Chemical Production

Abstract

The present teachings relate to a method for monitoring and/or controlling a production process for manufacturing at least one industrial product at an industrial plant comprising at least one equipment by processing at least one input, the method comprising: receiving, via an input inter-face, real-time process data from the equipment; determining, via the computing unit, a subset of the real-time process data; providing as output data the subset of the real-time process data. The present teachings also relate to a system, a use, and a software product.

Claims

1. A method for monitoring and/or controlling a production process for manufacturing a chemical product at an industrial plant, the industrial plant comprising at least one equipment, and the product being manufactured by processing, via the equipment, at least one input material using the production process, the method at least partially being performed via a computing unit, wherein the method comprising: receiving, via an input interface, real-time process data from the equipment; determining, via the computing unit, a subset of the real-time process data; the subset of the real-time process data being indicative of the process parameters and/or equipment operating conditions that the input material is processed under, providing as output data, via an output interface, the subset of the real-time process data.

2. The method of claim 1, wherein the method further comprises: computing, via the computing unit, at least one performance parameter of the chemical product related to the input material, the computing being performed based on the subset of the real-time process data and historical process data.

3. The method of claim 2, wherein the output data include the at least one performance parameter.

4. The method of claim 1, wherein the method further comprises: providing, via an interface, an object identifier comprising input material data; wherein the input material data is indicative of one or more properties of the input material.

5. The method of claim 4, wherein the method further comprises: appending, to the object identifier, the subset of the real-time process data.

6. The method of claim 4, wherein the method further comprises: appending, to the object identifier, the at least one performance parameter.

7. The method of claim 1, wherein the input material for the processing via the equipment is divided into at least two packages wherein the size of a package is fixed or is determined based on an input material weight or amount, for which considerably constant process parameters or equipment operation parameters can be provided by the equipment.

8. The method of claim 1, wherein the processing of the at least two packages is managed by means of corresponding data objects, each of which at least including an object identifier.

9. The method of claim 1, wherein a data object is generated in response to a trigger signal being provided via the equipment.

10. The method of claim 9, wherein the trigger signal is provided in response to the output of a corresponding sensor being arranged at each of an equipment unit of the equipment.

11. The method of claim 1, wherein the equipment comprises a plurality of physically separated equipment zones, such that the output data comprise sub-sets of the real-time process data from each of the equipment zones and/or at least one performance parameter computed at each of the equipment zones.

12. The method of claim 1, wherein the output data form a time-dependent data stream.

13. The method of claim 1, wherein the output data and/or the time-dependent data stream are/is provided to a human machine interface (“HMI”) system.

14. The method of claim 13, wherein the HMI system is at least partially a display device.

15. The method of claim 13, wherein the HMI system is at least partially an augmented reality (“AR”) and/or virtual reality (“VR”) device.

16. The method of claim 13, wherein the HMI system is at least partially an audio device.

17. (canceled)

18. A system for monitoring and/or controlling a production process, the system being configured to perform the method of claim 1.

19. A computer program, or a non-transitory computer readable medium storing the program, comprising instructions which, when the program is executed by a suitable computing, cause the computing unit to carry out the method of claim 1.

Description

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0152] Certain aspects of the present teachings will now be discussed with reference to the following drawings that explain the said aspects by the way of examples. Since the generality of the present teachings is not dependent on it, the drawings may not be to scale. Certain features shown in the drawings can be logical features that are shown together with physical features for sake of understanding and without affecting the generality of the present teachings.

[0153] FIG. 1 illustrates certain aspects of a system according to the present teachings.

[0154] FIG. 2 illustrates a method aspect in accordance with the present teachings.

[0155] FIG. 3 shows a first embodiment of a system and corresponding method according to the present teachings, by way of a combined block/flow diagram.

[0156] FIG. 4 shows a second embodiment of a system and corresponding method according to the present teachings, by way of a combined block/flow diagram.

[0157] FIG. 5 shows a third embodiment of a system and corresponding method according to the present teachings, by way of a combined block/flow diagram.

[0158] FIG. 6 shows a first embodiment of a graph-based database arrangement representing the topological structure of an industrial plant, or cluster of plants, including a plurality of equipment devices and according plurality of equipment zones between which the input material progresses during the manufacturing or production process.

[0159] FIG. 7 shows a second embodiment of a graph-based database arrangement as shown in FIG. 6.

[0160] FIG. 8 shows another embodiment of a system and corresponding method according to the present teachings using a cloud computing platform, by way of a combined block/flow diagram, where a machine learning (ML) process is implemented in the cloud.

DETAILED DESCRIPTION

[0161] FIG. 1 shows an example of a system 168 for monitoring and/or controlling a production process for manufacturing a chemical product 170 an industrial plant. At least some of the method aspects will also be understood from the following discussion. The industrial plant comprises at least one equipment or a plurality of equipment zones for manufacturing or producing the chemical product 170 using the production process. The chemical product 170 may in any form, for example, a pharmaceutical product, a foam, a nutritional product, an agricultural product, or a precursor. For example, the chemical product 170 may be a thermoplastic polyurethane in granular form. The chemical product 170 may even be in batches, for example a package of 10 kg each. Due to the nature of such chemical products, they may be hard to trace in the production chain. However, it may be important to ensure that each component, e.g., each unit or package, or even parts inside have consistent and desired properties or quality. At least some aspects of the present teachings can enable that.

[0162] The equipment is shown in FIG. 1 as comprising equipment zones, for example, as a hopper or mixing pot 104, which may be a part of an upstream equipment zone. The mixing pot 104 receives input material, which may be a single material, or it may comprise multiple components, for example, methylene diphenyl diisocyanate (“MDI”) and/or polytetrahydrofuran (“PTHF”). Here, the input material is received in two parts, which are shown supplied to the mixing pot 104 via a first valve 112a and a second valve 112b respectively. The first valve 112a and a second valve 112b may also belong to the upstream equipment zone.

[0163] Optionally, an object identifier, or in this case, an upstream object identifier 122 is provided for the input material 114. The upstream object identifier 122 may be a unique identifier, preferably a globally unique identifier (“GUI D”), distinguishable from other object identifiers. The GUI D may be provided dependent upon the specifics of the particular industrial plant and/or the specifics of the chemical product 170 being manufactured and/or specifics of the date and time, and/or specifics of the particular input material being used. The upstream object identifier 122 is shown provided at a memory storage 128. The memory storage 128 is operatively coupled to a computing unit 124. The memory storage 128 may even be a part of the computing unit 124. The memory storage 128 and/or the computing unit 124 may at least partially be a part of a cloud service. Optionally, the memory storage 128 may even be a data store, or the memory storage 128 may provide output data to the data store.

[0164] The computing unit 124 is operatively coupled to the upstream equipment zone or the equipment belonging to the upstream equipment zone, for example, via a network 138, which may be any suitable kind of data transmission medium. The computing unit 124 may even be a part of the equipment in the plant, for example it may be at least partially be a part of the upstream equipment zone. The computing unit 124 may even be at least partially a plant control system, such as a DCS and/or PLC. The computing unit 124 may receive one or more signals from one or more sensors operatively coupled to the equipment of the upstream equipment zone. For example, the computing unit 124 may receive one or more signals from a fill sensor 144 and/or one or more sensors related to the transport elements 102a-b. Said sensors are also a part of the upstream equipment zone. The computing unit 124 may even at least partially to control the upstream equipment zone, or some parts thereof. For example, the computing unit 124 may control the valves 112a,b, e.g., via their respective actuators, and/or a heater 118 and/or the transport elements 102a-b. The transport elements 102a,b and others in the example of FIG. 1 are shown as a conveyor system that may comprise one or more motors and a belt driven via said motors such that it moves such that the input material 114 via the belt is transported in the direction of transverse 120 of the belt.

[0165] Without affecting the scope or generality of the present teachings, other kinds of transport elements can also be usable instead or in combination with a conveyor system. In some cases, any kind of equipment that involves a flow of material, e.g., one or more materials in and one or more materials out, may be termed a transport element. Thus, besides a conveyor system, belt, conduit, or rail, equipment such as extruder, pelletizer, heat exchanger, buffer silo, silo with mixer, mixer, mixing vessel, cutting mill, double cone blender, curing tube, column, separator, extraction, thin film vaporizer, filter, sieve may also be termed transport elements. Thus, it will be appreciated that presence of a transport system as a conveyor system may be optional, at least because in some cases material may move directly from one equipment to another via mass flow, or as normal flow via one equipment to another. For example, a material may move directly from a heat exchanger to a separator or even further such as to a column and so forth. Thus, in some cases, one or more transport elements or system may be inherent to an equipment.

[0166] The object identifier shown here as the upstream object identifier 122 may be provided in response to a trigger signal or event, which may be a signal or an event related to a quantity of the input material. For example, the fill sensor 144 may be used to detect at least one quantity value such as fill degree and/or weight of the input material. When the quantity reaches a predetermined threshold, the computing unit 124 may automatically provide the first upstream object identifier 122 at the memory storage 128. The upstream object identifier 122 comprises data related to the input material, or input material data. The input material data is indicative of one or more property of the input material.

[0167] In some cases, the computing unit 124 may receive, via an input interface, process data from all equipment or equipment zones in the industrial plant. The computing unit 124 may determine a subset of the real-time process data, e.g., based on a zone presence signal and/or the upstream object identifier. The subset of the real-time process data may be provided as output data via an output interface. The output data may be provided to a data store. In some cases, the data store may at least partially be the same system as the memory storage 128. Or, the data store may be provided the output data via the memory storage 128.

[0168] The trigger signal or event may also be used for generating the zone presence signal for the upstream equipment zone. The zone presence signal can hence be used for determining not only the process parameters and/or equipment operating conditions that are relevant for the processing of the input material 114 at the upstream equipment zone, but also the time aspect of said process parameters and/or equipment operating conditions which are included in the realtime process data.

[0169] Optionally, the computing unit 124 may compute at least one performance parameter that is relevant for the chemical product 170, which is related to the upstream object identifier 122. The computation is based on the subset of real-time process data 126, which in this case is shown optionally appended at the upstream object identifier 122. The computation is also based on historical data which may comprise data from one or more historical upstream object identifiers. Each historical upstream object identifier is related to the respective input material which was processed, e.g., in the upstream equipment zone in the past. At least one historical upstream object identifier may have been appended with at least a part of the process data which is indicative of the process parameters and/or equipment operating conditions that the previously processed input material was processed under, e.g., in the upstream equipment zone. The at least one performance parameter may be appended to the upstream object identifier 122 and/or the at least one performance parameter is included in the output data.

[0170] The at least one zone-specific performance parameter is shown appended to the upstream object identifier 122, for example as metadata. Thus, the upstream object identifier 122 is enriched with the performance parameter that is related to the quality of the chemical product 170. Quality control process can thus be simplified and improved while improving traceability, e.g., by coupling the quality related data with the resulting chemical product 170.

[0171] The subset of real-time process data 126 from the upstream equipment zone may be data within the time window that the input material 114 was at the upstream equipment zone, or the time window may be even shorter thus just for the time that the input material 114 was processed via the mixing pot 104. The real-time process data can be used to determine the time window. Hence, the upstream object identifier 122 can be enriched with high relevance data by using the time-dimension of the real-time process data. Thus, object identifiers not only can be used to track the material in the production process, but also encapsulate high quality data that can make edge computing and/or cloud computing more effective. The object identifier data can be highly suitable for faster training and retraining of machine learning models. Data integration can also be simplified as the data encapsulated in the object identifiers can be more compact than traditional datasets. Accordingly, the output data can also become high relevance data suitable for streaming and ingestion, e.g., for data analytics, for example at one or more applications or devices. The output data may for example be provided to an HMI system. The HMI system may comprise at least one display device and/or at least one audio device and/or at least one MR device.

[0172] The subset of real-time process data 126 is indicative of the process parameters and/or equipment operating conditions, i.e., the operating conditions of the mixing pot 104 and valves 112ab, that the input material is processed under in the upstream equipment zone, for example, any one or more of, incoming mass flow, outgoing mass flow, filling degree, temperature, moisture, time stamps or time of entry, time of exit, etc. The equipment operating conditions in this case may be control signals and/or set-points of the valves 112a,b and/or the mixing pot 104. The subset of real-time process data 126 may be or it may comprise time-series data, which means that it may include time dependent signals, which may be obtained via one or more sensors, for example, output of the fill sensor 144. The time-series data may comprise signals that are continuous or any of them may be intermittent with regular or irregular time intervals. The subset of real-time process data 126 may even include one or more time-stamps, for example time of entry and/or time of exit, from the mixing pot 104. Thus, a particular input material 114 may be associated with the subset of real-time process data 126 relevant for that input material 114 via the upstream object identifier 122. The upstream object identifier 122 may be appended to other object identifiers downstream of the production process such that specific process data and/or equipment operating conditions can be correlated to a specific chemical product. Other important benefits were already discussed in other parts of this disclosure, e.g., in the summary section.

[0173] The conveyor system comprising the transport elements 102a,b and the associated belt may be considered an intermediate equipment zone which is downstream of the upstream equipment zone. The intermediate equipment zone in this example comprises a heater 118 that is used for applying heat to the input material traversing on the belt. The conveyor system may even comprise one or more sensors, for example any one or more of, speed sensor, weight sensor, temperature sensor, or any other kind of sensor for measuring or detecting the process parameters and/or properties of the input material 114 at the intermediate equipment zone. Any or all outputs of the sensors may be provided to the computing unit 124.

[0174] As the input material 114 progresses along the direction of transverse 120, it is applied heat via the heater 118. The heater 118 may be operatively coupled to the computing unit 124, i.e., the computing unit 124 may receive signals or real-time process data from the heater 118. Furthermore, the heater 118 may even be controllable via the computing unit 124, for example via one or more control signals and/or set-points. Similarly, the conveyor system comprising the transport elements 102a,b and the associated belt may also be operatively coupled to the computing unit 124, i.e., the computing unit 124 may receive signals or process data from the transport elements 102a,b. The coupling may for example be via the network. Furthermore, the transport elements 102a,b may even be controllable via the computing unit 124, for example via one or more control signals and/or set-points provided via the computing unit 124. For example, the speed of the transport elements 102a,b may be observable and/or controllable by the computing unit 124. Optionally, as the quantity of the input material 114 is constant or near constant in the intermediate equipment zone, a further object identifier may not be provided for the intermediate equipment zone. Thus, the process data from the intermediate equipment zone, i.e., from the heater 118 and/or the transport elements 102a,b may also be appended to the object identifier of the previous or preceding zone, i.e., the upstream object identifier 122. It will be appreciated that, the subset of real-time process data now refers to the real-time data from the intermediate equipment zone as the input material is being processed there, thus the output data dynamically tracks the input material along the production process. The output data thus forms a time-dependent stream of process data that are relevant for transforming the respective input material to their respective chemical product. Similarly, the performance parameters may also be changed dynamically. Advantages of such output data and stream were also discussed in detail in the summary section.

[0175] Furthermore, the appended subset of real-time process data 126 may thus be enriched to be further indicative of the process parameters and/or equipment operating conditions from the intermediate equipment zone, i.e., the operating conditions of the heater 118 and/or transport elements 102a,b, that the input material 114 is processed under in the intermediate equipment zone, for example, any one or more of, incoming mass flow, outgoing mass flow, one or more temperature values from the intermediate zone, time of entry, time of exit, speed of the transport elements 102a,b and/or belt, etc. The equipment operating conditions in this case may be control signals and/or set-points of the transport elements 102a,b and/or the heater 118. It will be clear that the subset of real-time process data 126 predominantly relates to the time-periods within which the input material 114 is present in the respective equipment zone. Thus, an accurate snapshot of the relevant process data for the specific input material 114 can be provided via the upstream object identifier 122. Further observability of the input material 114 may be extracted via the knowledge of the specific portion or part of the production process, e.g., a chemical reaction, within the intermediate equipment zone. Alternatively, or in addition, the speed by with the input material 114 traverses through the intermediate equipment zone can be used to extract further observability via the computing unit 124. In conjunction with the subset of realtime process data 126 with specific time-stamps, or the time-series data, and/or time of entry and/or time of exit of the input material 114 in the intermediate equipment zone, a more granular detail of conditions under which the input material 114 is processed in the intermediate equipment zone may be obtained from the upstream object identifier 122.

[0176] The data from the upstream object identifier 122 may be used for training one or more ML models for monitoring the production process and/or the specific portions thereof, for example, the portion of the production process within the upstream equipment zone and/or the intermediate equipment zone. The ML model and/or upstream object identifier 122 may even be used for correlating one or more performance parameters of the chemical product to the specifics of the production process in one or more zones.

[0177] It will be appreciated that as the input material 114 progresses along the direction of transverse 120, it may change its properties and may transform or convert to a derivative material 116. For example, as the heater 118 heats the input material 114, it may result in the derivative material 116. Those skilled in the art will appreciate that for simplicity and ease of understanding, the derivative material 116 may also be sometimes referred to as input material in the present teachings. For example, in context of the equipment zone or components under discussion, it will thus be clear in which phase the input material is within the production process as discussed in the description of this example.

[0178] Now discussing an example of a zone where a material is divided in multiple parts. FIG. 1 shows such a zone as a downstream equipment zone comprising a cutting mill 142 and second transport elements 106a,b. The derivative material 116 traversing along the direction of transverse 154 is divided or fragmented using the cutting mill 142, thus resulting in a plurality of parts, shown in this example as a first divided material 140a and a second divided material 140b.

[0179] Thus, according to an aspect of the present teachings, an individual object identifier may be provided for each part. In some cases though, an object identifier may only be provided for one of the parts, or for some of the parts, instead of providing an individual object identifier for each part. This may be the case, for example if tracking any of the parts is not of interest. For example, an object identifier may not be provided for a part of the derivative material 116 that is discarded. Now referring back to FIG. 1, a first downstream object identifier 130a is provided for the first divided material 140a and a second downstream object identifier 130b is provided for the second divided material 140b. Such split in the material may also trigger separate output data, e.g., individual streams for each object identifier. Thus, in this example, two streams may be provided, which may be selectable or subscribeable, e.g., via the unique object identifier.

[0180] Optionally, the first downstream object identifier 130a may be appended with a first subset of downstream real-time process data 132a and the second downstream object identifier 130b may be appended with a second subset of downstream real-time process data 132b. The first subset of downstream real-time process data 132a may be a copy of the second subset of downstream real-time process data 132b, or they may partly be the same data. For example, in cases when the first divided material 140a and the second divided material 140b undergo the same process, i.e., at essentially the same place and time, then the process data appended to the downstream object identifier 130a and the second downstream object identifier 130b may be the same or similar. If, however, within the downstream equipment zone the downstream object identifier 130a and the second downstream object identifier 130b were to be treated differently, the first subset of downstream real-time process data 132a and the second subset of downstream real-time process data 132b may be different from each other.

[0181] Those skilled in the art will appreciate that in some cases, however, optionally only one object identifier may be provided at the cutting mill 142 and then multiple object identifiers may be provided subsequent to the cutting mill 142 if the material processed via the cutting mill 142 is split in multiple parts. Thus, dependent upon the specifics of a particular production process, a cutting mill may or may not be a separation device. Similarly, in some cases no new object identifier may be provided for a cutting mill such that process data from the zone is appended to the preceding object identifier. New object identifier may thus be provided at the zones where the material is split and/or it is combined. For example, in some cases, the downstream object identifier 130a and the second downstream object identifier 130b may be provided after the cutting mill 142, for example at entry at the different zones subsequent to the cutting mill 142.

[0182] In this example, the downstream equipment zone also comprises an imaging sensor 146, which may be a camera or any other kind of optical sensor. The imaging sensor 146 may also be operatively coupled to the computing unit 124. The imaging sensor 146 may be used for measuring or detecting one or more properties of the derivative material 116 prior to entering the downstream equipment zone. This may for example be done to sort or divert the material that meets a given quality criteria, for example at least one of the performance parameters determined at the upstream equipment zone and/or the intermediate equipment zone. As mass flow of the material is altered in the downstream equipment zone, according to an aspect of the present teachings, another object identifier (not shown in FIG. 1) may have been provided prior to the downstream object identifier 130a and the second downstream object identifier 130b.

[0183] The providing of the downstream object identifier 130a and the second downstream object identifier 130b may be triggered in response to the derivative material 116 passing the quality criteria via the imaging sensor 146. By correlating data from the adjacent zones or from the object identifiers, for example, mass flow from the intermediate equipment zone and mass flow to the downstream equipment zone, the computing unit 124 may determine which specific input material 114 or derivative material 116 is related to the material entering the subsequent zone. Alternatively, or in addition, two or more of the time stamps may be correlated between the zones, for example time-stamp of exit from the intermediate equipment zone and time-stamp of detection via the imaging sensor 146 and/or entry at the downstream equipment zone. The speed of the transport elements 102a,b either measured directly via a sensor output or determined from two or more time-stamps can also be used to establish relationship between a specific packet or batch of input material and its object identifiers. It may thus even be determined where the specific chemical product 170 was within the production process at a given time, thus a time-space relationship may be established. Some or all of these aspects can be usable not only in improving the traceability of the chemical product 170 from input material to finished product, but also in monitoring and improving the production process and making it more adaptable and controllable.

[0184] As discussed, the first downstream object identifier 130a and the second downstream object identifier 130b may be appended with the first subset of downstream real-time process data 132a and the second subset of downstream real-time process data 132b respectively from the downstream equipment zone. The first subset of downstream real-time process data 132a and the second subset of downstream real-time process data 132b may even be linked to or appended with the upstream object identifier 122. Similar to the previously discussed upstream object identifier 122, the first subset of downstream real-time process data 132a and the second subset of downstream real-time process data 132b are indicative of the process parameters and/or equipment operating conditions, i.e., the output of the imaging sensor 146, the operating conditions of the cutting mill 142 and the second transport elements 106a,b, that the derivative material 116 is processed under in the downstream equipment zone, for example, any one or more of, incoming mass flow, outgoing mass flow, filling degree, temperature, optical properties, time stamps, etc. The equipment operating conditions in this case may be control signals and/or set-points of the cutting mill 142 and/or the second transport elements 106a,b. The first subset of downstream real-time process data 132a and the second subset of downstream real-time process data 132b may comprise time-series data, which means that it may include time dependent signals, which may be obtained via one or more sensors, for example, output of the imaging sensor 146 and/or speed of the second transport elements 106a,b.

[0185] As the derivative material 116 proceeds after encountering the imaging sensor 146, it is moved towards the cutting mill 142 in the direction of transverse 154 driven by the second transport elements 106a,b. The second transport elements 106a,b are in this example shown as a part of a second conveyor belt system separate from the conveyor system comprising transport elements 102a,b. It will be appreciated that it the second conveyor belt system may even be a part of the same conveyor system comprising transport elements 102a,b. Accordingly, the downstream equipment zone may comprise some of the same equipment used in another zone.

[0186] As can be seen in FIG. 1, even though the first divided material 140a and the second divided material 140b go different ways later in production, their respective object identifier i.e., downstream object identifier 130a and the second downstream object identifier 130b allow following or tracking them individually through the remaining production process and in some cases also beyond. Similarly, output data also track the respective material.

[0187] As seen, the second divided material 140b is transported for curing at a third equipment zone comprising a curing apparatus 162 and third transport elements 108a,b. The transport elements 108a,b shown are accordingly a non-limiting example, as discussed previously. It will be appreciated that the third equipment zone is downstream of the upstream equipment zone and the downstream equipment zone.

[0188] As the second divided material 140b is moved via a belt in the direction of transverse 156, it undergoes the curing process via the curing apparatus 162 to result on a cured second divided material 160. Since no substantial mass change may occur, according to an aspect, no new object identifier may be provided for the third equipment zone. However, the output data corresponding to the second divided material 140b changes dynamically according to the production process at the third equipment zone, e.g., streams data from the curing apparatus 162 from the processing that is being performed. Accordingly, as previously discussed, the process data from the third equipment zone may also be appended to the second downstream object identifier 130b. Similar to the above, the appended second subset of downstream real-time process data 132b may thus be enriched to be further indicative of the process parameters and/or equipment operating conditions from the third equipment zone, i.e., the operating conditions of the curing apparatus 162 and/or transport elements 108a,b, that the second divided material 140b is processed under in the third equipment zone, for example, any one or more of, incoming mass flow, outgoing mass flow, one or more temperature values from the third zone, time of entry, time of exit, speed of the transport elements 108a,b and/or belt, etc. The equipment operating conditions in this case may be control signals and/or set-points of the transport elements 102a,b and/or the curing apparatus 162.

[0189] Similarly, the first divided material 140a progresses to a fourth equipment zone comprising the extruder 150, a temperature sensor 148 and fourth transport elements 110a,b. Here too, as no substantial mass change may occur, according to an aspect, no new object identifier may be provided for the fourth equipment zone. Accordingly, as previously discussed, the process data from the fourth equipment zone may be included in the output data, and optionally also be appended to the downstream object identifier 130a. Similar to the above, the appended first subset of downstream real-time process data 132a may thus be enriched to be further indicative of the process parameters and/or equipment operating conditions from the fourth equipment zone, i.e., the operating conditions of the extruder 150 and/or the temperature sensor 148 and/or transport elements 108a,b, that the first divided material 140a is processed under in the third equipment zone, for example, any one or more of, incoming mass flow, outgoing mass flow, one or more temperature values from the third zone, time of entry, time of exit, speed of the transport elements 110a,b and/or belt, etc. The equipment operating conditions in this case may be control signals and/or set-points of the transport elements 108a,b and/or the extruder 150. Thus, properties and dependencies of transformation of the first divided material 140a to an extruded material 152 may also be included in the downstream object identifier 130a. It will be appreciated that the fourth equipment zone is also downstream of the upstream equipment zone and the downstream equipment zone.

[0190] As can be appreciated, the number of individual object identifiers can be reduced while improving material and product monitoring throughout the production process.

[0191] As the extruded material 152 moves further in the direction of traverse 158 generated via the transport elements 108a,b, it may be collected in a collection zone 166. The collection zone 166 may be a storage unit, or it may be a further processing unit for applying further steps of the production process. In the collection zone 166, additional materials may be combined, for example, the cured second divided material 160 may be combined with the extruded material 152. Accordingly, a new object identifier may be provided as previously discussed. Such an object identifier is shown as a last downstream object identifier 134. The last downstream object identifier 134 may be appended with a subset of last zone real-time process data 136, which may include whole or a part of the downstream object identifier 130a and the second downstream object identifier 130b. The last downstream object identifier 134 is thus provided with the process parameters and/or equipment operating conditions from the collection zone 166, similar to as was discussed in detail in this disclosure. Depending upon the function or further processing if any done in the collection zone 166, data such as, any one or more of, incoming mass flow, outgoing mass flow, one or more temperature values from the collection zone 166, time of entry, time of exit, speed, etc. may be included as last zone real-time process data 136. The corresponding output data are adapted as previously discussed.

[0192] In some cases, individual lots from the collection zone 166 may be sorted and packaged and/or stored. Such an sorted lot is shown as product collection bin 164a. As quantities are being split again, an individual object identifier may be provided for each of the silos such that the chemical product 170 in its silo, i.e., the individual object identifier for the product collection bin 164a can be associated with the process data or conditions that the chemical product 170 is exposed to there. Also, the performance parameters associated with such plurality of products may be appended to the individual object identifier for the product collection bin 164a.

[0193] As will be appreciated, each of the object identifiers may be a GUID. Each may include wholly or partly data from the preceding object identifier, or they may be linked. The relevant quality data can thus be attached as a snapshot or traceable link to a particular chemical product 170.

[0194] As was also discussed, one or more ML models may be used for computing or predicting one or more performance parameters. It is also possible that each or some of the ML models also are configured to provide a confidence value indicative of the confidence level for the at least one zone-specific performance parameter. A warning may be generated as a warning signal, for example to initiate a physical test of a sample for lab analysis should the confidence level in predicting the performance parameter be low than a predetermined limit. It is also possible that in response to the confidence level of the prediction falling below an accuracy threshold value, a sampling object identifier is automatically provided via the interface. The sampling object identifier may be provided in a similar way and the computing unit 124 may append the subset of relevant process data to the sampling object identifier for the material which the sampling object identifier relates to, shown here as a sample material 172. The computing unit 124 may also append the at least one zone-specific performance parameter, which had low confidence level, to the sampling object identifier. The sample material 172 can thus be collected and verified and/or analyzed to further improve the quality control using object identifiers. It will also be appreciated that the sampling bin 164b may be a target zone for the sample material 172. Thus, reliability of sampling and sample collection is thus also improved.

[0195] FIG. 2 illustrates a flow chart 200 or routine showing method aspects of the present teachings, in this example, as viewed from the first equipment zone.

[0196] In block 202, it is received, via an input interface, real-time process data from the equipment or from one or more of the equipment zones, e.g., the upstream equipment zone. The real-time process data comprise process parameters and/or equipment operating conditions. In block 204, it is determined, a subset of the real-time process data. The subset of the real-time process data is indicative of the process parameters and/or equipment operating conditions that the input material 114 is processed under. In block 206, it is provided as output data, via an output interface, the subset of the real-time process data.

[0197] The determination of the subset may be done using a zone presence signal, which indicates presence of the input material 114 at a specific equipment zone during the production process.

[0198] Optionally, in block 208, it is computed, at least one performance parameter of the chemical product related to the input material 114, or the upstream object identifier, based on the subset of the real-time process data and historical process data. The historical process data may comprise data from one or more historical object identifiers related to previously processed input material, preferably in the same equipment, e.g., the upstream equipment zone. Preferably, each historical object identifier is appended with at least a part of the process data which is indicative of the process parameters and/or equipment operating conditions that the previously processed input material was processed under, e.g., in the same equipment zone.

[0199] Optionally, in block 210, it is included, in the output data the at least one performance parameter.

[0200] The output data according to the present teachings can be a dynamic stream of data tracking the respective material during production. The output data can be especially suitable for integration, streaming, cloud computing, edge computing, and for real-time monitoring and/or controlling and/or optimization or improving of the production process at any suitable industrial plant.

[0201] As the input material progresses to a subsequent zone, it may be determined if another object identifier is to be provided or not. If not, then the process data from the subsequent zone may also be appended to the same object identifier. If it is determined that another object identifier is to be provided, then the process data from the subsequent zone is appended to the another object identifier. Details for each of these options, such as the intermediate equipment zone and the downstream equipment zone are discussed in detail in the present disclosure, for example, in the summary section as well as with reference to FIG. 1. Moreover, examples of target zones were discussed.

[0202] The block diagram shown in FIG. 3 represents parts of a product production system of an industrial plant, which, in the present embodiment, comprises ten product processing devices or units 300-318, or technical equipment respectively, being arranged along the shown entire product processing line. In the present embodiment one of these processing units (processing unit 308) includes three corresponding equipment zones 320, 322, 324 (see also more detailed embodiments in FIGS. 3 and 5).

[0203] In the present example a chemical product, as input material, is produced based on a raw material which is provided to the processing line via a liquid raw material reservoir 300, a solid raw material reservoir 302, and a recycling silo 304 which recycles any chemical products or intermediate products that e.g. comprise insufficient material/product properties or an insufficient material/product quality. The respective raw material being input to the processing line 306-318 is processed via the respective processing equipment, namely a dosing unit 306, a subsequent heating unit 308, a subsequent treatment unit including a material buffer 310, and a subsequent sorting unit 312. Downstream of this processing equipment 306-312, there is arranged a transport unit 314 which transports material that needs to be recycled, e.g. due to insufficient quality of the produced material, from the sorting unit to the recycling silo 304. Finally, the material being sorted by the sorting unit 312 is transferred to a first and a second packing unit 316, 318 which pack the according materials into material containers for shipping purposes, e.g. material bags in case of bulk material or bottles in case of liquid material.

[0204] The production system 300-318, in the present embodiment, provides a data interface of a computing unit (both not being depicted in this block diagram), via which data objects comprising data about the respective input materials and their changes due to the processing are provided. The entire production process is, at least partially, controlled via the computing unit.

[0205] The input material(s) being processed by the processing equipment 306-312 is(are) divided into physical or real-world so-called “package objects” (in the following also called “physical packages” or “product packages”), wherein these package objects are handled or processed by each of the processing units 306-312. The package size of such package objects can be fixed, e.g. by material weight (e.g. 10 kg, 50 kg, etc.) or by material amount (e.g. 1 decimeter, 1/10 cubic meter, etc.), or even can be determined by a weight or amount, for which considerably constant process parameters or equipment operation parameters can be provided by the processing equipment.

[0206] The dosing unit 306 first creates such package objects from the input liquid and/or solid raw material and/or the recycled material provided by the recycling silo 304. Having created the package objects, the dosing unit transports these objects to the homogenization unit 308. The homogenization unit 308 homogenizes the materials of the package objects, i.e. homogenizes e.g. a processed liquid material and a solid material, or two liquid or solid materials. After the heating process, the heating unit 308 transports the accordingly heated package objects to the treatment unit 310 which transforms the material of the input package objects into a different physical and/or chemical state, e.g. by heating, drying or humidifying or by a certain chemical reaction. The accordingly transformed package objects are then transported to one or more of the three downstream packing units 316, 318 or the mentioned transport unit 314.

[0207] The subsequent processing of the real-world package objects is managed by means of corresponding data objects 330, 332, 334 (or pre-described “object identifiers”, respectively) which are assigned to each package object via the computing unit operatively coupled to the equipment 306-312, or being a part of the equipment, and is stored at a memory storage element of the computing unit. According to the present embodiment, the three data object 330-334 are generated in response to a trigger signal which is provided via the equipment 306-312, namely in response to the output of a corresponding sensor being arranged at each of the equipment units 306-312, or according switches respectively, wherein such sensors are operatively coupled to the equipment units 306-312. As mentioned beforehand, the industrial plant may include different types of sensors, e.g. sensors for measuring one or more process parameters and/or for measuring equipment operating conditions or parameters related to the equipment or the process units. In the present embodiment, sensors for measuring the flowrate and the level of the bulk and/or liquid materials processed inside the equipment units 306-312 are arranged at these units.

[0208] The three exemplary data objects 330, 332, 334 depicted in FIG. 3, in the present embodiment, each relate to different the three equipment zones 320, 322, 324 of the entire product production process based on the processing units 306-312 and 314-318.

[0209] The first two data objects 330, 332 comprise product package objects which contain process data. The process data comprises processing/treatment information which the related physical package has experienced during its residence/treatment within the several processing units. The process data can be aggregated data such as a calculated average temperature during the residence time of the underlying physical package within the related processing units and/or it can be time series data of the underlying production processes.

[0210] The first data object 330 is a first kind of package (in FIG. 3 called “A-Package”) which, in the present embodiment, is assigned to a physical package that has been transported through the two processing units, the Dosing unit 306 and the Heating unit 308. The first data object 330 includes, at the present point in processing time, the related data of both units during each residence. The first data object includes a corresponding “Product Package ID”.

[0211] The Heating unit 308 contains several equipment zones, in the present embodiment, three equipment zones 320, 322, 324 (“Zone 1”, “Zone 2”, “Zone 3”). These different equipment zones are utilized as sorting group for sorting or selecting the related process data. Such a sorting may help to obtain only those data for a package object out of a related equipment zone, which relate to the processing of the underlying physical package within the corresponding point in time during which the related physical package is inside this equipment zone. However, in the present embodiment, the material composition of the physical package is not changed by both processing units 306, 308.

[0212] Once the A-package 330 has arrived at the next Treatment unit 310 (in the present embodiment a “treatment unit with buffer”), the material composition of each physical package changes, because this processing unit 310 not only transports physical packages in a plug flow mode. Moreover, corresponding physical packages comprise a buffer volume which is bigger than the original package size, so that such physical packages have a defined backmixing degree. As a consequence, each physical package which leaves this Treatment unit 310, is another kind of physical package, which is called “B-package” in FIG. 3.

[0213] The corresponding second data object 332 (“B-package”) also includes a corresponding “Product Package ID”. The data object 332 further includes the data of a defined number of previous data objects, in the present example the data object 330 designated as “A-Package”, in a defined percentage, the so-called “Aggregated data from related A-packages”. An according aggregation scheme or algorithm depends e.g. on the underlying processing unit, on the size of the underlying physical package, on the mixing capabilities of the material of the underlying physical package and on the residence time of the underlying physical package within the underlying processing unit, or a corresponding equipment zone of the processing unit.

[0214] Once processed physical (product) packages are packed by one of the two Packing units 316, 318 into discrete physical packages, e.g. by packing processed physical packages into a container, a drum or into an octabin vessel or the like, in the present embodiment, corresponding packed physical packages are handled or tracked via another data object 334 called “Physical package”. This data object 334 includes related previous physical packages (like the “A-Package” and the “B-Package” in the present scenario) which have been packed into it. The designation of corresponding “Product Package IDs” is sufficient e.g. for tracking purposes, instead of using complete data objects, because such Product Package IDs can be easily linked together during a later data processing, e.g. data processing performed by means of an external “cloud computing” platform.

[0215] The first data object (or “object identifier”) 330 particularly includes the following information: [0216] A “Product Package ID” for an underlying package; [0217] general information about the underlying package, like information, or a specification, about the underlying processed material(s) of the package; [0218] the current location of the underlying package within the entire processing line 306-318; [0219] process data, i.e. as aggregated values of temperature and/or weight of the processed material(s) of the underlying package; [0220] time series data of the underlying production process; and [0221] connections to samples out of the underlying package, wherein a product package passes a sample station and, at a defined moment, an operator takes a sample out of this product package and provides it to a lab. For this sample, a sample object (see FIG. 6, reference signs 634 and 638) will be generated and will be linked to the related product package (see FIG. 6, reference signs 626 and 630). This sample object, in particular, contains corresponding product quality control (QC) data from the lab and/or performance data from according testing machines.

[0222] The second object identifier 332 additionally includes [0223] aggregated data from related A-packages which is generated in the treatment unit with buffer 310.

[0224] The third object identifier 334 is generated by the two packing units 316, 318 with the designation and time stamp “Physical package 1976-02-06 19:12:21.123” and includes the following information: [0225] Again, an according package or object identifier (“Package ID”); [0226] the name of the product being packed into the two material containers for shipping purposes depicted in FIG. 3; [0227] the order number for ordering the product being packed accordingly; and [0228] the Lot number of the product being packed accordingly.

[0229] The package general information of the first and second object identifier 330, 332 includes material data of the input raw material, which in the present embodiment, is indicative of a chemical and/or physical property of the input material, or processed material(s) respectively, like the material(s) temperature and/or weight, and in the present embodiment comprises also above mentioned lab sample or test data related to the input material, such as historical test results.

[0230] According to the product production process also illustrated by FIG. 3, via the mentioned interface, process data from the overall equipment are gathered which are indicative of process parameters like the mentioned temperature and/or weight of the processed material(s), and in the present embodiment also of equipment operating conditions that the input material is processed under, like the temperature of a mentioned heater and/or the applied dosing parameters. The gathered process data, in the present embodiment only part of the process data like the aggregated data from related A-packages, in the present embodiment, are appended to the second object identifier 332.

[0231] As described beforehand, the three object identifiers 330-334, in the present embodiment, are used for correlating or mapping the mentioned input material data and/or specific process parameters and/or equipment operating conditions to at least one performance parameter of the chemical product, said performance parameter being, or it being indicative of, any one or more properties of the underlying material(s), e.g. an according chemical product, respectively.

[0232] According to the present embodiment shown in FIG. 3, the gathered process data (as aggregated values) included in the two object identifiers 330, 332 comprise numerical values indicative of the process parameters, and additionally of the equipment operating conditions measured during the production process. In addition, the object identifiers 330, 332 include process data being provided as time-series data of one or more of the process parameters and/or the equipment operating conditions. The equipment operating conditions can be any characteristics or values that represent the state of the equipment, in the present embodiment, production machine setpoints, controller outputs, and any equipment related warning, e.g. based on vibration measurements. Additionally, the transport element speed, temperature and fouling value such as filter differential pressure, a maintenance date can be included.

[0233] In the embodiment of the product production system shown in FIG. 3, the entire product processing equipment 306-318 comprises the mentioned plurality of three equipment zones 320-324 such that during the production process, the input raw material(s) 300-304 traverses along the entire processing line 306-318 and, in the present embodiment, progresses from the first equipment zone 320 to the second equipment zone 322 and from the second equipment zone 322 to the third equipment zone 324. In such a production scenario, the first object identifier 330 is provided at the first equipment zone 320, wherein the second object identifier 332 is provided at the entry of the input material at the second equipment zone 322, after having been processed through the first equipment zone 320. The second object identifier 332 is appended with or includes at least part of the data or information provided by the first object identifier 330 and additionally includes the last data/information “Aggregated data from related A-packages”.

[0234] It is noteworthy that any or each of the object identifiers 330-334 may include a unique identifier, preferably a globally unique identifier (“GUID”), in order to allow for a reliable and safe assignment of an object identifier to a corresponding package during the whole production process.

[0235] In the present product processing scenario, the mentioned process data appended to the first object identifier 330 are at least part of the process data gathered from the first equipment zone 320. Accordingly, the second object identifier 332 is appended with at least part of the process data gathered from the second equipment zone 322, wherein the process data gathered from the second equipment zone 322 are indicative of the process parameters and/or equipment operating conditions that the input raw material(s) 300-304 is processed under in the second equipment zone 322.

[0236] In the following TABLE 1, another exemplary object identifier is shown, again in a tabular format. This object identifier includes much more information/data than the previously described three object identifiers 330-334.

[0237] This exemplary object identifier concerns a so-called “B-Package” with an underlying date and time stamp “1976-02-06 18:31:53.401”, like that shown in FIG. 4 being described in the following but including more data than that included in FIG. 4.

[0238] The unique identifier (“Unique ID”), in the present example, comprises a unique URL (“uniqueObjectURL”). The main details of the underlying package (“Package Details”), in the present example, are the date and timestamp of the creation of the package (“Creation Timestamp”) having the two values “02.02.1976 18:31:53.401” and the type of the package (“Package Type”), in the present example having a package type “B”. The current location of the package along the underlying production line (“Package Location”) is defined by a “Package Location Link”, in the present example a transport link to a “Conveyor Belt 1” of the production line.

[0239] At the Conveyor Belt 1, there is provided measuring equipment (see “Measuring Points” which include exemplary processing data or values) for measuring the average temperature (“Average Value”) currently revealing a material temperature of 85° C. and an according description (“Description”) of the underlying temperature zone, in the present example “Temperature Zone 1”. In addition, the measuring equipment can also include sensors for detecting the entry date/time of the package at the Conveyor Belt 1 (“Entry Time”), in the present example being “02.02.1976 18:31:54.431” and for detecting the leaving date/time of the package from the Conveyor Belt 1 (“Leaving Time”), in the present example being “02.02.1976 18:31:57.234”. Finally, the measuring equipment includes sensor equipment for detecting time series values (“Time Series Values”) of underlying time series information (“Time Series”) concerning the production process.

[0240] In addition, the shown object identifier, in the present example, further includes information about a downstream located “Conveyor Belt 2”, a downstream located “Mixer 1” and a downstream located “Silo 1” for intermediately storing already processed material(s).

TABLE-US-00001 TABLE 1 Exemplary tabular object identifier B-Package 1976 Feb. 6 18:31:53.401 Unique ID Unique URL uniqueObjectUrl Package Details Creation Timestamp Feb. 2, 1976 18:31:53.401 Package Type B Package Location Package Location Link Conveyor Belt 1 Conveyor Belt 1 Measuring Point Average Value 85° C. Description Temperature Zone 1 Entry Time Feb. 2, 1976 18:31:54.431 Leaving Time Feb. 2, 1976 18:31:57.234 Time Series Time Series Values Conveyor Belt 2 Mixer 1 Silo 1

[0241] FIG. 4 shows a second embodiment of ‘process parts of an underlying product production system of an industrial plant, which, in the present second embodiment, comprises six product processing devices 400, 402, 406, 410, 412, 416, or technical equipment, respectively.

[0242] An “Upstream process” 400 for processing package objects is connected to a “Sorting Unit” 402 for sorting the processed package objects. The upstream process 400 and the sorting unit 402 are managed by means of a first data object 404. This data object 404 concerns an already described “B-Package” with an underlying date and time stamp “1976-02-06 18:51:43.431” depicting the date and time of its creation. The data object 404 includes a “Package ID” of a currently processed package object (so-called “object identifier”). The data object 404 further includes n pre-described chemical and/or physical properties about the currently processed package object, in the present example a “Property 1” and a “Property n”.

[0243] The input materials, i.e. the corresponding package objects being fed in to the upstream process 400, in the present example, are provided by a “Recycling Silo” 406. The recycling silo 406, on the other hand, gets the underlying recycled materials from a “Transport unit 1” 410 which transports package objects, that have to be recycled and are sorted out by the sorting unit 402 accordingly, to the recycling silo 406. The underlying transport process step 410 is managed by means of a second data object 408 which concerns the above described “B-Package” and includes the mentioned underlying date and time stamp “1976-02-06 18:51:43.431”, the “Package ID” of the currently processed package object and the two chemical and/or physical properties “Property 1” and a “Property n”. However, due to the mentioned requirement to recycle the underlying sorted-out package object, the second data object 408 further includes another chemical and/or physical property of the underlying package object, in the present example a “Property 2”, which particularly includes a respective performance indicator for that package object, in the present example a “low or insufficient material or product performance”.

[0244] Package objects being processed by the upstream process 400 and not being sorted out by the sorting unit 402 are provided by the sorting unit 402 to either a first “Packing Unit 1” 412 or a second “Packing Unit 2” 416, depending on performance values for the corresponding package objects. The packing units 412, 416 are used for packing the corresponding package objects to respective containers 414, 418. The packing process being executed by the two packing units 412, 416 is managed by means of a third data object 420 and a fourth data object 422.

[0245] The two data objects 420, 422 both concern “Physical Packages” and include the same date “1976-02-06” as the above described “B-Package”, but a later time stamp “19:12:21.123” than the above described “B-Package”. They also include the “Package ID” of the underlying package objects. However, the data objects 420, 422 further include performance indicators for the underlying final products, in the present example a “performance medium range” regarding the products stored in the first container (or filling sack) 414 and a “performance high range” in case of the products stored in the second container (or filling sack) 418. In addition, the two data objects 420, 422 include the “Order no.” and “Lot no.” of the corresponding final products.

[0246] FIG. 5 shows a third embodiment of parts of an underlying chemical product production process or system implemented at an industrial plant, which, in the present second embodiment, comprises nine product processing devices 500-516, or technical equipment respectively.

[0247] The present product processing approach is based on two raw materials, namely a “Raw Material Liquid” 500 and a “Raw Material Solid” 502, in order to produce a polymeric material in a known manner. Like in the previously described production scenarios according to FIGS. 3 and 4, the technical equipment includes a “Recycling silo” 504 for using recycled materials, as described beforehand.

[0248] The technical equipment further includes a “Dosing unit 506” for creating package objects based on the mentioned input raw materials which are processed by a “Reaction unit” 508 which transports package objects along the shown four polymeric reaction zones (“Zones 1-4”) 510, 512, 514, 516 in order to process them and by a “Curing unit” 518 for curing the polymeric material (i.e. the corresponding package objects) being produced in the reaction unit 508. The curing unit 518, in the present embodiment, comprises only a material buffer, but not a back-mixing equipment. The curing unit 518 also transports accordingly processed package objects.

[0249] A “Transport unit 1” 520 transports package objects being sorted out for their recycling by means of the recycling silo 504. The finally processed, i.e. not sorted out, units are transported again to a first “Packing Unit 1” 522 and to a second “Packing Unit 2” 524. The two packing units 522, 524 transform and transport the corresponding package objects to respective containers or filling sacks 526, 528.

[0250] The production process depicted in FIG. 5 is managed by means of a first data object 530 and a second data object 534.

[0251] The first data object 530 concerns an “A-Package” with creation date “1976-02-06” and creation time “18:31:53.401”. The data object 530, in the present production scenario, includes again a pre-described “Package ID”, process information about the dosing process (“Dosing properties”) being performed by the dosing unit 506, and further process information (“Reaction unit properties”) about the production of the polymeric material by means of the reaction unit 508. The dosing properties include information about the raw material amounts for each package object, namely the “Percentage raw material 1 (liquid)”, the “Percentage raw material 2 (solid)” and the product temperature. The Reaction unit properties include the temperatures of the four polymeric reaction zones 510-516 (“temperature zone 1”, “temperature zone 2”, “temperature zone 3” and “temperature zone 4”).

[0252] Thereupon, the first data object 530 includes the current location of an underlying package object (“Current Package Location”) along the processing line 506-524. The current location of that package object, in the present embodiment, is managed by means of a “Package Location Link” and a corresponding “Zone location”. Finally included is chemical and/or physical information about the underlying polymeric reaction, namely the corresponding “Reaction enthalpy/turnover degree”. Hereby, the processing units 506-524 which transport a given package object, calculate and write/actualize permanently reaction enthalpy values into the first data object 530. This is possible due to existing information about package positions and corresponding residence times and about according process values, e.g. package temperatures. Based on the current values of the reaction enthalpy and/or turnover degree included in the first data object 530, via a communication line 532 between the first data object 530 and the curing unit 518, the curing time parameters are adjusted, based on a calculated value of the reaction enthalpy.

[0253] The second data object 534 concerns a “Physical package” being processed by one of the packing units 522, 524 and includes the corresponding creation date/time information “1976-02-06 19:12:21.123”. Included are a “Package ID”, a “Product” description/specification, an “Order no.”, a “Lot no.” and the mentioned value of the calculated enthalpy and/or turnover degree.

[0254] FIG. 6 shows a first embodiment of a graph-based database arrangement representing the hierarchical or topological structure of an underlying industrial plant 602, which is part of a cluster 600 of industrial plants, and which includes a plurality of equipment devices and corresponding equipment zones being part of an according product processing line 604.

[0255] This topological structure allows to visualize the functional relationship between the underlying different parts of the industrial plant 602 (or underlying plant cluster 600) in order to enable an improved processing or planning of underlying product packages. The shown circular nodes of the graph-based database are linked via connection lines, for which different link types are possible.

[0256] The equipment devices, in this embodiment, include material processing units 606, 614 which are connected via a signal and/or data connection with sensors/actors 608, 616 being part of the processing units 606, 614 and which are connected to several input/output (I/O) devices 610, 612 and 618, 620.

[0257] In the present embodiment, the first processing unit 606 is further connected with exemplary three product packages (Product Packages 1-3) 622, 624, 626, wherein the second processing unit 614 is further connected with further three product packages (Product Packages 4-n) 628, 630, 632. Only exemplary, “Product Package 3” 626 is connected to a product sample (Sample 1) 634, wherein “Product Package 5” 630 is connected to another product sample (Sample n) 638. “Sample 1” 634 is further connected with an “Inspection lot 1” 636, wherein “Sample n” is further connected with an “Inspection lot n” 640. Finally, both inspection lots 636, 640 are connected with an “Inspecting Instruction 1” unit 642 which serves as a specification on how to create a mentioned inspection lot and on how to realize the analysis/quality control of a respective underlying sample 634, 638.

[0258] The topological structure shown in FIG. 6, advantageously provides data structures which allow for an intuitive and easy understanding of the functionality and processing of a shown chemical plant and thus an easy manageability of such a complex production process in the chemical plant or cluster of chemical plants by a user, in particular a machine/plant operator, since the shown objects (nodes) are modelled very similar like the corresponding real-world objects.

[0259] More particularly, this topological structure provides a high degree of contextual information, based on which the user/operator can easily gather the technical and/or material property of each object. This additionally allows for rather complex queries by the user, e.g. about relevant production-related connections or relations between objects, particularly across several nodes or even topology/hierarchy levels. Thereupon, the objects (nodes) shown in FIG. 6 can be extended easily during runtime by further properties and/or values.

[0260] FIG. 7 shows a second embodiment of a graph-based database arrangement as shown in FIG. 6, but only for a production line 700 (“Line 1”).

[0261] The equipment devices, in the present embodiment, include material processing units 702 “Unit 1” and “Unit n” 708 which are connected via a signal and/or data connection with sensors/actors “Sensor/Actor 1” 704 and “Sensor/Actor n” 710 which are connected to corresponding input/output (I/O) devices “I/O 1” 706 and “I/O n” 712. These I/O devices comprise a connection to a (not shown) PLC for controlling the operation of the production line 700.

[0262] In the present embodiment, the first processing unit (“Unit 1”) 702 is further connected with exemplary three product packages (“Product Portions” 1-3) 714, 716, 718, wherein the second processing unit (“Unit n”) 708 is further connected with further two product packages (“Product Portions” 4 and n) 720, 722. Only exemplarily, product package 3″ 718 is connected to a product sample (“Sample 1”) 724, wherein product package n 722 is connected to another product sample (“Sample n”) 728.

[0263] In contrast to the embodiment shown in FIG. 6, the first “Sensor/Actor 1” 704 is also connected to the first product sample (“Sample 1”) 724, wherein the second “Sensor/Actor n” 710 is also connected to the second product sample (Sample n”) 728. These two additional connections have the advantage that it is possible to independently take samples at different sample stations at independent times, or even at the same time. For instance, the sensor/actor 704 can be a push button being arranged at a sample station, which is pressed by a user or operator at the moment when a sample is taken.

[0264] Alternatively, such a sample can be a signal that can be generated automatically by a sampling machine. Such an automatically generated signal can e.g. reach the sensor/actor object 704 via the shown I/O object 706, wherein the I/O object 706 receives the mentioned push button information from the (not shown) PLC/DCS. At the moment of taking the sample, the sample object 724 (e.g.) will be created and linked to the product portion located at the sampling station location in that moment.

[0265] Based on the accordingly generated samples 724, 728, one or more inspection lots 726, 730 can be generated, even for only one (and the same) sample. However, one or more samples can be generated within one processing line independently, or even at same time.

[0266] Finally, like in the embodiment shown in FIG. 6, “Sample 1” 724 is further connected with a first “Inspection unit 1” 726, wherein “Sample n” is further connected with a second “Inspection unit n” 730. Both inspection units 726, 730 are finally connected with an “Inspecting Instruction 1” unit 732 which again serves as a specification, like in the case of the “Inspecting Instruction 1” unit 642 depicted in FIG. 6, namely on how to create a mentioned inspection lot and on how to realize the analysis/quality control of an underlying sample 724, 728.

[0267] The “Inspecting instruction 1” unit 732 can be created independently, and may be created only once, while using the inspecting instruction 732 for more than only one inspection lot, as illustrated in FIG. 7 by the “Inspection lot 1” 726 and further “Inspection lot n” 730.

[0268] FIG. 8 depicts an abstraction layer 800 which includes an object database 801 and which serves as an abstraction layer for a pre-described production equipment and corresponding raw materials, and for the pre-described product data, maybe including pre-described physical package or product package related data, namely as according digital twins.

[0269] The abstraction layer 800, in the present embodiment, provides a bi-directional communication line 802 with an external Cloud computing platform 804. Further, the abstraction layer 800 communicates also with a number of n production PLC/DCS and/or machine PLCs 806, 808, either bidirectionally 810, as in the case of “PLC/DCS 1” 806, or unidirectionally 812, as in the case of “PLC/DCS n” 808. The Cloud computing platform 804, in the present embodiment, comprises a bidirectional communication line 814 to a Customer integration interface or platform 816, via which customers of the present production plant owner can communicate and/or deliver control signals to pre-described equipment units of the plant.

[0270] In the object database 801 further included are other objects concerned herewith, e.g. above described samples, inspection lots, sample instructions, sensors/actors, devices, device-related documentation, users (e.g. machine or plant operators), according user groups and user rights, recipes, orders, setpoint-parameter sets, or inbox objects from cloud/edge devices.

[0271] At the Cloud computing platform 804, an Artificial Intelligence (AI) or machine learning (ML) system is implemented, by which to find or create an optimum algorithm which is deployed via a dedicated deployment pipeline 818 to an Internet-of-Things (IoT) Edge device or component 820, in order to use an accordingly created or found algorithm for controlling the Edge device 820. The Edge device 820, in the present embodiment, communicates 822 bidirectionally with the abstraction layer 800.

[0272] By means of the abstraction layer 800 and the included object database 801, pre-described physical or product packages are created, as described within this document. The abstraction layer 800 can also connect to certain processing and/or AI (or ML) components within the Cloud computing platform 804. For this connection, the known data streaming protocol “Kafka” can be used. Hereby, at or around the time of creation of an underlying product package, first an empty data packet can be sent out as a message, in particular independent of the underlying timeseries data. After that, another message can be sent out when the final product package has been processed. These messages contain the object identifier of the underlying package as data packet ID, so that the relating packets can be linked again with each other on side of the Cloud platform later. This has the advantage that large-size data packets can be avoided for the transmission to the Cloud, thus minimizing the required transmission bandwidth or capacity.

[0273] Within the Cloud computing platform 804, the streamed and received product data is used by mentioned AI methods or ML methods in order to find or create algorithms for getting additional data related to an underlying product, such as predicted product quality control (QC) values. For this procedure being performed within the Cloud computing platform 804, additional data like QC data or measured performance parameters of a related product (or physical) package is needed. This can either be received via the same way from the object database 801 in the form of sample objects and inspection lot objects (see also FIG. 6) which contain such information about related product packages.

[0274] Such information can also be received from any other systems than the object database. In this case the other system sends the QC and/or performance data together with a sample/inspection lot ID out of the object database. Within Cloud computing platform 804, this data will be combined and used for finding e.g. ML-based algorithms/models. Hereby the computing power within the Cloud platform 804 can be used effectively.

[0275] In the present embodiment, the accordingly found algorithms or models are deployed to the Edge device 820 via the deployment pipeline 818. The Edge device 820 can be a component which is located close to the object database 801 of the abstraction layer 800, and thus also close to the PLC/DCS 1 to PLC/DCS n 806, 808 accordingly, namely in terms of a network security level and and location which allows for a low network latency and direct and se-cure communication.

[0276] Since, for usage of the ML-model, not such a computing power is needed, the Edge device 820 uses the ML model to generate the mentioned advanced information and provides it to the object database 801. Therefore, the Edge device 820 needs the same information or a subset of the information which is used at the Cloud computing platform 804 to generate the ML-based algorithm or model, the object database 801 can provide this data to the Edge device 820, e.g. via an open network protocol for machine-to-machine communication, like the known “Message Queuing Telemetry Transport” (MQTT) protocol.

[0277] This setup enables the realization of an AI/ML-based advanced process control and autonomous manufacturing and according autonomously operating machines.

[0278] As illustrated in the embodiment shown in FIG. 8, based on data from a pre-described data object 330-334 (FIG. 3), on side of the Cloud computing platform 804 the AI/ML system or according AI/ML model is trained using such data as training data. The training data, in the present embodiment, thus may comprise historical and current laboratory test data, in particular data from the past, being indicative of the performance parameters of the chemical product.

[0279] The AI/ML model can be used for predicting one or more of pre-described performance parameters, said prediction being preferably done via the computing unit. Additionally, or alternatively, the AI/ML model can be used for least partially controlling the production process, preferably via adjusting the equipment operating conditions, and more preferably said controlling being done via the mentioned computing unit. Additionally, or alternatively, the AI/ML model can also be used, e.g., by the computing unit, for determining which of the process parameters and/or equipment operating conditions have a dominant effect on the chemical product, such that those dominant of the process parameters and/or equipment operating conditions are appended to the data object, or the mentioned object identifier, respectively.

[0280] Those skilled in the art will appreciate that the method steps, at least those which are performed via the computing unit may be performed in a “real-time” or near real-time manner. The terms are understood in the technical field of computers. As a specific example, a time delay between any two steps performed by the computing unit is no more than 15 s, specifically of no more than 10 s, more specifically of no more than 5 s. Preferably, the delay is less than a second, more preferably, less than a couple of milliseconds. Accordingly, the computing unit may be configured to perform the method steps in a real-time manner. Moreover, the software product may cause the computing unit to perform the method steps in a real-time manner.

[0281] The method steps may be performed, for example, in the order as shown listed in the examples or aspects. It shall be noted, however, that, under specific circumstances, a different order may also be possible. Further, it is also possible to perform one or more of the method steps once or repeatedly. The steps may be repeated at regular or irregular time periods. Further, it is possible to perform two or more of the method steps simultaneously or in a timely overlapping fashion, specifically when some or more of the method steps are performed repeatedly. The method may comprise further steps which are not listed.

[0282] The word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single processing means, processor or controller or other similar unit may fulfil 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. Any reference signs in the claims should not be construed as limiting the scope.

[0283] Further, it shall be noted that in the present disclosure, the terms “at least one”, “one or more” or similar expressions indicating that a feature or element may be present once or more than once typically may have been used only once when introducing the respective feature or element. Thus, in some cases unless specifically stated otherwise, when referring to the respective feature or element, the expressions “at least one” or “one or more” may not have been repeated, non-withstanding the fact that the respective feature or element may be present once or more than once.

[0284] Further, the terms “preferably”, “more preferably”, “particularly”, “more particularly”, “specifically”, “more specifically” or similar terms are used in conjunction with optional features, without restricting alternative possibilities. Thus, features introduced by these terms are optional features and are not intended to restrict the scope of the claims in any way. The present teachings may, as the skilled person will recognize, be performed by using alternative features. Similarly, features introduced by “according to an aspect” or similar expressions are intended to be optional features, without any restriction regarding alternatives of the present teachings, without any restrictions regarding the scope of the present teachings and without any restriction regarding the possibility of combining the features introduced in such way with other optional or non-optional features of the present teachings.

[0285] Any headings utilized within the description are for convenience only, accordingly such headlines do not have any limiting or restrictive effect on the subject matter.

[0286] Various examples have been disclosed above for a method for monitoring and/or controlling and/or improving a production process; a use; a system for carrying out the method herein disclosed; a system for monitoring and/or controlling and/or improving a production process; a software program; and a computing unit comprising the computer program code for carrying out the method herein disclosed. Those skilled in the art will understand however that changes and modifications may be made to those examples without departing from the spirit and scope of the accompanying claims and their equivalents. It will further be appreciated that aspects from the method and product embodiments discussed herein may be freely combined.