SYSTEM AND METHOD FOR RISK ASSESSMENT

Abstract

The present invention is directed to a system, comprising a first data-processing system and at least one second data-processing system, a processing component, and data-storage component. The system is configured to perform for each condition-state of at least a subset of the condition states: comparing each condition-state value and the respective condition-state threshold, thus generating a comparison result for each of these condition-states, and further assigning each comparison result to the respective condition-state. The system is further configured for generating a condition-node modifier for each condition-node of at least a subset of condition-nodes by aggregating the comparison results of the condition-states of at least the subset of the condition-states which condition-states are assigned to the respective condition-node. The invention is further directed to a corresponding computer-implemented method.

Claims

1. A system, comprising a first data-processing system and at least one second data-processing system, a processing component, and data-storage component, wherein the system is configured to perform for each condition-state of at least a subset of the condition states comparing each condition-state value and the respective condition-state threshold, thus generating a comparison result for each of these condition-states, and further assigning each comparison result to the respective condition-state, and wherein the system is further configured for generating a condition-node modifier for each condition-node of at least a subset of condition-nodes by aggregating the comparison results of the condition-states of at least the subset of the condition-states which condition-states are assigned to the respective condition-node.

2. The system according to claim 1, wherein the processing component comprises a condition-node processing component, and wherein the system is configured for generating a condition-node value for each condition-node of at least the subset of the condition-nodes.

3. The system according to claim 1, wherein the system is configured for outputting data, wherein the processing component comprises an output-determining component, and wherein the output-determining component is configured for determining at least one of condition-nodes and condition-states to be outputted that are each linked to at least one of a specified condition-node and a specified condition-state.

4. The system according to claim 3, wherein the processing component comprises a pre-calculating component, and wherein the pre-calculating component is configured for performing pre-calculations of for at least a portion of the data to be outputted and to thus generate pre-calculated data.

5. The system according to claim 3, wherein the output-determining component is configured to determine at least a portion of the condition-states and/or condition-nodes based on the pre-calculated data.

6. The system according to claim 1, wherein the data-storage component is configured for storing at least one or a plurality of subset(s) of the condition-nodes wherein further the at least one second data processing system is a plurality of second data processing systems and wherein the data-storage component is configured for storing at least an indicator of one subset of the condition-nodes and of one of the condition-states for each of the second data processing systems.

7. The system according to claim 6, wherein the system is further configured to store and process for each second data-processing system at least one of a set of condition-node values, a set of condition-state values, a set of comparison results, and a set of condition-state thresholds.

8. The system according to claim 3, wherein the system comprises at least one user interface and the system is configured for outputting at least a portion or all of the data to be outputted to at least one of the at least one user interface, and/or wherein the system is configured for outputting at least a portion or all of the data to be outputted by transmitting them to a third data-processing system.

9. A computer-implemented method, comprising using at least one of a first data-processing system and a second data-processing system to perform the method, storing a plurality of the condition-nodes and at least one condition-state, wherein each condition-state is assigned to at least one condition-node, and wherein each condition-state comprises a condition-state threshold and a condition-state value storing at least one node-link(s), wherein each node-link connects two condition-nodes and each node-link is directed, a condition-state determining step, comprising for each condition-state of at least a subset of the condition-states comparing the respective condition-state value and the respective condition-state threshold and thus generating a respective comparison result, and assigning the comparison result to the respective condition-state a condition-state processing step, comprising for each condition-node of the subset of the condition nodes aggregating the comparison results of the condition-states of the subset of the condition-states relating to the respective condition-node and thus generating a condition-node modifier for the respective condition-node.

10. The method according to claim 9, wherein the step of generating the condition-node value for each condition-node of at least the subset of the condition-nodes comprises combining the condition-node modifier of the respective condition-node, and the condition-node value of each condition-node of the subset of the condition-nodes that is linked to the respective condition-node by a node-link that is directed towards the respective condition-node.

11. The method according to claim 9, wherein the method further comprises an outputting step that comprises outputting data, and wherein in the outputting step, the outputting data comprises outputting at least one of condition-nodes and condition-states to be outputted that are each linked to at least one of a specified condition-node and a specified condition-state according to a linking-criterion.

12. The method according to claim 11, wherein the method comprises a pre-calculating step that comprises determining at least one of the condition-nodes and the condition-states to be outputted for at least one or a plurality of linking-criteria and a plurality of the at least one of the specified condition-node and the specified condition-state and to thus generate pre-calculated data.

13. The method according to claim 12, wherein the pre-calculating step is performed by the first data-processing system and wherein the outputting data is based on the pre-calculated data.

14. The method according to claim 9, wherein the method comprises using the first data-processing system and a plurality of second data-processing systems, performing the condition-state determining step for each second data-processing system, wherein each subset of the condition-states corresponds to at least one or exactly one second data-processing system, and performing the condition-state processing step for each second data-processing system, wherein each subset of the condition-nodes corresponds to at least one second data-processing system, and wherein the method comprises furthermore storing separate sets of values for the condition-node values, the condition-node modifiers, the condition-state values and the comparison results for each second data-processing system.

15. The method according to claim 10, wherein in the outputting step, the outputting comprises outputting at least a part or all of the respective data to a user interface and said outputting to the user interface is performed by the second data-processing system, and/or the outputting comprises transmitting at least a part or all of the respective data to a third data-processing system and said transmitting to the third data-processing system is performed at least partially by the first data-processing system.

16. A computer program comprising instructions causing the system according to claim 1 to execute steps of the method comprising: using at least one of a first data-processing system and a second data-processing system to perform the method, storing a plurality of the condition-nodes and at least one condition-state, wherein each condition-state is assigned to at least one condition-node, and wherein each condition-state comprises a condition-state threshold and a condition-state value storing at least one node-link(s), wherein each node-link connects two condition-nodes and each node-link is directed, a condition-state determining step, comprising for each condition-state of at least a subset of the condition-states comparing the respective condition-state value and the respective condition-state threshold and thus generating a respective comparison result, and assigning the comparison result to the respective condition-state a condition-state processing step, comprising for each condition-node of the subset of the condition nodes aggregating the comparison results of the condition-states of the subset of the condition-states relating to the respective condition-node and thus generating a condition-node modifier for the respective condition-node.

Description

SHORT DESCRIPTION OF THE FIGURES

Figures

[0651] FIG. 1 shows a part of a general concept of a computer-implemented method

[0652] FIG. 2 shows method steps and used data-processing systems of the computer-implemented method

[0653] FIG. 3 shows an embodiment of the method for a plurality of second data-processing systems

[0654] FIG. 4 shows a detail of an embodiment of the method for a plurality of second data-processing systems

[0655] FIG. 5 shows precalculated data relating to condition-nodes from which specified condition-nodes can be reached for a subset of condition-nodes and condition-links

[0656] FIG. 6 shows precalculated data relating to condition-nodes from which specified condition-nodes can be reached for another subset of condition-nodes and condition-links

[0657] FIG. 7 shows precalculated data relating to condition-states and condition-nodes that impact a value of other condition-nodes

DETAILED DESCRIPTION OF THE FIGURES

[0658] FIG. 1 shows the general concept of the invention. A method comprises using a plurality of condition-nodes 20, in FIG. 1 indicated by capital letters A to I, wherein the number of condition-nodes 20 is merely exemplary. The condition-nodes (20) are connected by node-links 40. The node-links 40 can optionally each be associated with a node-link value 42. The node-links 40 are directed and each node-link 40 links one condition-node 20 to another condition-node 20.

[0659] As an example, FIG. 1 shows furthermore a plurality of condition-states 30 that are assigned to one of the condition-nodes 20. Each of the condition-states 30 can also be assigned to at least one or a plurality of other condition-nodes 20, and each or at least some of the condition-states 30 can be assigned to different condition-nodes 20. For the sake of clarity and readability, such further relations of shown condition-nodes 20 as well as further condition-states 30 are not shown. However, the method may comprise using such further relations of condition-states 30 to condition-nodes 20 as well as further condition-states 30.

[0660] Each condition-state can comprise a condition-state threshold 34 and a condition-state value 36.

[0661] In one example, the method can be used to monitor and manage a condition or a plurality of conditions or reliabilities of a ship, or risks relating to the ship. In such this example, a condition-node relates to at least an aspect of a technical system and/or a corresponding risk. For example, a propulsion-system of the ship may comprise at least one internal combustion engine, a transmission system, and a power-output, such as at least one propeller. The transmission system can for example be a combination of at least one electrical generator and at least one electrical motor, typically completed by corresponding power electronics. The transmission system can for example also be a mechanical transmission system as known to the person ordinarily skilled in the art. In this example, condition-node A represents the internal combustion engine of the ship. The shown condition-states 30 relate all at least to said internal combustion engine. A first condition-state 30 can relate to a quantity of fuel that is stored in the fuel tank. This condition-state's 30 condition-state threshold 34 can for example indicate a minimum quantity of fuel, and this condition-state's condition-state value can refer to the carried quantity of fuel. As this example illustrates, the ship (or the overall system, respectively) may be operational, even though condition-state value 36 is below the condition-state threshold 34. Nevertheless, a risk of fuel-shortage on the high seas may be increased. Analogously, a second condition-state 30 can relate to a lubrification system of the ship. The second condition-state 30 can also relate to another condition-node 20, such as the transmission system of the ship, which may also require the lubrification system to be in an operative state. A third condition-state 30 may relate to a controller, such as an ECU of the combustion engine, or to its software. Also one or more condition-nodes 20 may refer to software components, such as a software component operating a RADAR-system of the ship. That is, more generally speaking, condition-states 30 can relate to one or more condition-nodes 20.

[0662] The method comprises comparing the condition-state value 36 and the condition-state threshold 34 of condition-states 30. A result of this comparison is a comparison result 38 (not shown). The comparison result can be obtained by different measures. The comparison results 38 can for example be obtained by calculating a difference of each condition-state value 36 and the respective condition-state threshold 34 if the respective condition-state value 36 is lower than the respective condition-state threshold 34 and assigning said result to the respective comparison result 38, and assigning 0 to the respective comparison result 38 otherwise.

[0663] The method can furthermore comprise aggregating the comparison results 38 of each condition-state 30 which condition-state is assigned to a condition-node 20 and thus generating a condition-node modifier 22. In FIG. 1, the condition-states 30 assigned to condition-node 20 A are shown, that is, a condition-node modifier 22 of condition-node 20 A can be obtained from aggregating the shown condition-states' 30 comparison results 38.

[0664] Returning to the example of using the method for monitoring a ship's condition or risks relating to a ship, the abovementioned exemplary condition-node modifier 22 relates to the ship's internal combustion engine. If said condition-node modifier 22 and the corresponding comparison results 38 are calculated as discussed above, then they can for example be a measure for a risk of a failure or a stoppage of the internal combustion engine. If their calculation is adapted, such as by subtracting the condition-node modifier 22 from another value, such as 1, then the condition-node modifier 22 can represent a reliability of the internal combustion engine. Analogous considerations apply to other condition-nodes, condition-states 30 and related elements. Condition-node 20 D can in this example relate to a generation of electrical power on board, for example in case of a diesel-electric ship. Condition-nodes 20 A and D are linked by a node-link 40, as the generation of electrical power on board depends on the internal combustion engine. Condition-node 20 F and G are then aspects of the ship that depend on the generation of electrical power on board, such as an operation of the propulsion system (in the case of a diesel-electric ship, where the propulsion system comprises electric motors that power propellers or the like), and an availability of electrical systems on board. In general, the node-links 40 do not need to express absolute dependencies, but they can also only indicate a propagation of conditions or risks, such as in case of the exemplary availability of electrical systems on board. Even in case of an interruption of generation of electrical power on board by generators on board, at least a part of the electrical systems on board will still remain operational at least for some time, as they will most probably be linked to batteries, too.

[0665] The detailed example illustrates a use of the method as modern tool of engineering, namely for maintenance and naval operation. However, the method is not limited to this application, but can also be used to monitor other systems, for example a ship as discussed above, a cyber-physical system such as an IT-system, or even conditions and risks in an operation of another system, such as a bank or an insurance.

[0666] For example in case of a bank or an insurance, the condition-nodes could for example correspond to risks that contribute to an operations risk, and the condition-states could correspond to measures that are implemented or required in order to limit or control these risks. The method can hence be a computer-implemented method for risk-assessment of a bank, an insurance and/or any company of corporate finance.

[0667] In FIG. 1, some condition-nodes 30 F, G, H and I only have node-links 40 incoming from other condition-nodes 30, but no “outgoing” node-links 40.

[0668] Thus, the invention allows to efficiently manage, forecast and simulate impacts of adjustments or measures on conditions or states of a system. As the method uses a graph-representation, applicable states, conditions, measures and (inter-)dependencies can be flexibly changed.

[0669] FIG. 2 shows an embodiment of the method with a set of method steps, of which some are optional, and used data-processing systems, comprising a first data-processing system 10 and a second data-processing system 14, 15.

[0670] The first data-processing system 10 can for example be a server, a server system, a cloud system, or a hybrid system, wherein calculation operations can be distributed to several devices that may even be end-user computer devices, or a system emulating a server, such as a server system with an appropriate software for running a virtual machine.

[0671] The second data-processing system 14, 15 is a data-processing system that comprises at least one user interface. The second data-processing system 14, 15 optionally has a lower computing performance than the first data-processing system 10, or at least computing devices of the second data-processing system 14, 15 optionally have a lower computing performance than the first data-processing system 10. The second data-processing system can for example comprise at least one terminal computer or another end user computer device such as a smart phone.

[0672] The first data-processing system 10 may comprise one or more processing units configured to carry out computer instructions of a program (i.e. machine readable and executable instructions). The processing unit(s) of the first data-processing system 10 may be singular or plural. For example, the first data-processing system 10 may comprise at least one of CPU, GPU, DSP, APU, ASIC, ASIP or FPGA. The first data-processing system 10 may comprise memory components, such as, main memory (e.g. RAM), cache memory (e.g. SRAM) and/or secondary memory (e.g. HDD, SDD). The first data-processing system 10 may comprise volatile and/or non-volatile memory such an SDRAM, DRAM, SRAM, Flash Memory, MRAM, F-RAM, or P-RAM. The first data-processing system 10 may comprise internal communication interfaces (e.g. busses) configured to facilitate electronic data exchange between components of the data processing system, such as, the communication between the memory components and the processing components. The first data-processing system 10 may comprise external communication interfaces configured to facilitate electronic data exchange between the data processing system and devices or networks external to the data processing system. For example, the first data-processing system 10 may comprise network interface card(s) that may be configured to connect the data processing system to a network, such as, to the Internet. The first data-processing system 10 may be configured to transfer electronic data using a standardized communication protocol. The first data-processing system 10 may be a centralized or distributed computing system.

[0673] To put it simply, the first data-processing system 10 may be a processing unit configured to carry out instructions of a program. The first data-processing system 10 may be a system-on-chip comprising processing units, memory components and busses.

[0674] The second data-processing system 14, 15 may comprise one or more processing units configured to carry out computer instructions of a program (i.e. machine readable and executable instructions). The processing unit(s) of the second data-processing system 14, 15 may be singular or plural. For example, the second data-processing system 14, 15 may comprise at least one of CPU, GPU, DSP, APU, ASIC, ASIP or FPGA. The second data-processing system 14, 15 may comprise memory components, such as, main memory (e.g. RAM), cache memory (e.g. SRAM) and/or secondary memory (e.g. HDD, SDD). The second data-processing system 14, 15 may comprise volatile and/or non-volatile memory such an SDRAM, DRAM. SRAM, Flash Memory, MRAM, F-RAM, or P-RAM. The second data-processing system 14, 15 may comprise internal communication interfaces (e.g. busses) configured to facilitate electronic data exchange between components of the second data-processing system 14, 15, such as, the communication between the memory components and the processing components. The second data-processing system 14, 15 may comprise external communication interfaces configured to facilitate electronic data exchange between the data processing system and devices or networks external to the data processing system. For example, the second data-processing system 14, 15 may comprise network interface card(s) that may be configured to connect the data processing system to a network, such as, to the Internet. The second data-processing system 14, 15 may be configured to transfer electronic data using a standardized communication protocol. The data processing system may be a centralized or distributed computing system.

[0675] The second data-processing system 14, 15 may comprise user interfaces, such as: [0676] output user interface, such as: [0677] screens or monitors configured to display visual data, [0678] speakers configured to communicate audio data, [0679] input user interface, such as: [0680] camera configured to capture visual data, [0681] microphone configured to capture audio data, [0682] keyboard configured to allow the insertion of text and/or other keyboard commands and/or [0683] trackpad, mouse, touchscreen, joystick.

[0684] To put it simply, the second data-processing system 14, 15 may be a processing unit configured to carry out instructions of a program. The second data-processing system 14, 15 may be a system-on-chip comprising processing units, memory components and busses. The data processing system may be a personal computer, a laptop, a pocket computer, a smartphone, a tablet computer. The second data-processing system 14, 15 may be a processing unit or a system-on-chip that may be interfaced with a personal computer, a laptop, a pocket computer, a smartphone, a tablet computer and/or user interfaces (such as the upper-mentioned user interfaces).

[0685] In the shown embodiment of the method, at least some steps of the method are executed by the first data-processing system 10. Said steps of the method can be in particular steps whose execution requires many operations, that is, whose execution can be considered to consume much calculation time and/or performance. An optional advantage can be that the first data-processing system 10 can provide a considerably higher computing performance than the second data-processing system 14, 15.

[0686] An attribution of steps to data-processing systems 10, 14, 15 as shown in FIG. 2 is to be understood as exemplary. At least one or some steps can optionally also be at least partially performed by the second data-processing system 14, 15, even though shown differently in FIG. 2.

[0687] The method comprises storing a plurality of condition-nodes 20, at least one condition-state 30 and at least one node-link 40 together with the other variables such as condition-state thresholds 34, condition-state values 36 and condition-node values 24. These data can be optionally stored on the first data-processing system 10.

[0688] The method can comprise at least one or a plurality of optional steps of selecting data. The method can optionally comprise a condition-state selecting step (CSS). The condition-state selecting step (CSS) can comprise selecting a subset of condition-states 52, 53 that is applicable. The subset of condition-states 52, 53 can comprise all condition-states 30. The condition-state selecting step (CSS) can comprise storing said subset 52, 53, wherein this step of storing said subset of condition-states 52, 53 can optionally be performed on the first data-processing system 10.

[0689] If, in the subsequently described method steps in the context of FIG. 2, reference is made to “all” condition-states 30 or to “each” condition-state 30, then the condition-states 30 that the subset of condition-states 52, 53 comprises, are meant.

[0690] The method can optionally further comprise a condition-node selecting step (CNS). The condition-node selecting step (CNS) can comprise selecting a subset of condition-nodes 50, 51 that is applicable. The subset of condition-nodes 50, 51 can comprise all condition-nodes 20. The condition-node selecting step (CNS) can comprise storing said subset 50, 51, wherein this step of storing said subset of condition-nodes 50, 51 can optionally be performed by the first data-processing system 10.

[0691] If, in the subsequently described method steps in the context of FIG. 2, reference is made to “all” condition-nodes 20 or to “each” condition-state 20, then the condition-states 20 that the subset of condition-nodes 50, 51 comprises, are meant.

[0692] The method can optionally further comprise a node-link selecting step (NLS). The node-link selecting step (NLS) can comprise selecting a subset of node-links that is applicable. The subset of node-links can comprise all node-links 40. The node-link selecting step (NLS) can comprise storing said subset, wherein this step of storing said subset of node-links can optionally be performed on the first data-processing system 10.

[0693] If, in the subsequently described method steps in the context of FIG. 2, reference is made to “all” node-links 40 or to “each” node-link 40, then the node-links 40 that the subset of node-links comprises, are meant.

[0694] The abovementioned node-link selecting step (NLS), condition-node selecting step (CNS) and condition-state selecting step (CSS) can comprise receiving input data, such as user input data. A respective part or respective parts of these steps can be performed by the second data-processing system 14, 15. Optionally, also further parts of these steps can be performed by the second data-processing system 14, 15, such as pre-processing input data.

[0695] At least one, some or all of the three abovementioned selecting steps may be omitted in some cases, for example if the method is adapted for a standardized system.

[0696] The method can optionally further comprise a condition-state value receiving step (CSV). The condition-state value receiving step (CSV) can comprise receiving input data that indicate at least a part of the condition-state values 36. The condition-state value receiving step (CSV) can further comprise pre-processing the input data. The condition-state value receiving step (CSV) can optionally be performed at least partially by the first data-processing system 10. Receiving the input data that indicate at least the part of the condition-state values 36 can optionally at least partially be performed by the second data-processing system 14, 15. Receiving the input data that indicate at least the part of the condition-state values 36 can optionally comprise receiving sensed data, data that are generated by a sensing device and/or data derived from such data.

[0697] In some cases, at least one of the previously discussed four steps may comprise receiving data from another data-processing system. That can for example be the case if one of the selecting steps is at least partially automated and/or if one of the selecting steps relies at least partially on data that are already stored by another data-processing system.

[0698] The method can further comprise a condition-state determining step (CSD). The condition-state determining step (CSD) can comprise generating respective comparison results 38 for the condition-states 30 or for each condition-state 30 selected in the condition-state selecting step (CSS) as far as applicable, as discussed above. This step can optionally be performed by the first data-processing system 10. Its result(s) can be optionally stored by the first data-processing system 10.

[0699] The method can further comprise a condition-state processing step (CSP). The condition-state processing step (CSP) can comprise aggregating for each condition-node 20 all comparison results that are associated to condition-states 30 that relate to the respective condition-node as respective condition-node modifier (22). The condition-state processing step (CSP) can optionally be performed by the first data-processing system 10.

[0700] The method can further comprise a condition-node processing step (CNP). The condition-node processing step (CNP) can comprise generating a condition-node value 24 for each condition-node 20. Generating the condition-node value(s) 24 can comprise combining the respective condition-node modifier 22 generated in the condition-state processing step (CSP) and condition-node value(s) 24 of condition-nodes 20 that are linked to the respective condition-node 20 by a node-link 40 that is directed towards the respective condition-node 20. In a case where no condition-node 20 is linked to the respective condition-node 20 by a node-link 40 that is directed towards the respective condition-node 20, the step of combining can optionally be limited respectively to assigning the respective condition-node modifier 22 or a value generated thereof to the condition-node value 24 of the respective condition node 20. In FIG. 1, this would for example apply to the condition-nodes 20 A, B, and C. Furthermore, if the node-links 40 are each associated with a node-link value 42, then the step of combining may further comprise combining or weighting the condition-node values 24 with the respective node-link values 42 of the node-links 40 linking these condition-node values 24 to the respective condition-node 20.

[0701] The method can optionally further comprise an outputting step (OS). The outputting step can comprise outputting results of any of the abovementioned method steps. The outputting step (OS) can optionally comprise displaying data by the second data-processing system 14, 15. Outputting results can optionally be or comprise transferring data to another data-processing system.

[0702] The outputting step (OS) can comprise outputting at least one of the condition-node values 24 of the condition-nodes 20 of the subset of the condition-nodes 50, 51, the node-links 40 linking the condition-nodes 20 of the subset of the condition-nodes 50, 51, and the comparison results 38 of the conditions-states 30 of the subset of the condition-states 52, 53.

[0703] FIG. 3 shows an optional embodiment of the method with two second data-processing systems 14, 15.

[0704] Each of the second data-processing systems 14, 15 can be associated with an execution of the method. Therefore, the subsets of the condition-nodes 50, 51 can be specific to each second data-processing system 14, 15. The same applies for each subset of the condition-states 52, 53. In consequence, each subset of the condition-nodes 50, 51 can optionally be associated with a respective subset of the condition-states 52, 53. The same can be applicable for the subsets of the node-links (not shown in FIG. 3).

[0705] The abovementioned method steps can respectively be applicable for each set of subsets 50, 52; 51, 53.

[0706] The number of second data-processing systems 14, 15 is to be understood as an example. Instead of two second data-processing systems 14, 15 and respective subsets, the method can also comprise a plurality of second data-processing systems, with or without adapted subsets of condition-nodes, conditions-states and node-links.

[0707] However, for every second data-processing system, the condition-state values 36 are generated independently from each other. In consequence, the comparison results 38, the condition-node modifiers 22 and the condition-node values 24 are calculated for each second data-processing system 14, 15 depending on the respectively received input data.

[0708] The first data-processing system 10 can thus carry out the abovementioned method for a plurality of second data-processing systems 14, 15, that is, for a plurality of applications for which the condition-nodes 20 are determined. Hence, the first data-processing system 10 can be configured for this functionality, and the above-described method can be carried out several times.

[0709] FIG. 4 shows an example for two subsets of the condition-nodes 50, 51, wherein the node-links 40 are the same. However, there could also be diverging subsets of node-links. The same applies to the condition-states 30, which are not shown in FIG. 4.

[0710] An example for an application of the method as shown in FIG. 3 and FIG. 4 can be an application for a production plant with a plurality of production systems, such as a plant for a set of mechanical products that are obtained for example by machining and heat treatment, wherein each type of product is produced by a separated manufacturing line. In such an example, each subset of condition nodes 50, 51, the respective second data-processing system 14, 15, the respective subset of the condition-states 52, 53, the respective subset of the node-links 54, 55 and the respectively stored values can correspond to a manufacturing line or to a part of the production plant that produces one product.

[0711] The condition-nodes 20 can in this case correspond to a reliability of parts of the system or respective functions.

[0712] The condition-nodes 20 can also refer to a risk of failure, a risk that a function cannot be performed and/or to other risks.

[0713] FIGS. 5, 6 and 7 show an example of pre-calculated data that can be pre-calculated by the first data-processing system. Pre-calculating data can decrease response times during runtime of an application reacting to user requests.

[0714] An example for such condition-nodes 20 can be “Risk of improper use of machine X”, “Risk of failures of machine X”, “Risk of unplanned stop of production of machine X” and “Risk of unplanned stop of production of production-one Y (comprising machine X)”, wherein these condition-nodes 20 can be linked by node-links 40 in the order in which they are named in this example. That is, a condition-node 20 referring to the risk of improper use of the machine X can be connected to a condition-node 20 referring to the risk of failure of the machine X, as improper use of the machine X may increase its risk of failure.

[0715] In said example, each of the second data-processing systems 14, 15 refers to all devices for data input and data output, such as devices used by maintenance personnel, maintenance engineers and machine operators to enable entry of condition-state values 36 or indicators thereof. Each of the second data-processing systems 14, 15 can optionally also comprise at least one interface to at least one other data-processing system, such as an interface to a data-processing system that controls or monitors a part of the respective production line.

[0716] Referring to a device used by a maintenance engineer who is in charge of the whole production facility, this device may be a part of a plurality of second data-processing systems 14, 15, wherein data referring to a first subset of condition-nodes, node-links and node-links are considered to be a part of a first second data-processing system and data referring to a second subset of condition-nodes, node-links and node-links are considered to be a part of a second second data-processing system.

[0717] Whenever a relative term, such as “about”, “substantially” or “approximately” is used in this specification, such a term should also be construed to also include the exact term. That is, e.g., “substantially straight” should be construed to also include “(exactly) straight”.

[0718] Whenever steps were recited in the above or also in the appended claims, it should be noted that the order in which the steps are recited in this text may be accidental. That is, unless otherwise specified or unless clear to the skilled person, the order in which steps are recited may be accidental. That is, when the present document states, e.g., that a method comprises steps (A) and (B), this does not necessarily mean that step (A) precedes step (B), but it is also possible that step (A) is performed (at least partly) simultaneously with step (B) or that step (B) precedes step (A). Furthermore, when a step (X) is said to precede another step (Z), this does not imply that there is no step between steps (X) and (Z). That is, step (X) preceding step (Z) encompasses the situation that step (X) is performed directly before step (Z), but also the situation that (X) is performed before one or more steps (Y1), . . . followed by step (Z). Corresponding considerations apply when terms like “after” or “before” are used.

[0719] While in the above, a preferred embodiment has been described with reference to the accompanying drawings, the skilled person will understand that this embodiment was provided for illustrative purpose only and should by no means be construed to limit the scope of the present invention, which is defined by the claims.

NUMBERED REFERENCE SIGNS

[0720] 10 first data-processing system [0721] 14, 15 second data-processing system [0722] 20 condition-node [0723] 22 condition-node modifier [0724] 24 condition-node value [0725] 30 condition-state [0726] 34 condition-state threshold [0727] 36 condition-state value [0728] 38 comparison result [0729] 40 node-links [0730] 42 node-link value [0731] 50, 51 subset of the condition-nodes [0732] 52, 53 subset of the condition-states [0733] 54, 55 subset of the node-links [0734] 60 processing component [0735] 62 condition-state determining component [0736] 64 condition-state processing component [0737] 66 condition-node processing component [0738] 68 input-processing component [0739] 70 output-determining component [0740] 72 limiting element [0741] 74 pre-calculating component [0742] 80 data-storage component [0743] CSD condition-state determining step [0744] CSP condition-state processing step [0745] CNP condition-node processing step [0746] CSS condition-state selecting step [0747] CNS condition-node selecting step [0748] CSV condition-state value receiving step [0749] OS outputting step [0750] NLS node-link selecting step [0751] PCS pre-calculating step