 may be further configured to run cloud native apps, connect with external PaaS and Saas tenants, integrate machine learning with manufacturing data and processes, deploy training tests, and / or visualize data, access and orchestrate apps.

[0055] The above system architecture allows for a bottom-up contextualization concept, where all information available on the lower layers may already be added as attributes to the data, so that the context of the lower layers is not lost. Here, the first layer 100 as the lowest context layer may contain measurements and data that are contextualized with respect to the parameters on which the measurements were performed. The second or third layers 200, 300 may be further contextualized by further adding tags related to the individual chemical plants.

[0056] The contextualization concept may cover at least two basic types of context. One type may be a functional location in a production environment with multiple chemical plants. This may cover information about what and where this data point represents inside the production environment. Examples are association with a functional location, attributes for which physical asset the data was collected, etc. This context may be beneficially used for later applications to explain which data is available for which plants and assets.

[0057] The fifth layer 500 comprises an IoT hub 700 coupled to the IoT edge unit 232 in the second layer 200 and the IoT edge unit 312 in the third layer 300.

[0058] FIG. 2 is a schematic diagram of a part of the system of FIG. 1. In FIG. 2, a number of sensors 110, 120 belonging to the first layer 100 and a number of processing units 210, 220, 230, 240 from the second layer 200 are shown. The sensors 110, 120 output measurement data, which are input to input / output units (IO cards) 211, 221, 230a of the CMS unit 210, the MPS unit 220, or the analysis unit 230, respectively. The IO units 211, 221, 230a can add metadata to the measurement data from the sensors 110, 120. This metadata can include time information, such as a timestamp. The time information, for example in the form of a timestamp, can be received from an NTP server 800. The measurement data together with their metadata can be processed in the units of the second layer 200. The output of these units 210-230 can be forwarded to an IoT edge unit acting as an interface 600. Here, the data may be analyzed, pre-processed, and / or conditioned before the data is forwarded to a data sink 530 in the fourth or fifth layer 400, 500. The interface 600 may share processing resources of, for example, the analysis unit 230 or 310. Alternatively, the interface 600 may have dedicated resources. The interface 600 may have a digital output 601 and / or an analog output 602 towards the data sink 530.

[0059] The metadata includes time information from a timestamp generator, which may generate timestamps using the Network Time Protocol NTP from an NTP server 800.

[0060] FIG. 3 shows a part of the first and second layers of the system of FIG. 1. Here, sensors 130-150 are provided to measure parameters of equipment in an industrial plant 100. Data from the sensor 150 is forwarded to a data splitter 151. An output of the data splitter 151 is forwarded to the MPS unit 220, which uses the data to perform machine protection actions. An output of the data splitter 151 is forwarded to the IO unit 211, where a timestamp can optionally be introduced as metadata. An output of the sensor 140 is received by the IO unit 241. The IoT edge unit 230 acting as an interface 600 can be implemented as an industrial PC IPC, which can for example be coupled to the IO unit 241 and / or the IO unit 211 and can add metadata (in the form of a timestamp). The IPC 600 can be coupled to a timestamp generator 610 (like an NTP server) to generate a timestamp and introduce it as metadata.

[0061] The units of the first, second and third layers 100, 200, 300 are data sources and may be a Machine Protection System MPS, a Condition Monitoring System CMS or an industrial PC. In addition, the output of a sensor (via an I / O unit) may be a data source. Furthermore, a Process Information Management System (PIMS) or a Laboratory Information Management System (LIMS) may also be a data source.

[0062] FIG. 4 shows a schematic block diagram of an interface according to an embodiment of the present invention. The interface 600 is implemented as an IoT edge unit and can receive output data from the processing units 210, 220, 230, from the second level 200 or from the sensors 110-150 in the first level 100. The interface 600 optionally comprises a data converter 605, an analyzer 610, a (ring) buffer 620, a key performance indicator KPI calculator 650, an upload selector 630, and an uploader 640. The IoT edge unit 600 is coupled to an IoT hub 700. Thus, the IoT hub can control the data converter 605, the analyzer 610, the (ring) buffer 620, the KPI calculator 650, the upload selector 630, and the uploader 640. The analyzer 610 is provided to analyze data from the input sources 210, 220, 230 and add metadata if necessary. The metadata 10 can be time information such as a timestamp. The time information may also relate to a time shift, i.e. a shift in timing information of the received data. This may be necessary if the respective data is compared or analyzed against other data. The received and possibly analyzed data may be stored in a (ring) buffer 620. If the amount of data from a particular source is too large, a KPI calculator 650 may calculate key performance indicators KPIs based on the data in the buffer 620. The KPI calculator 650 may forward the KPIs to the data sink 530. If the amount of data is not too large, an upload selector may select the data to be uploaded to the data sink 530. This data may be uploaded by the uploader 640.

[0063] The sensors 110-150 can be high frequency HF sensors, such as temperature sensors, pressure sensors, current sensors, position sensors, vibration sensors, or optical sensors (such as video cameras, bars, optical fibers, etc.).

[0064] The interface 600 may be implemented or integrated in an IoT edge unit (e.g., analyzer 230 and / or 310). The interface may receive data from the first layer 100 (sensors 110-150), from the second layer (CMS 210, MPS 220), and / or from the third layer 300 (CMS 320, PIMS 330). It should be noted that the interface 600 may receive data only from within the first layer, second layer, or third layer and not from external sources. The interface 600 may receive raw data (sensor data) as input from sensors and / or from processing units 210, 220, 230, 240 in the second layer 200. Depending on the processing units 210-240, the interface 600 may also receive only key performance indicators. The protocol of the data may be a proprietary protocol. Data can be received as analog or digital signals (Modbus, OPC-UA).

[0065] The interface 600 may analyze the incoming data. If the amount of data from one of the data sources is too large, the amount of data must be reduced, for example by determining key performance indicators, and the KPIs must be forwarded to the data sink 530 together with metadata instead of the raw data.

[0066] In the data sink 530, the input data may be analyzed using, for example, big data techniques.

[0067] A single unit device or system may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Procedures such as analyzing data and adding metadata to data performed by one or more units or devices can be performed by any other number of units, devices or systems. These procedures may be implemented as program code means of a computer program and / or as dedicated hardware. The computer program product may be distributed by storage / media on any suitable medium, such as an optical storage medium or a solid medium supplied together with or as part of other hardware, but also in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0068] Any reference signs in the claims shall not be construed as limiting the scope. [Explanation of symbols]

[0069] List of References 10 Metadata 20 Processing equipment 30 Processing equipment 100 1st Layer 110 Sensors 120 Sensors 130 Sensors 140 Sensors 150 Sensors 151 Data Splitter 200 Second Layer 210 Condition Monitoring System CMS 211 Input / Output Unit (IO Card) 220 Machine Protection System MPS 221 Input / Output Unit (IO Card) 230 Analysis Units 230a Input / Output Unit (IO Card) 231 Analysis Components 232 IoT Edge Unit 233 Container 240 Multiple Processing Units 241 units 300 Third Layer 310 Analysis Unit 311 Analysis Component 312 IoT Edge 313 Container 320 Condition Monitoring System (CMS) 330 Process Information Management System (PIMS) 400 The Fourth Layer 500 5th Layer 530 Data Sink 600 Interface 601 Digital Output 602 Analog Output 605 Data Converter 610 Server 620 (ring) buffer 630 Upload Selector 640 Uploader 650 KPI Calculator 700 IoT Hub 710 Container Deployment Unit 720 Recovery Unit 730 Service Unit 740 Pipeline Unit 750 Test Unit 800 Servers CMS Condition Monitoring System HF High Frequency IPC Industrial PC MPS Machine Protection System

Claims

1. 1. A system for monitoring a product processing device (20, 30) in an industrial plant, comprising: a first layer (100) having a plurality of sensors (110-150) configured to detect parameters of the product processing equipment (20, 30) of the industrial plant; a second layer (200) configured to implement a process control system based on data from the first layer (100); a third layer (300) configured to implement an operational control system; at least one Internet of Things edge unit (230, 310) in the second and / or third layers (200, 300) configured to receive data from the first and / or second layers (100, 200) and to analyze the received data; an Internet of Things hub (700) configured to remotely control, manage, and / or monitor the at least one Internet of Things edge unit (230, 310); A system for monitoring a product processing apparatus (20, 30), comprising:

2. an interface (600) coupled to said first and / or second processing layers (100, 200); Further comprising: the interface (600) comprises at least one Internet of Things edge unit (230, 310) and is configured to analyze the data from the first and / or second layers (100, 200) and to add metadata to the data from the plurality of sensors (110-150); the interface (600) is configured to permit only one-way data communication to a data sink (530); 2. The system for monitoring a product processing apparatus of claim 1.

3. the interface (600) further comprises a data buffer (620), a key performance calculator (650) configured to determine at least one key performance indicator based on the data in the buffer (620), and an upload selector (630) configured to select data from the received data to be transferred to the data sink (530), 3. A system for monitoring a product processing apparatus as recited in claim 2.

4. the metadata (10) including time information and / or information about the sensor that detected the data; 4. A system for monitoring a product processing apparatus according to claim 1, 2 or 3.

5. The time information includes a time stamp or time shift information.

5. A system for monitoring a product processing apparatus as recited in claim 4.

6. the second layer (200) comprises a condition monitoring system (210) and / or a machine protection system (220); the interface (600) is configured to analyze the data from the condition monitoring system (210) and / or the machine protection system (220), add metadata to their output data, process the data to reduce the amount of data if necessary, and output the processed data to the data sink (530). A system for monitoring a product processing apparatus according to any one of claims 1 to 5.

7. the interface (600) is configured to perform a time shift on the data from the first layer (100) based on time shift information in the metadata to harmonize the data with data from other sensors. A monitoring system for monitoring a product processing apparatus according to any one of claims 4 to 6.

8. 1. An industrial plant comprising: At least one industrial plant device (20, 30); a control system having a first layer (100) having a plurality of sensors (110-150) configured to detect parameters of the industrial plant equipment (20, 30) and a second layer configured to implement a process control system based on data from the first layer (100); A system for monitoring a product processing device (20, 30) according to any one of claims 1 to 7, An industrial plant comprising:

9. A method for monitoring product processing equipment (20, 30) in an industrial plant by a monitoring system having a first layer (100) with a number of sensors (110-150) for detecting parameters of the equipment (20, 30), a second layer (200) implementing a process control system based on data from the first layer (100), and a third layer implementing an operational control system, comprising: receiving data from the first and / or second layers (100, 200) and analyzing the received data in at least one Internet of Things edge unit (230, 310) in the second and / or third layers (200, 300); remotely controlling, managing, and / or monitoring said at least one Internet of Things edge unit (230, 310) at an Internet of Things hub (700); A method comprising the steps of:

10. A computer program for monitoring a product processing apparatus, the computer program comprising code means for causing a monitoring system according to any one of claims 1 to 8 to carry out the method according to claim 9, when the program is run on a monitoring system.

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