A method and system for asset full life cycle management based on EAM

Abstract

The present invention belongs to the field of asset management technology. A method and system for full life cycle management of EAM assets is provided, the method comprising: in response to detecting that a target asset is in the installation or maintenance stage, obtaining continuous status data of the target asset from the EAM management system based on the type attribute of the target asset; predicting the first health status data and the first residual value data of the target asset based on the continuous status data, and importing the first health status data and the first residual value data into the management entry corresponding to the target asset in the EAM management system; generating a management strategy for the target asset based on the first health status data and the first residual value data, and outputting management prompt information to the management personnel based on the management strategy. The present invention realizes the management of tangible assets in the use stage and the non-use stage, realizes the real full life cycle management of assets, and is very beneficial to the efficient management of assets by enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of asset management, and in particular to an EAM-based asset full life cycle management method and system. Background Art

[0002] Enterprise asset management (EAM) system is an integrated computer management system for asset-intensive enterprises, which aims to improve the availability of assets and reduce enterprise operation and maintenance costs through information technology. The core goal of the EAM management system is to optimize the quality and utilization of assets throughout the life cycle, improve normal operation time and reduce operating costs.

[0003] The existing enterprise asset management (EAM) system can only manage the deployment location, deployment time, and usage status of tangible assets based on the intelligent collection terminals configured on the tangible assets, but cannot manage the status of the non-usage stage of tangible assets, such as the installation stage and maintenance stage. As a result, the enterprise management cannot accurately grasp the real status of tangible assets, which is not conducive to making the best management strategy in time, including equipment maintenance and replacement. The present invention aims to solve this technical problem to a certain extent. Summary of the invention

[0004] In this regard, the present invention provides an EAM-based asset full life cycle management method, system, electronic device, computer storage medium and computer program product to solve the above technical problems.

[0005] The present invention provides an EAM-based asset life cycle management method, which is applied to an EAM management system. The method includes the following steps: in response to detecting that a target asset is in an installation or maintenance stage, obtaining continuous status data of the target asset from the EAM management system based on the type attribute of the target asset; predicting first health status data and first residual value data of the target asset based on the continuous status data, and importing the first health status data and the first residual value data into a management entry corresponding to the target asset in the EAM management system; generating a management strategy for the target asset based on the first health status data and the first residual value data, and outputting management prompt information to management personnel based on the management strategy.

[0006] Optionally, the response to detecting that the target asset is in the installation or maintenance stage includes: receiving reporting information associated with the target asset uploaded by an intelligent acquisition terminal, and if the reporting information includes installation information or maintenance information, it is determined that the target asset is detected to be in the installation or maintenance stage; or, if the reporting information uploaded by the intelligent acquisition terminal is not received for more than a preset time period, it is determined that the target asset is detected to be in the installation or maintenance stage.

[0007] Optionally, the method of obtaining the continuous status data of the target asset from the EAM management system based on the type attribute of the target asset includes: screening out a number of other assets of the same type based on the type attribute of the target asset, obtaining usage data of each of the other assets, and calculating an average idle time according to each of the usage data; determining an acquisition time according to the average idle time, and obtaining the continuous status data of the target asset from the EAM management system according to the acquisition time.

[0008] Optionally, determining the acquisition duration according to the average idle duration includes: calculating the acquisition duration based on the average idle duration and the following formula (1) and formula (2), ; In the formula, To obtain the duration, To obtain a fixed duration, is the average idle time, is the adjustment factor, , is a constant, To calculate the average idle time Based on the mode values ​​of several idle time periods, To calculate the average idle time Based on median values ​​of several idle times.

[0009] Optionally, predicting the first health status data and the first residual value data of the target asset based on the continuous status data includes: inputting the continuous status data into a health trend prediction model constructed based on the Transformer model, the health trend prediction model deeply processing the continuous status data to predict the first health status data of the target asset; and evaluating the first residual value of the target asset based on the first health status data and the real-time market value corresponding to the target asset.

[0010] Optionally, the method also includes: in response to detecting that the target asset is not in the installation or maintenance stage, obtaining second health status data and second residual value data of the target asset from the EAM management system; wherein the second health status data and the second residual value data are obtained by analyzing in a non-predictive manner based on the status data associated with the target asset uploaded by the intelligent acquisition terminal; generating a management strategy for the target asset based on the second health status data and the second residual value data, and outputting management prompt information to the management personnel based on the management strategy.

[0011] The present invention also provides an EAM asset life cycle management system, which is applied to the EAM management system, and the system includes an acquisition module, a prediction module and a management module; the acquisition module is used to obtain the continuous status data of the target asset from the EAM management system based on the type attribute of the target asset in response to detecting that the target asset is in the installation or maintenance stage; the prediction module is used to predict the first health status data and the first residual value data of the target asset based on the continuous status data, and import the first health status data and the first residual value data into the management entry corresponding to the target asset in the EAM management system; the management module is used to generate a management strategy for the target asset based on the first health status data and the first residual value data, and output management prompt information to the management personnel based on the management strategy.

[0012] The present invention also provides an electronic device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the computer program implements the method described in any of the preceding items when executed by the processor.

[0013] The present invention also provides a computer storage medium storing a computer program executable by a processor to implement any of the methods described above.

[0014] The present invention also provides a computer program product, which includes a computer program that can be executed by a processor to implement any of the methods described above.

[0015] The beneficial effect of the present invention is that the scheme of the present invention can not only realize the management of tangible assets in the use stage, but also realize the management of tangible assets in the non-use stage, thereby realizing true full life cycle management of assets, which is very beneficial to the efficient management of assets by enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of a method for managing the entire life cycle of EAM assets disclosed in an embodiment of the present invention.

[0018] Figure 2 It is a structural diagram of an EAM asset life cycle management system disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0020] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0021] like Figure 1 As shown, an embodiment of the present invention discloses a method for full life cycle management of EAM assets, which is applied to an EAM management system, and the method includes the following steps: in response to detecting that a target asset is in an installation or maintenance stage, obtaining continuous status data of the target asset from the EAM management system based on the type attribute of the target asset; predicting first health status data and first residual value data of the target asset based on the continuous status data, and importing the first health status data and the first residual value data into the management entry corresponding to the target asset in the EAM management system; generating a management strategy for the target asset based on the first health status data and the first residual value data, and outputting management prompt information to management personnel based on the management strategy.

[0022] When it is detected that the target asset is currently in the installation or maintenance stage, the intelligent collection terminal set on the target asset will be unable to send the status data of the target asset to the EAM management system due to power failure, shutdown, etc., and the data in the management entry corresponding to the target asset in the EAM management system is empty, and the EAM management system cannot provide the management personnel with valid information corresponding to the target asset. In view of this technical problem, the present invention is set to obtain its continuous status data from the EAM management system based on the type attribute of the target asset when it is detected that the target asset is in the installation or maintenance stage. The continuous status data refers to the status data of the target asset at multiple continuous collection moments, and the status data includes but is not limited to the deployment location, deployment time, usage status, maintenance status, etc. According to the obtained continuous status data, the first health status data and the first residual value data of the target asset can be predicted, and then the obtained first health status data and the first residual value data are imported into the management entry corresponding to the target asset in the EAM management system. Therefore, even if the status data of the target asset in the installation or maintenance stage cannot be uploaded to the EAM management system, the EAM management system can generate a management strategy for the target asset based on the predicted first health status data and the first residual value data of the target asset, and then output management prompt information to the management personnel based on the management strategy.

[0023] Therefore, the solution of the present invention can not only realize the management of tangible assets in the use stage, but also realize the management of tangible assets in the non-use stage, thereby realizing true full life cycle management of assets, which is very beneficial to the enterprise's efficient management of assets.

[0024] Optionally, the response to detecting that the target asset is in the installation or maintenance stage includes: receiving reporting information associated with the target asset uploaded by an intelligent acquisition terminal, and if the reporting information includes installation information or maintenance information, it is determined that the target asset is detected to be in the installation or maintenance stage; or, if the reporting information uploaded by the intelligent acquisition terminal is not received for more than a preset time period, it is determined that the target asset is detected to be in the installation or maintenance stage.

[0025] In this embodiment, each target asset is equipped with an intelligent collection terminal, which periodically collects relevant status data of the corresponding target asset and reports it to the EAM management system. If installation information or maintenance information is parsed from the information reported by the intelligent collection terminal, it is determined that the target asset is currently in the installation or maintenance stage. The installation information or maintenance information can be manually input to the intelligent collection terminal by the installation or maintenance personnel.

[0026] During the installation or maintenance process, the intelligent collection terminal can be shut down or powered off, or it can be left powered off but set to stop reporting the target asset's status data to the EAM management system. Therefore, in addition to the above methods, a preset time can also be set. When the preset time is exceeded and no reporting information is received from the intelligent collection terminal, it is determined that the intelligent collection terminal is shut down and cannot report the target asset's status data to the EAM management system. At this time, it can also be directly determined that the target asset is detected to be in the installation or maintenance stage.

[0027] Optionally, the method of obtaining the continuous status data of the target asset from the EAM management system based on the type attribute of the target asset includes: screening out a number of other assets of the same type based on the type attribute of the target asset, obtaining usage data of each of the other assets, and calculating an average idle time according to each of the usage data; determining an acquisition time according to the average idle time, and obtaining the continuous status data of the target asset from the EAM management system according to the acquisition time.

[0028] In this embodiment, when the target asset is in the installation or maintenance stage, the predicted state of the target asset in the installation or maintenance stage, i.e., the first healthy state data and the first residual value data mentioned above, can be predicted in a short time by analyzing the continuous state data of the target asset stored in the EAM management system. Moreover, when the duration of the installation or maintenance stage is too long (e.g., 1 month), the practical significance of the prediction is particularly obvious. At the same time, the continuous state data of the target asset used to predict the first healthy state data and the first residual value data mentioned above should be within a reasonable range. Too much will lead to useless high computing load, while too little will lead to insufficient accuracy of the predicted first healthy state data and the first residual value data.

[0029] In view of the above technical problems, the present invention is set to decide the size of the time span for obtaining continuous status data according to the average idle time corresponding to the target asset. Specifically, based on the type attribute of the target asset, several other assets of the same type are screened. For example, if the target asset is a blender, the corresponding other assets are also blenders (which can be the same or different models). Then, the usage data of these other assets are obtained, wherein the usage data is the usage record of these other assets, including the date and time of use, the date and time of return, etc., and the average idle time of assets of this type can be statistically calculated based on this. Finally, the acquisition time corresponding to the target asset is determined according to the average idle time, and the continuous status data of the target asset is obtained from the EAM management system according to the acquisition time. For example, if the current time is 12:00 on December 20 and the acquisition time is 20 days, multiple status data of the target asset from 12:00 on December 01 to 12:00 on December 20 are obtained, that is, continuous status data.

[0030] Optionally, determining the acquisition duration according to the average idle duration includes: calculating the acquisition duration based on the average idle duration and the following formula (1) and formula (2), ; In the formula, To obtain the duration, To obtain a fixed duration, is the average idle time, is the adjustment factor, , is a constant, To calculate the average idle time Based on the mode values ​​of several idle time periods, To calculate the average idle time Based on median values ​​of several idle times.

[0031] In this embodiment, the average idle time refers to the length of time that each other asset has been idle in its life cycle up to the current stage, in days. The longer the asset is idle, the lower the maintenance frequency it receives, and the higher the probability of failure and the shorter the life cycle; conversely, the shorter the asset is idle, the more it is used, the higher the maintenance frequency it receives, and the lower the probability of failure and the longer the life cycle. It should be noted that assets and equipment (especially some heavy machinery and equipment) have a very long service life if they are properly maintained. Except for the end of the use of assets and equipment, the above relationship is applicable to a variety of assets and equipment.

[0032] Therefore, the present invention sets the acquisition duration and the average idle time of the asset to conform to the negative correlation represented by the above formula (1), that is, when the average idle time of the asset type to which the target asset belongs is longer, only the continuous status data of a short period of time is needed to more accurately predict the first health status data and the first residual value data of the target asset during the installation or maintenance stage; conversely, when the average idle time of the asset type to which the target asset belongs is shorter, the health change trend and the residual value change trend of the target asset are slower, and at this time, continuous status data of a longer period of time is needed to more accurately predict the first health status data and the first residual value data of the target asset during the installation or maintenance stage.

[0033] The present invention also sets the adjustment factor through formula (2): , the adjustment factor It is dynamic and is determined based on the relationship between the average idle time, the mode of idle time, and the median value. It is calculated based on the idle time of other assets, and the mode value is the majority value among these idle time.

[0034] Optionally, predicting the first health status data and the first residual value data of the target asset based on the continuous status data includes: inputting the continuous status data into a health trend prediction model constructed based on the Transformer model, the health trend prediction model deeply processing the continuous status data to predict the first health status data of the target asset; and evaluating the first residual value of the target asset based on the first health status data and the real-time market value corresponding to the target asset.

[0035] In this embodiment, after obtaining the continuous status data of the target asset with a suitable time span, the first health status data of the target asset during the installation or maintenance phase can be predicted based on the data. At the same time, since the real-time market value of the target asset (i.e., the real-time market price of the new target asset) can be obtained from the quotation platform, the first residual value data of the target asset is obtained based on the first health status data and the real-time market value evaluation of the target asset.

[0036] Among them, the Transformer model adopts a self-attention mechanism, which can process each element in the sequence data in parallel, which greatly improves the training and reasoning speed of the model, and the powerful parallel computing capability of the Transformer model is particularly suitable for the large amount of time series data that needs to be processed when predicting the health trend of asset equipment; and, the Transformer model can effectively capture the long-distance dependencies in the sequence through the self-attention mechanism, which is also very suitable for the health trend of asset equipment, because equipment failures are often related to problems accumulated in long-term operation. Therefore, the prediction of the first health status data is based on the above-mentioned health trend prediction model. The present invention chooses to use the Transformer model to construct the health trend prediction model. Among them, the training of the Transformer model is preferably carried out by optimizing the maximum likelihood logarithmic objective function loss.

[0037] Optionally, the method also includes: in response to detecting that the target asset is not in the installation or maintenance stage, obtaining second health status data and second residual value data of the target asset from the EAM management system; wherein the second health status data and the second residual value data are obtained by analyzing in a non-predictive manner based on the status data associated with the target asset uploaded by the intelligent acquisition terminal; generating a management strategy for the target asset based on the second health status data and the second residual value data, and outputting management prompt information to the management personnel based on the management strategy.

[0038] In this embodiment, the EAM management system manages the target assets throughout the entire life cycle, that is, it includes both the management of the use phase and the management of the non-use phase. For the non-use phase, the above has detailed the method of predicting the first health status data and the first residual value data of the target asset through continuous status data, and then analyzing the first health status data and the first residual value data to obtain the corresponding target asset management strategy. In the use phase, the intelligent acquisition terminal can smoothly upload the status data associated with the target asset to the EAM management system, and the EAM management system can analyze the second health status data and the second residual value data of the target asset. The analysis method here is generally the same as the above method, the main difference is that the second health status data is not obtained based on the previous continuous status data prediction, but is obtained based on the status data uploaded by the intelligent acquisition terminal and the corresponding health status comparison table, and then the second residual value data is obtained based on the comparison of the second health status data and the real-time market value evaluation corresponding to the target asset.

[0039] Among them, there are multiple groups of health states in the health state comparison table, such as 80%, 75%, 50%, 25%... These percentages represent the remaining service life of the target asset. And corresponding to these percentages are multiple comparison parameters, such as usage time, maintenance data (the difference between the number of maintenance times and the standard maintenance times, the difference between the maintenance interval and the standard maintenance interval, etc.). Correspondingly, in addition to installation information or maintenance information, the reporting information of the intelligent acquisition terminal also includes the status data of the target asset, and the status data includes usage time, maintenance data, deployment location, deployment time, etc. Alternatively, the status data of the target asset reported by the intelligent acquisition terminal is further analyzed and extracted to obtain the above-mentioned usage time, maintenance data, etc.

[0040] It should be noted that the management strategy for the target asset may be preset. For example, when the health status or residual value of the target asset is not good, management prompt information may be generated to remind the management personnel to perform more frequent maintenance or replacement (component replacement, equipment replacement) of the target asset, etc. The present invention does not specifically limit the specific content of the management strategy.

[0041] like Figure 2As shown, the present invention also discloses a management system based on the full life cycle of EAM assets, which is applied to the EAM management system, and the system includes an acquisition module, a prediction module and a management module; the acquisition module is used to obtain the continuous status data of the target asset from the EAM management system based on the type attribute of the target asset in response to detecting that the target asset is in the installation or maintenance stage; the prediction module is used to predict the first health status data and the first residual value data of the target asset according to the continuous status data, and import the first health status data and the first residual value data into the management entry corresponding to the target asset in the EAM management system; the management module is used to generate a management strategy for the target asset according to the first health status data and the first residual value data, and output management prompt information to the management personnel based on the management strategy.

[0042] The present invention also discloses an electronic device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the computer program implements the method of the aforementioned embodiment when executed by the processor.

[0043] The present invention also discloses a computer storage medium, which stores a computer program that can be executed by a processor to implement the method of the above embodiment.

[0044] The present invention also discloses a computer program product, which includes a computer program that can be executed by a processor to implement the method as described in the above embodiment.

[0045] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0046] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0047] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0048] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0049] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0050] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0051] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for managing the entire life cycle of EAM assets, applied to the EAM management system, characterized by: The method comprises the following steps: in response to detecting that the target asset is in the installation or maintenance stage, obtaining continuous status data of the target asset from the EAM management system based on the type attribute of the target asset; predicting first health status data and first residual value data of the target asset according to the continuous status data, and importing the first health status data and the first residual value data into the management entry corresponding to the target asset in the EAM management system; generating a management strategy for the target asset according to the first health status data and the first residual value data, and outputting management prompt information to a manager based on the management strategy; Based on the type attribute of the target asset, continuous status data of the target asset is obtained from the EAM management system, including: based on the type attribute of the target asset, a number of other assets of the same type are screened, usage data of each of the other assets are obtained, and an average idle time is calculated according to each of the usage data; an acquisition time is determined according to the average idle time, and the continuous status data of the target asset is obtained from the EAM management system according to the acquisition time; wherein the acquisition time is negatively correlated with the average idle time.

2. The EAM-based asset lifecycle management method according to claim 1, characterized in that: In response to detecting that the target asset is in the installation or maintenance stage, it includes: receiving reporting information associated with the target asset uploaded by the intelligent acquisition terminal, and if the reporting information includes installation information or maintenance information, it is determined that the target asset is detected in the installation or maintenance stage; or, if the reporting information uploaded by the intelligent acquisition terminal is not received for more than a preset time period, it is determined that the target asset is detected in the installation or maintenance stage.

3. The EAM-based asset lifecycle management method according to claim 1, characterized in that: Determining the acquisition duration according to the average idle duration includes: calculating the acquisition duration based on the average idle duration and the following formula (1) and formula (2), ; In the formula, To obtain the duration, To obtain a fixed duration, is the average idle time, is the adjustment factor, is a constant, To calculate the average idle time Based on the mode values ​​of several idle time periods, To calculate the average idle time Based on median values ​​of several idle times.

4. The EAM-based asset lifecycle management method according to claim 3 is characterized in that: Predicting the first health status data and the first residual value data of the target asset based on the continuous status data includes: inputting the continuous status data into a health trend prediction model constructed based on the Transformer model, the health trend prediction model deeply processes the continuous status data, and predicts the first health status data of the target asset; and evaluating the first health status data and the real-time market value corresponding to the target asset to obtain the first residual value data of the target asset.

5. The EAM-based asset lifecycle management method according to claim 1, characterized in that: The method also includes: in response to detecting that the target asset is not in the installation or maintenance stage, obtaining second health status data and second residual value data of the target asset from the EAM management system; wherein the second health status data and the second residual value data are obtained by analyzing in a non-predictive manner based on the status data associated with the target asset uploaded by the intelligent acquisition terminal; generating a management strategy for the target asset based on the second health status data and the second residual value data, and outputting management prompt information to the management personnel based on the management strategy.

6. A management system based on the full life cycle of EAM assets, applied to the EAM management system, the system is based on the method described in any one of claims 1 to 5; the system includes an acquisition module, a prediction module and a management module; characterized in that: The acquisition module is used to obtain the continuous status data of the target asset from the EAM management system based on the type attribute of the target asset in response to detecting that the target asset is in the installation or maintenance stage; the prediction module is used to predict the first health status data and the first residual value data of the target asset based on the continuous status data, and import the first health status data and the first residual value data into the management entry corresponding to the target asset in the EAM management system; the management module is used to generate a management strategy for the target asset based on the first health status data and the first residual value data, and output management prompt information to the management personnel based on the management strategy.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the computer program implements the method according to any one of claims 1 to 5 when executed by the processor.

8. A computer storage medium, characterized in that: The computer storage medium stores a computer program that can be executed by a processor to implement the method according to any one of claims 1 to 5.

9. A computer program product, characterized in that: The computer program product comprises a computer program executable by a processor to implement the method according to any one of claims 1 to 5.

Images