How to integrate key indicators of virtual objects in software components?

Abstract

To provide a computer implemented method for consolidating at least one key indicator of a virtual object.SOLUTION: A method comprises, for a predefined configuration of a virtual object, the steps of: receiving a description of at least one key indicator of the virtual object; receiving a set of attributes of the virtual object; receiving a data model for indexation of the virtual object; receiving a set of rules to convert the attributes of the virtual object into the data model for indexation; applying the set of rules to convert said attributes into the data model for indexation; transforming, in an index, the data model for indexation into a directed acyclic graph; and consolidating, in a software component which is distinct from the index, the key indicator based on an expansion of the directed acyclic graph.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to the field of Computer Aided Engineering (CAE), more precisely to the field of Computer Aided Design (CAD). It relates to a computer-implemented method for integrating key indicators of a virtual object composed of several object parts, in particular complex objects. [Background technology]

[0002] Key Indicators (KI) are major characteristics that allow strategic decisions to be made. There are several types of key indicators, including: -Key sustainable indicators (KSIs), e.g. carbon footprint, impact on scarce resources. - Key Quality Indicators (KQIs), for example, the defect rate during manufacturing of the part in question. -Key Performance Indicators (KPIs), for example the weight of the object (hereinafter also called mass), its inertia matrix, its center of gravity (these parameters are commonly called "weight and balance"), and the characteristics of the object: range, destruction distance, air penetration coefficient, minimum length of the track for takeoff or landing, etc.

[0003] Within a few decades, the number of parts that make up complex objects expanded significantly in digital models, from thousands to millions of parts, thereby making the integration of key indicators extremely complex.

[0004] An object can be described by the use of a global structure consisting of an engineering bill of materials (reflecting how the object is designed), a manufacturing bill of materials (focusing on the parts required to manufacture the object), a process bill of materials for the object in use, and a bill of materials at the end of the object's life. The manufacturing bill of materials describes the object in terms of subassemblies. It consists of an itemized list of the parts of the structure that are shown, for example, in a drawing in the form of a table. The bill of materials can therefore be represented in a hierarchical tree structure with a root entity and a subtree of children (leaves) with parent nodes. Consolidating the key indicators of an object is an examination of this global bill of materials, from the leaves to the root of the tree. The bottom-up calculation of metrics is done by a rollup operation (or simply called "rollup"). The rollup function is defined as the way in which the values ​​of the metrics are calculated bottom-up. At each level of the tree, a complex process of decision-making and consolidation is applied.

[0005] Some key indicators are relatively easy to integrate. For example, integrating the mass of a virtual object consists of adding the mass of all parts of the object. Thus, the rollup mainly consists of adding value, but does not consume much CPU. However, the problem is that during the manufacturing and engineering process, various subcontractors are implied. This means that the data needed to integrate key indicators (text documents, spreadsheets, ERP software, or CAD software), even those that do not consume CPU, may be stored in several systems and may not be up to date. Each of these systems may be considered a "silo" insofar as each system is insulated from the others. Operating in silos impacts the efficient integration of key indicators.

[0006] Other key indicators relate to the inertia matrix of the object. To integrate the inertia matrix, it is first necessary to calculate the products of the moments of inertia and the inertia of the leaves. The inertia matrix is ​​then a 3x3 matrix containing these values ​​in relation to the 3-axis system in which the object is instantiated. Then the inertia matrix is ​​diagonalized. The diagonalized eigenvalues ​​are the principal moments of inertia of the object, and the three eigenvectors are the principal axes of inertia. It can be noticed that diagonalizing a matrix is ​​CPU consuming. Furthermore, once the inertia matrix is ​​calculated for a part of the object (corresponding to the lowest child in the table of materials), the inertia matrix of the parent part of the object is calculated based on the moments of inertia of the children, and based on the axes of inertia of the child objects. Thus, a very complex matrix calculation is performed when rolling up the inertia matrix from children to parents in the table of materials. In that case, the rollup is performed by implementing the parallel axis theorem, also known as the Huygens-Steiner theorem. In that case, the rollup function is determined by the Huygens-Steiner theorem.

[0007] So integrating the key indicator with millions of parts lasts for hours, which is unacceptable. Especially the exact measurement of weight and balance of a cruise ship is a very complex operation compared to other key indicators and is actually estimated with a high degree of uncertainty during the design of the ship. In fact, manufacturers cannot determine the exact mass of the ship during the design phase, or even during the manufacturing phase. Once built, the ship is launched in the water and the mass is derived from the amount of water displaced. If the buoyancy needs to be corrected, the ship is weighed with additional equipment. It is worth noting that the weight and balance of a cruise ship is very important, as it indicates how the cruise ship passes through the waves.

[0008] In the automotive sector, a large number of key performance indicators (KPIs) are monitored during the vehicle design process. For example, for a racing car, up to 350 KPIs can be monitored. In practice, during a project review, a huge amount of key performance indicators are analyzed and some key performance indicators may be prioritized over others. KPI integration is a fully integrated decision-making procedure. It should therefore be performed whenever a strategic decision needs to be made.

[0009] Another constraint in the automotive sector is related to the large number of possible configurations of a vehicle. Until now, car manufacturers have consolidated one key performance indicator for only one vehicle, i.e. the heaviest commercial vehicles, without taking into account the diversity of configurations. The consolidation is therefore performed for a single graph. Moreover, even for a limited number of vehicles, the consolidation lasts for a few hours, so the consolidated data is not up-to-date. As vehicles consist of more and more parts, the consolidation of KPIs takes more and more time, regardless of the different configurations.

[0010] Key performance indicators such as mass are also important in space engineering, especially in satellites. Agreements between launcher operators / manufacturers and satellite operators / manufacturers usually have specific provisions related to the mass of the satellite, so that it does not exceed a predefined mass. Indeed, during the launch phase, each kilogram of payload is important in terms of propellants. In practice, launcher operators / manufacturers may apply penalties of several thousand euros for an error of 1 kg of the satellite. Mass indicators must therefore be closely monitored. It is also interesting for satellite operators / manufacturers to be able to quantify the tolerances calculated during roll-up, for example through a margin of error. Summary of the Invention [Problem to be solved by the invention]

[0011] There is therefore a need to provide a method for aggregating key indicators of virtual objects that is scalable, manages different data sources from different suppliers, and takes into account the diversity of configurations of the objects. [Means for solving the problem]

[0012] The object of the invention is a computer-implemented method for integrating at least one key indicator of a virtual object, said method comprising the steps of: a) receiving a description of at least one key indicator of a virtual object; b) receiving a set of attributes of the virtual object; c) receiving a data model for indexing the virtual objects; d) receiving a set of rules for transforming attributes of the virtual object into a data model for indexing; e) applying a set of rules to transform said attributes into a data model for indexing; f) transforming the data model for indexing into a directed acyclic graph within the index; g) integrating the key indicators into a software component distinct from the index based on an extension of a directed acyclic graph; Includes.

[0013] In a preferred embodiment, in the data model, a virtual object is at least one aggregate feature, which represents a configuration of the virtual object according to a bill of materials; and / or at least one facet feature, which represents a classification of the virtual object; It is characterized by:

[0014] In a preferred embodiment, the aggregate features and facet features are referenced in an index.

[0015] In a preferred embodiment, the aggregate features and / or facet features are updated incrementally in the index.

[0016] In a preferred embodiment, step g) includes applying the rollup to the expanded directed acyclic graph in the index.

[0017] In a preferred embodiment, step a) comprises receiving a rollup function of the key indicators during a rollup on the expanded directed acyclic graph, said rollup function representing how the key indicators are bottom-up integrated into a bill of material of the virtual object.

[0018] In a preferred embodiment, step g) includes receiving a tolerance value for each aggregate feature and calculating a statistical tolerance value based on the Euclidean distance of said tolerance values.

[0019] In a preferred embodiment, the key indicators are key performance indicators of the virtual object.

[0020] In a preferred embodiment, the key performance indicators include the weight and balance of the object, in particular the weight of the virtual object and / or the centre of gravity of the virtual object and / or the inertia matrix of the virtual object.

[0021] In a preferred embodiment, the directed acyclic graph is transferred from the index to the software components via a client-server communication protocol.

[0022] In a preferred embodiment, the client-server communication protocol is the HyperText Transfer Protocol.

[0023] In a preferred embodiment, the virtual object is a vehicle, in particular a ship.

[0024] The present invention also relates to a computer program product stored on a non-volatile computer readable data storage medium, comprising computer executable instructions for causing a computer system to perform the above-described method.

[0025] The invention also relates to a non-transitory computer-readable data storage medium comprising computer-executable instructions for causing a computer system to perform the aforementioned method.

[0026] The invention also relates to a computer system configured to perform the aforementioned method, comprising at least one client device configured to process a user request to integrate at least one key indicator of a virtual object and at least one index, said index configured to perform at least the steps of transforming a data model for indexing into a directed acyclic graph and a software component distinct from said index for integrating said key indicators based on an extension of the directed acyclic graph. [Brief description of the drawings]

[0027] Additional features and advantages of the present invention will become apparent from the subsequent description taken in conjunction with the accompanying drawings in which: [Figure 1] FIG. 2 illustrates the index build phase in the method according to the invention. [Diagram 2] FIG. 2 illustrates a data model used in the method according to the invention. [Diagram 3] FIG. 13 illustrates an example of key indicator information attached to an entity of a data model. [Figure 4] FIG. 1 illustrates an example set of rules that drive the transformation of engineering information into a data model, and also includes the transformation of diversity information into a data model. [Diagram 5] FIG. 1 shows an example set of rules driving the transformation of manufacturing information into a data model, which also includes the transformation of diversity information into a data model. [Figure 6] FIG. 1 illustrates an example bill of materials that includes three objects. [Figure 7] FIG. 7 illustrates indexing of the objects shown in FIG. 6 according to the data model of the present invention. [Figure 8] FIG. 1 illustrates a computer environment in accordance with the present invention. [Figure 9] FIG. 13 is a diagram showing an example of a display of roll-up results of ship weight and balance. [Figure 10] FIG. 1 illustrates a computer suitable for performing methods according to exemplary embodiments of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] The present invention relies on two main steps called "build" and "run". Figure 1 shows the main steps of the build, where four computing systems CSY are represented. Of course, the number of computing systems CSY is not limited. Each computing system CSY: - PLM (Product Lifecycle Management) system CSY1, including a CAD (Computer-Aided Design) system providing 3D modeling data of virtual objects, and its diversification dictionary; - CSY2, an ERP (Enterprise Resource Planning) system providing supply chain data; - EIS (Enterprise Information System) SY3; - several sensors CSY4 connected to a network such as the Internet to collect data and transmit them directly or not directly to another entity; It is.

[0029] The computing systems (CSY1, CSY2, CSY3, CSY4) are connected to an index IND of a search engine. The index IND is stored on a machine or set of machines that are connected to the computing system CSY via a connection means (cable, fiber optic, or wireless using one of the wireless communication protocols). By "index" one skilled in the art can also refer to a "cache" or "data lake", i.e. a software component that can be queried and that contains raw and structured, semi-structured, or unstructured data.

[0030] A description of each key indicator is provided upstream of step a) of the method, specifically by a superuser. Indeed, the descriptions of key indicators are not intended to be modified by normal users. The descriptions of key indicators include a rollup function, i.e., the behavior of the key indicators during rollup on the unfolded directed acyclic graph. The rollup function represents how, for one configuration, the key indicators are integrated bottom-up into the bill of materials of the virtual configuration object OBJ.

[0031] The key indicator description states: - name (e.g. noise, mass, inertia matrix); - magnitude (e.g. mass, temperature, pressure); - potentially security regarding access (editable by superusers or normal users); - Potentially, the father and his children.Indeed, a key indicator may contain elements which are themselves key indicators; - A series of analyses potentially bringing complementary information to key indicators; - Potentially, an icon, Also includes.

[0032] In step b) of the method of the invention, a set of attributes ATT of the virtual object is received by the index. The attributes ATT are data provided to the index IND by any of the computing systems CSY. The attributes ATT thus characterize the object according to its originating computing system CSY.

[0033] A single data model DM is provided in step c) of the method. The data model represents the typing of the objects in the index IND and of the links that make up the objects in the index IND. All attributes ATT sent to the index IND are transformed according to the data model DM shown in figure 2.

[0034] The contents of the conversion are: 1. Interpret the object OBJ from the computer system CSY and enter it according to the data model DM, 2. Creating links between objects that may come from computer systems CSY. It is important to note that these links do not exist between computer systems CSY. They only exist in the index IND. Thus, the index is a software component that creates semi-structured data based on initially unstructured data.

[0035] The data model DM may be qualified as "independent" to the extent that any attribute of an object is transformed according to the data model, regardless of the originating computing system CSY or regardless of the format of the attribute ATT.

[0036] In the data model DM, two elements characterize a virtual object: at least one aggregate feature AGG, which represents the configuration of the virtual object OBJ according to a bill of material, and / or at least one facet feature FAC, which represents the classification of the virtual object OBJ. For example, a machine part may have a material facet, a recycling facet, a supply facet, etc. More generally, the facet feature specifies the virtual object. The aggregate feature AGG defines the configuration of the object according to a bill of material. An example of a configuration is the instantiation of an object. By "instance" one skilled in the art refers to its position and orientation in a reference frame attached to the object. The aggregate feature AGG and the facet feature FAC are referenced by an index IND.

[0037] Figure 3 shows an example of key indicator information attached to entities in a data model. For example: - The key indicator KI1 is oriented towards weights with three facets: value, tolerance and confidence level; - The key indicator KI2 is oriented towards carbon footprint with three facets: value, tolerance and confidence level; - the key indicator KI3 is oriented to the nominal power with three facets: value, tolerance and confidence level; - The key indicator KI4 is oriented towards the center of gravity with three facets: value, tolerance and confidence level.

[0038] When an attribute is indexed, the tolerance value may be copied into the data model DM. In a preferred embodiment, a statistical tolerance may be calculated based on the Euclidean distance of the tolerance value. Considering a father and n children:

[0039]

number

[0040] is within the father's tolerance range,

[0041]

number

[0042] is the tolerance of the ith children. The paternity tolerance is calculated using the following formula:

[0043]

number

[0044] Thus, when aggregating key indicators, the user also gets the tolerance values ​​associated with the key indicators, so that the tolerance values ​​calculated during the rollup can be quantified, for example, with a margin of error.

[0045] Step d) of the inventive method comprises receiving a set of rules RUL for converting attributes of a virtual object OBJ into a data model DM for indexing, and step e) of the inventive method comprises applying said set of rules RUL for converting said attributes into a data model DM for indexing.

[0046] For example, Figure 4 shows the rules for transforming engineering information into a data model DM during the build phase. The "check mark" symbol represents that the attribute is indexed. The "cross" symbol represents that the attribute is not indexed. The "arrow" symbol represents the flattening of the attribute: it is copied to an indexed attribute and then removed from the index. The decision to index or not an attribute or to aggregate it is made by the superuser based on the required key indicators. Thus, the rules differ depending on the scenario. An attribute may be aggregated with facets to categorize it.

[0047] For example, representations of visualization triangles or geometric shapes of mathematically defined objects do not need to be indexed. Key indicators do not need to be indexed as objects, since diversity (configurations) cannot be applied. In indexing, the key indicators become attributes of objects in the product's bill of materials. Objects in the diversity dictionary (also called configurations) do not participate in the bill of materials, so they do not need to be indexed. On the other hand, the options used to define the configurations are indexed. If diversity is not possible, a flattening operation is performed. Elements that contribute nothing to the bill of materials are not indexed.

[0048] Similarly, FIG. 5 shows the rules for transforming manufacturing information into a data model during the build phase.

[0049] Figure 6 shows a bill of materials BOM that contains three object parts of an aircraft (first object part OBJ1, second object part OBJ2, and third object part OBJ3). The attributes of the objects are converted for indexing with index IND, as shown in Figure 7.

[0050] In Figure 7, a directed acyclic graph representing an aircraft is created in index IND. It aggregates information from a first computing system CSY1, such as a PLM system, from a second computing system CSY2, such as an EIS, and from a third computing system CSY3, such as an ERP. Information from the different silos is structured in index IND.

[0051] Attributes ATT of three computing systems (CSY1, CSY2, CSY3) are transformed into a data model DM for indexing with index IND.

[0052] In a first computing system CSY1, a root object (the object in which the key indicators are integrated, i.e. the "aircraft") is stored together with simplified representations of the 3D geometry of objects OBJ1, OBJ2 and OBJ3.

[0053] - the attribute "Estimated weight" of the first object OBJ1 with a value of 37 kg.

[0054] - The third object OBJ3 has the attribute "Calculated weight" with a value of 31.2 kg and a confidence value of 30%.

[0055] - Uses a simplified representation of the 3D geometry of three objects: OBJ1, OBJ2, and OBJ3.

[0056] In the second calculation system CSY2, the attribute "weight" of the second object OBJ2 is stored with a value of 22 kg.

[0057] In a third computing system CSY2 the attribute "measured weight" of a third object OBJ3 is stored with a value of 33.2 kg and a confidence value of 80%.

[0058] The aforementioned attributes ATT are transformed into a data model DM for indexing. Then the root object “Aircraft” is aggregated.

[0059] - First element C1 with CSY2 facet C5.

[0060] - Second element C2 with CSY3 facet C4.

[0061] - The third element, C3.

[0062] Next, once the attribute ATT has been transformed according to the data model DM for indexing, the data model is transformed into a directed acyclic graph in the tree data structure (step f) of the method of the invention, as shown in FIG.

[0063] Once the data model is transformed into a directed acyclic graph during the build phase, the execute phase can be performed on the directed acyclic graph. In a preferred embodiment, the aggregate features AGG and / or facet features FAC are updated incrementally in the index IND, without the need to execute the build phase from scratch every time the data changes. The execute phase, including the consolidation of key indicators, is therefore based on the extension of the directed acyclic graph with the latest data (step g of the invented method), taking into account the configuration (set of options from the diversity). On each object of the extended graph, from bottom to top, a specific consolidation method of key indicators (i.e., rollup function) is called.

[0064] 8 is a diagram of a computer environment according to the invention. The system comprises at least one client device CD configured to process a user request to integrate at least one key indicator of a virtual object. For example, the user request may be queried by one of the program managers of the 3D object during the engineering phase or during the manufacturing phase of the object.

[0065] In a preferred embodiment, the step of transforming the initial data into the data model (build phase) is implemented in the index IND, and the step of integrating the key indicators (execution phase) is implemented in the software component SCO (which may be called a roll-up component distinct from the index IND). The directed acyclic graph on which the graph evolution depends is replicated between the index IND and the software component SCO. The directed acyclic graph is computed in the index IND and transferred to the software component SCO via stream / unstream technology based on the HyperText Transfer Protocol. The index and the software component SCO run in two different software layers.

[0066] Referring to the example in Figure 7, the index IND expands the aircraft tree (the root aircraft itself and its three children with two second-level children), and the software component SCO rolls up the expanded tree. When the tree is expanded, six elements (C1 to C6) are obtained. The rollup integrates the weight information from the bottom to the top of the tree. The weight of the fifth element C5 is 22 kg. The weight of the fourth element C4 is 33.2 kg. The weight of the third element C3 is 37 kg. The weight of the first element C1 is 22 kg, since the first element C1 directly obtains the same value as the fifth element C5. For the second element C2, the information from the two facets is compared. Since the confidence level of 80% is greater than 30%, the weight of the second element C2 is considered to be 33.2 kg. Finally, the aircraft, which aggregates the first element C1, the second element C2, and the third element C3, is considered to have a weight of 22 + 33,2 + 37 = 92,2 kg.

[0067] Steps a) to f) (build phase) of the method of the present invention can be performed offline and step g) (run phase) can be performed online. Performing the build phase offline can save significant computation time.

[0068] Figure 9 shows a screenshot depicting the results of the weight and balance KPI for a cruise ship using the method of the invention. On the left side of the screen, the user can browse the tree of objects and select the whole object or its sub-parts. The user's selection may be highlighted in the central part of the screen. On the right side of the screen, the results of the integration are displayed, in particular the weight, center of gravity and inertia matrix.

[0069] The methods of the present invention can be carried out by a suitably programmed general-purpose computer or computer system, possibly including a computer network, that stores a suitable program in non-volatile form on a computer-readable medium such as a hard disk, solid state disk, or CD-ROM, and can execute said program using a microprocessor and memory.

[0070] Each of the aforementioned client device CD, computing system CSY, index IND and software component SCO is a computer CPT suitable for performing the method according to an exemplary embodiment of the invention described with reference to Fig. 10. In Fig. 10, the computer CPT comprises a central processing unit (CPU) P for performing the above-mentioned method steps while executing an executable program, i.e. a set of computer-readable instructions, stored in a memory device such as a RAM M1 or a ROM M2, or a hard disk drive (HDD) M3, a DVD / CD drive M4, or stored remotely.

[0071] The claimed invention is not limited by the form of the computer readable media on which the computer readable instructions and / or data structures of the processes of the invention are stored. For example, the instructions and files can be stored on a CD, DVD, flash memory, RAM, ROM, PROM, EPROM, EEPROM, hard disk, or other information processing device with which the computer communicates, such as a server or computer. The programs and files can be stored on the same memory device or on different memory devices.

[0072] Furthermore, computer programs suitable for carrying out the methods of the present invention may be provided as a utility application, a background daemon, and / or a component of an operating system and run in conjunction with a CPU P and an operating system such as Microsoft VISTA, Microsoft Windows 10, UNIX, Solaris, LINUX, Apple MAC-OS, and other systems known to those skilled in the art.

[0073] The CPU P can be a Xenon processor from Intel of America or an Opteron processor from AMD of America, or other processor types such as a Freescale ColdFire, IMX, ARM processor from Freescale Corporation of America. Alternatively, the CPU can be a processor such as a Core2 Duo from Intel Corporation of America, or can be implemented in an FPGA, ASIC, PLD, or using discrete logic circuitry, as will be appreciated by those skilled in the art. Additionally, the CPU can be implemented as multiple processors operating in concert to execute the computer readable instructions of the process of the present invention described above.

[0074] The computer CPT of FIG. 10 also includes a network interface NI, such as an Intel Ethernet PRO network interface card from Intel Corporation of America, for interfacing with a network, such as a local area network (LAN), a wide area network (WAN), or the Internet. The computer further includes a display controller DC, such as an NVIDIA GeForce GTX graphics adapter from NVIDIA Corporation of America, for interfacing with a display DY, such as a Hewlett-Packard HPL2445w LCD monitor. A general purpose I / O interface IF interfaces with a keyboard KB and a pointing device PD, such as a roller ball, mouse, or touch pad. The display, keyboard, and pointing device, together with the display controller and I / O interface, form a graphical user interface, which the user uses to provide input commands and the computer uses to display the results of key indicators.

[0075] The disk controller DKC connects the HDDM3 and DVD / CD M4 to a communication bus CBS, such as ISA, EISA, VESA, PCI, etc., to interconnect all components of the computer.

[0076] A description of the general features and functions of the display, keyboard, and pointing device, as well as the display controller, disk controller, network interface, and I / O interface, is omitted here for the sake of brevity, since these features are known.

[0077] In an alternative embodiment, the computer CPT is replaced by a server and an end-user computer. The overall architecture of the server is the same as described above for the computer CPT, except that the server may not have a display controller, a display, a keyboard, and / or a pointing device. The end-user computer runs the front-end section of the "execution" infrastructure, including the user interface. The server runs the "build" infrastructure and the back-end section of the "execution" infrastructure. User actions on the user interface launch queries (such as REST queries) to a web service provided by a server (such as an Apache server) that runs the key indicator rollup algorithm.

[0078] The network NW may be a public network such as the Internet, a private network such as a LAN or WAN network, or any combination thereof, including PSTN or ISDN sub-networks. The network NW may be wired, such as an Ethernet network, or wireless, such as a cellular network, such as EDGE, 3G, 4G wireless cellular systems. The wireless network may be Wi-Fi, Bluetooth, or other known wireless forms of communication. Thus, the network NW is merely illustrative and in no way limits the scope of the present advancements.

[0079] Any method steps described herein should be understood as representing a module, segment, or portion of code that contains one or more executable instructions for performing a particular logical function or step in a process, and alternative implementations are included within the scope of the exemplary embodiments of the present invention.

Claims

1. 1. A computer-implemented method for integrating at least one key indicator of a virtual object (OBJ), comprising: a) receiving a description of at least one key indicator of a virtual object; b) receiving a set of attributes (ATT) of said virtual object; c) receiving a data model (DM) for indexing said virtual objects; d) receiving a set of rules (RUL) for transforming the attributes of the virtual object (OBJ) into the indexing data model (DM); e) applying said set of rules (RUL) to transform said attributes into said indexing data model (DM); f) in an index (IND), transforming said indexing data model (DM) into a directed acyclic graph; g) in a software component (SCO) different from the index (IND), based on the unfolding of the directed acyclic graph, rolling up attributes of the directed acyclic graph to consolidate the key indicators; A method comprising:

2. In the data model (DM), the virtual object is at least one aggregate feature (AGG), which represents the composition of said virtual object (OBJ) according to a bill of materials, and / or at least one facet feature (FAC), which represents a classification of said virtual object (OBJ); The method of claim 1 , characterized by:

3. The method of claim 2 , wherein the aggregate features (AGG) and the facet features (FAC) are referenced in the index (IND).

4. The method according to claim 2 or 3, wherein the aggregate features (AGG) and / or the facet features (FAC) are incrementally updated in the index (IND).

5. 5. The method of claim 1, wherein step g) comprises applying a rollup to the unfolded directed acyclic graph in the index (IND).

6. 6. The method of claim 5, wherein step a) comprises receiving a rollup function of the key indicators during a rollup on the unfolded directed acyclic graph, the rollup function representing how the key indicators are bottom-up integrated in a bill of material of the virtual object (OBJ).

7. 7. The method of claim 2, wherein step g) comprises receiving a tolerance value for each aggregate feature (AGG) and calculating a statistical tolerance value based on a Euclidean distance of the tolerance values.

8. The method according to claim 1 , wherein said key indicators are key performance indicators (KPIs) of said virtual object (OBJ).

9. The method of claim 8 , wherein the key indicators (KPIs) comprise the weight and balance of the virtual object, or the weight of the virtual object and / or the centre of gravity of the virtual object and / or the inertia matrix of the virtual object.

10. The method according to any one of claims 1 to 9, wherein said directed acyclic graph is transferred from said index (IND) to said software component (SCO) via a client-server communication protocol.

11. 11. The method of claim 10, wherein the client-server communication protocol is the HyperText Transfer Protocol.

12. The method according to any one of claims 1 to 11, wherein the virtual object (OBJ) is a vehicle or a boat.

13. A computer program stored on a non-volatile computer readable data storage medium, comprising computer executable instructions for causing a computer system to carry out the method of any one of claims 1 to 12.

14. A non-transitory computer-readable data storage medium (M1, M2, M3, M4) having computer-executable instructions recorded thereon for causing a computer (CPT) system to execute a method according to any one of claims 1 to 12.

15. A computer system configured to implement the method according to any one of claims 1 to 12, comprising: At least one client device (CD) configured to process a user request to integrate at least one key indicator of a virtual object; at least one index (IND) configured to implement at least a step of transforming said indexing data model (DM) into a directed acyclic graph; a software component (SCO) distinct from said index (IND) for synthesizing said key indicators based on the unfolding of said directed acyclic graph; A computer system comprising:

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