A device selection method and system using digital twin technology

Abstract

The present invention provides an equipment selection system by means of digital twin technology, comprising: a client used by a factory, a supplier side used by a supplier, and an equipment pre-selection device that is data-connected to the client and the supplier side. The client collaborates with the equipment pre-selection device to construct a digital twin factory of the user's factory. The supplier uploads supply data for constructing digital twin modules to the equipment pre-selection device. The client provides the expected parameters of the equipment to be replaced to the equipment pre-selection device. The equipment pre-selection device filters digital twin modules based on the expected parameters. The equipment pre-selection device assigns a digital twin factory copy to each filtered digital twin module based on the filtering results. The equipment pre-selection device replaces the equipment to be replaced in each digital twin copy with the digital twin module and performs simulation. The equipment pre-selection device outputs the simulation parameters obtained from the simulation to the client so that the user can select the desired product through the client.

Description

Technical Field

[0001] The present invention relates to the field of replacement and selection of factory equipment, and relates to a method and system for equipment selection with the aid of digital twin technology. Background Art

[0002] Currently, for equipment selection in factories, usually, technical personnel in the factory first investigate the existing equipment in the factory to understand its working parameters. After obtaining the working parameters, based on the expected production goals of the factory, the expected parameters of the replacement equipment are determined, and then products that meet the requirements are searched for in the market. The search method is usually to query the product specification sheets printed and distributed by suppliers. The prior art is inefficient. First, the product specification sheets distributed by suppliers have timeliness and geographical restrictions, and factories usually cannot access more suppliers and more product options. Second, the equipment in the product specification sheets may not necessarily meet the needs of the factory. Since the products are already finalized, even if they meet the factory's needs on paper, problems may still occur during operation after actual installation.

[0003] When manufacturers conduct equipment selection, they have special parameters that they are concerned about, and these parameters may not be standard parameters in the suppliers' specification sheets and are not marked. Therefore, when manufacturers replace equipment, they lack comparison parameters and can only select models based on standard parameters. On the other hand, in some cases, neither manufacturers nor suppliers can anticipate the parameters that need to be inspected after the product equipment is replaced, especially the newly added parameters that need to be inspected after the product equipment is replaced. The main reason is that manufacturers and suppliers do not know each other's specific situations well, so it may occur that the parameter inspection sheets selected by manufacturers and suppliers during model selection are not perfect.

[0004] Taking pumps as an example, the following problems exist:

[0005] Firstly: The process of comparing the calculated design parameter values by designers with a large number of pumps with various parameters provided by existing suppliers is very cumbersome. The product specification sheets provided by each supplier have their own different layout and classification formats, which require a large amount of human and time costs. In addition, the details and parameter indicators of different product specification sheets are different, and these factors will reduce the pump selection efficiency of designers and even cause deviations when designers compare multiple suppliers.

[0006] Secondly: Since the various parameters of the pumps provided by each supplier are determined, there are often situations where some parameters are not exactly the same as the theoretical design parameter values. This is caused by the unique production purposes and requirements of the system. Therefore, the selected pumps generally can only be close to the design parameter values and cannot be exactly the same. It is difficult to select the most suitable pump for system operation from among the many alternative pumps that may meet the requirements, and the verification of performance and stability is rather cumbersome.

[0007] In addition, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making the present invention, but due to space limitations, not all details and contents are listed in detail. However, this does not mean that the present invention does not have the characteristics of these prior arts. On the contrary, the present invention already has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art to the background technology. Summary of the invention

[0008] In the prior art, establishing collaborative connections between the client and the supplier through an online management platform has become a development trend of the industrial Internet. For example, CN112100965A discloses a collaborative innovation platform for the electronic manufacturing industry and a method for using the same. In the technical solution, the designer uses the client's design tool cloud and IP service cloud to design and simulate the required products. The design files are encrypted by the collaborative innovation platform and transmitted to the backend management end; the intelligent recognition module receives and decrypts the encrypted design files, and automatically matches each supplier's equipment that meets the product process flow and process parameters through the deep mapping algorithm according to the decrypted design files, and generates a corresponding encrypted order and sends it to the supplier end; after decryption, the supplier end simulates the production scene, supplier equipment and production process through the digital twin cloud according to the product process flow, process parameters and corresponding supplier equipment recorded in the order, and generates a 3D panoramic display platform to achieve online visualization. The technical solution establishes a visual model that matches the client's needs through the backend management platform, thereby intuitively feeding back the client's expected effects, so as to facilitate adaptive adjustments based on the model results. However, the above-mentioned prior art is limited to the adjustment of the client's needs, and cannot reflect the adjustment needs of the supplier end.

[0009] In view of the shortcomings of the prior art, the present invention provides an equipment selection system with the help of digital twin technology, including: a user end used by a factory, a supplier end used by a supplier, and an equipment pre-selection device that is data-interconnected with the user end and the supplier end.

[0010] The user side collaborates with the equipment pre-selection device to build a digital twin factory of the user factory, and the supplier uploads the supply data used to build the digital twin module to the equipment pre-selection device.

[0011] The client provides the expected parameters of the device to be replaced to the device pre-selection device. The device pre-selection device filters the digital twin modules based on the expected parameters. The device pre-selection device assigns a digital twin factory copy to each filtered digital twin module based on the filtering result. The device pre-selection device replaces the device to be replaced in each digital twin copy with the digital twin module and performs simulation. The device pre-selection device outputs the simulation parameters obtained from the simulation to the client so that the user can select the desired product through the client. On the one hand, the present invention can provide the expected parameters of the device to be replaced to the device pre-selection device through the client. On the other hand, it can also upload the supply data for constructing the digital twin module to the device pre-selection device by the supplier. Based on the above technical means different from the prior art, the technical problem to be solved by the present invention is how to realize the end-to-end two-way construction process of the digital twin factory copy.

[0012] During the operation of the user factory, when it is desired to replace a device that is in use, the present invention provides a continuous selection scheme based on digital twin technology. The user can select the device to be replaced from the digital twin factory and obtain the expected parameters of the device to be replaced. After uploading the expected parameters to the device pre-selection device, the user can ignore the subsequent steps. The device pre-selection device will automatically match suitable products and further simulate the results of each filter by creating a digital twin factory copy. During the process of simulation or filtering, the supplier can still continuously construct new digital twin modules to facilitate the device pre-selection device to have more selectable objects. In other words, the present invention provides a supply and demand trading platform for suppliers and user factories based on digital twin technology. Compared with the prior art where technicians manually search in the product specifications provided by the supplier, this solution can better meet the actual needs of the factory at the practical operation level because the present application has found that even when the parameters are met, in the actual use process after installation, there will still be problems where the replaced device does not match the original requirements. This solution can well solve this problem.

[0013] When selecting equipment models, under certain special circumstances, considering the production line operation of their own factories, manufacturers may also have some special parameters that they specify and need to pay attention to. However, in the existing technology, when manufacturers provide product specifications or upload product specifications to online platforms, according to the standard factory process, only some necessary standard parameters will be tested and shown to the outside. In the case of querying from the specifications or platforms for model selection, the special parameters that manufacturers are concerned about cannot be shown. Therefore, when replacing equipment, a good comparison cannot be made, and only model selection can be carried out based on the standard parameters. To address this issue, the present invention proposes an optimal solution: after the user selects the object to be replaced through the user terminal, the user uploads the list of concerned parameters to the equipment pre-selection device; the equipment pre-selection device compares the list of concerned parameters with the standard parameter list attached to the filtered digital twin module, so as to obtain the parameters that do not correspond in the list of concerned parameters, and convert them into a special parameter list to provide to the supplier side corresponding to the digital twin module; after receiving the special parameter list, the supplier can arrange technical tests related to the special parameters to obtain the specific values of the special parameters; the supplier side uploads the specific values of the special parameters to the central server; the central server performs subsequent simulation work based on the updated parameters (the historical standard parameter list combined with the updated special parameter list). This solution can automatically send a request for supplementary parameters to the supplier side by the equipment pre-selection device for the parameters specifically concerned by the user. In other words, it can screen the equipment that can provide relevant special parameters and better meet the user's needs.

[0014] In another case, this solution also takes into account a problem, that is, both the manufacturer and the supplier may not pay attention to the problem of new parameters to be detected after equipment replacement. Taking the pump as an example, the existing technology believes that replacement can be carried out as long as the parameters meet the standards during replacement, and the standard parameters include head, power, etc. However, in the actual replacement process, for some production lines, the replaced equipment may require more parameter detection. For example, in a liquid transportation pipeline with a high viscosity, after replacing the pump equipment, the internal channels of the replaced equipment increase, but the inner diameter of each channel decreases. Although it meets the expected standards in terms of head, power, and unit transportation efficiency, the risk of pipe blockage increases, which is a situation that cannot be predicted by the manufacturer and the supplier. In response to this situation, the present invention also provides a preferred implementation manner. During the process of performing simulation by the equipment pre-selection device, a special parameter list to be concerned about is automatically formed based on the simulation process, and the special parameters are sent to both the supplier side and the user side. The supplier conducts technical tests based on the special parameter list and uploads the detection data to the equipment pre-selection device. The user considers changing the requirements or not based on the special parameter list. In the case where the user side selects not to change, the equipment pre-selection device removes the corresponding special parameters from the list. The way to automatically form the special parameter list can be that during the simulation process, the equipment pre-selection device analyzes the unexpected events encountered during the simulation process and forms special parameters. The recognition criteria for unexpected events can be that the simulated real-time parameters do not conform to the preset normal parameters, and rules such as the degree of non-conformity and the duration can be further set, which can be set by technicians. The above method realizes that when the equipment pre-selection device matches a suitable equipment selection according to the user's needs, new special parameters to be concerned about are spontaneously formed based on the simulation advantages of digital twin. This process does not require prior setting by the supplier and the user. Therefore, parameter items that neither party has considered can be found. In other words, the present invention can continuously update the selection criteria on the premise of meeting the user's needs, so as to find the equipment most suitable for the user from the supplier. In this case, the parameter range provided by the supplier can be relatively large, but as long as it is considered feasible after simulation, it can be recommended to the user, which can save a large amount of expenses for the user.

[0015] Preferably, within the set time at the user end, the device pre-selection device continuously screens for matching digital twin modules and conducts simulation. New digital twin modules can be formed at any time by the process data uploaded by the supplier to the device pre-selection device. In the prior art, attempts have been made to simulate equipment selection under different working conditions through digital simulation to improve the efficiency of equipment selection. For example, CN115982888A discloses a method, system, device, and storage medium for selecting a construction elevator system. When a configuration selection instruction is received, the selection requirement information of the construction elevator system and the type information of the construction elevator are obtained from the configuration selection instruction. Based on a preset calibration working condition set, a mechanical simulation model that meets the type information is selected. If the performance index of the initial digital prototype formed by the mechanical and electrical control coupling is optimal based on the mechanical simulation model, then based on the mechanical simulation model and the preset working conditions, a target simulation model that meets the selection requirement information is selected. The selection of the electromechanical control equipment corresponding to the target simulation model is used as the target selection of the construction elevator system. This technical solution simulates the operation of the construction elevator system under different working conditions through a digital prototype, replacing the actual performance of the construction elevator system and repeatedly adjusting the equipment model, thereby improving the selection efficiency of the construction elevator system. However, this technical solution can only simulate the simulation model based on the preset equipment information and cannot meet the process data change requirements of the supplier side. Based on technical means different from the above prior art, the technical problem to be solved by the present invention is how to provide corresponding customized digital twin components according to the specific parameter requirements of the user end. In many cases, the existing products provided by the supplier do not perfectly match the expected parameters initially set by the factory personnel because the parameters of the formed products are fixed and basically will not be changed after mass production. Therefore, the existing products cannot meet the expected parameters. The new digital twin modules of the present invention can be formed at any time by the process data uploaded by the supplier to the device pre-selection device, so as to provide the equipment closest to the expected parameters at the user end for replacement, thereby significantly improving the selection efficiency of different non-standard equipment.

[0016] Preferably, when the user needs to replace the equipment, the digital twin factory in the device pre-selection device is accessed through the user end. By selecting the equipment to be replaced, the device pre-selection device retrieves the working parameters of the equipment from the database and transmits them to the user end so that the user can determine the expected parameters based on the working parameters.

[0017] Preferably, when the expected parameters are uploaded at the user end, the device pre-selection device performs the first screening based on the type of the equipment to be replaced. The device pre-selection device screens for digital twin modules in the database whose equipment types are the same as the equipment type to be replaced.

[0018] Preferably, after the first screening is performed, the device pre-selection device performs a second screening based on a preset rule, and the preset rule is formulated based on the working parameters of the device to be replaced.

[0019] Preferably, the device pre-selection device performs a third screening on several digital twin modules screened out in the second screening. The third screening assigns a digital twin factory copy to each type of digital twin module. After the device to be replaced in the copy is replaced with a digital twin module, the device pre-selection device calculates the simulation parameters of the digital twin module based on the physical and chemical associations in the process.

[0020] Preferably, when replacing the digital twin module, the device pre-selection device replaces the model of the device to be replaced and simultaneously replaces the process parameters of the device to be replaced with the process parameters of the digital twin module.

[0021] Preferably, when constructing the copy, the device pre-selection device makes a backup based on the associated part where the device to be replaced is located to form the copy.

[0022] The present invention also provides a device selection method using digital twin technology, including: establishing a digital twin of the factory based on the physical factory, that is, a digital twin factory; obtaining the working parameters of the device to be replaced from the digital twin factory; determining the expected parameters of a replaced device based on the working parameters; inputting the expected parameters into the digital twin factory for automatic selection; performing a simulation test on the selected device; monitoring the simulation process and comparing and analyzing the design data with the real-time data; and outputting an optimized selection result to the user.

[0023] Preferably, "obtaining the working parameters of the device to be replaced from the digital twin factory" is to use the established digital twin factory database, select the device to be replaced from it, and the database automatically queries various information about the device and displays it as working parameters to the technical personnel. Description of the Drawings

[0024] Figure 1 is a schematic diagram of the system process provided by the present invention;

[0025] Figure 2 is a schematic diagram of the input and output of the twin factory stored in the device pre-selection device of the present invention;

[0026] Figure 3 is a schematic diagram of the process of the selection method of the present invention;

[0027] Figure 4 is a schematic diagram of the steps of the device selection method based on digital twin technology using the device pre-selection device of the present invention;

[0028] Figure 5 is a schematic diagram of the sub-steps of the "pre-" selection device simulation test step of the present invention. DETAILED DESCRIPTION

[0029] The following is combined with Figures 1 to 5 Provide detailed explanation.

[0030] At present, when factories select equipment, they need to go through a lot of preliminary preparation work. The technicians need to first investigate the various data of the equipment to be replaced in the factory, and based on the current expected production goals of the factory, consider the expected parameters of the new equipment to be replaced by comprehensive parameters. Based on the expected parameters, find the types that meet the requirements in the information of each manufacturer providing the equipment. After finding the types that may meet the requirements, you need to contact the person in charge of the manufacturer to obtain further technical information. This process is repeated until you can finally find the equipment that may meet the expected requirements. However, due to the low level of Internet in the field of factory equipment supply and demand, it is difficult to find more optional equipment information on the Internet. At present, most suppliers still provide their own products by printing product catalogs or product specifications and then manually distributing catalogs to factories that may have needs. This is an inefficient method for both suppliers and factories with needs. In addition, the factory is not able to take into account as many supplier products as possible. On the one hand, it is because they do not know that there is such a product, and on the other hand, it comes from the unfamiliarity with new products and new suppliers. In many cases, the existing products provided by suppliers do not perfectly match the expected parameters set by factory personnel at the beginning, because the parameters of the finished products are fixed and basically will not be changed after mass production. In the case of non-customization, most of the existing products are set conservatively in their own design parameters in order to meet a wider range of application scenarios, which may cause the existing products to fail to meet the expected parameters. At present, the factory technicians manually select the products provided by suppliers based on the expected parameters, with the aim of selecting the equipment closest to the expected parameters for replacement, which is undoubtedly a complex and inefficient task.

[0031] Based on this, the present invention provides an equipment selection system using digital twin technology. Figure 1As shown in the figure, the system includes a supplier side, a user side, and a device pre-selection device. The supplier side is accessed and used by suppliers. Suppliers upload supply data for constructing digital twin modules through the supplier side. The supplier points to the manufacturer that provides equipment to the factory. The user side is used by users, who are factories with equipment replacement needs and are usually consumers. The device pre-selection device provides a processing core for information interaction and intermediate data processing and calculation between suppliers and users, and is equipped with a digital twin construction program and a database. The user side collaborates with the device pre-selection device to establish a digital twin factory based on the user's own factory facilities. When the user determines the equipment to be replaced, in response to the user specifying the equipment to be replaced in the digital twin factory model displayed on the user side, the device pre-selection device retrieves the working parameters related to the equipment from the database and displays them to the user through the user side. The user determines the expected parameters of the equipment to be replaced based on their own needs and the working parameters of the existing equipment to be replaced. The user side uploads the input expected parameters to the device pre-selection device, and the device pre-selection device starts the selection process based on the expected parameters.

[0032] The device pre-selection device is a device with data processing and calculation capabilities. Preferably, it can at least meet the throughput, storage, and calculation processing of a large amount of data. Preferably, the device pre-selection device at least includes a processor (CPU), a storage (ROM, RAM, hard disk, disk, etc. for temporarily and permanently storing data), and a data interface. The data interface can be a hardware structure such as a data line network interface or a wireless network interface. The data interface is used to establish a communication connection with the supplier side and the user side. Preferably, the device pre-selection device has multiple data interfaces to facilitate establishing communication connections with multiple supplier sides and multiple user sides. The processor is used to perform a large amount of calculation and data interaction processing. In this solution, the main work of the processor is to establish a digital twin and simulate and match suitable equipment based on the digital twin and the requirements uploaded by the user side (i.e., complete the pre-selection work). Therefore, the processor in this solution can be composed of multiple processing chips and can have distributed computing and processing capabilities to handle the simultaneous processing of a large amount of data. The storage can be a large storage device formed by combining multiple data storage units, and is particularly preferably a database computer room, which can store a large amount of data. The device pre-selection device is equipped with a digital twin establishment program, which can construct a digital twin model of the factory in the virtual space based on the collected three-dimensional data of the factory site.

[0033] As Figure 4 shown, based on the device pre-selection device given in this solution, a device selection method using digital twin technology is provided, including the following content:

[0034] S1 Establish a digital twin of the factory based on the physical factory;

[0035] S2 obtains the working parameters of the expected replacement device from the digital twin factory;

[0036] S3 determines the working parameters of a replaced device based on the working parameters;

[0037] S4 inputs the expected parameters into the digital twin factory for automatic "pre"-selection;

[0038] S5 conducts simulation tests on at least one device selected through "pre"-selection;

[0039] S6 monitors the simulation process and compares and analyzes the design data with the real-time data;

[0040] S7 outputs the optimized selection result to the user.

[0041] Specifically, in S1, the digital twin of the factory is established based on the physical factory: based on the three-dimensional data of the factory collected on-site, it is uploaded to the device pre-selection device. The device pre-selection device constructs the digital twin of the factory based on the digital twin algorithm carried and the three-dimensional data. Digital twin means constructing a model in the virtual three-dimensional space that completely corresponds to the real object. Here, the correspondence does not only refer to the same structure on the model, but also the process of three-dimensionally constructing the structure parameters and process parameters of each device and each sub-structure in the factory, so that the three-dimensional digital twin can simulate the physical factory at a more detailed level. The way to collect the three-dimensional data of the physical factory can be to use a three-dimensional laser scanning tool to collect the three-dimensional data of various parts of the factory on-site. The laser scanning tool can emit lasers around, and record the spatial position of the laser contact points in three dimensions after the lasers return (the position of the tool itself is known, and the three-dimensional coordinates of the contact points can be obtained through coordinate calculation). By obtaining a large amount of three-dimensional data of all positions in the factory, the model of the factory can be restored by combining the three-dimensional data in the virtual space, and the accuracy can be as small as the smallest device level. Subsequently, each device in the formed three-dimensional digital twin is marked and classified to distinguish each component and sub-component in the digital twin. Subsequently, by inputting the parameters of each device in the factory (which can include structure parameters and working parameters, etc.) into the device pre-selection device, the construction of the digital twin is completed based on the binding of the parameters to the components and sub-components.

[0042] The specific process of obtaining the working parameters of the expected replacement device from the digital twin factory in S2 is as follows: The user of the factory accesses the digital twin factory in the device pre-selection device (i.e., the above digital twin) through the user terminal, and selects the expected replacement device in a 3D browsing manner. The user terminal has at least one display device and one input device. The display device is used to display the 3D digital twin factory model in the device pre-selection device, and the input device is used to control operations such as switching and zooming of the display perspective, and is also used to input selected instructions. By selecting the target device to be replaced on the user terminal (which can be reminded by highlighting the edge contour of the device), the device pre-selection device automatically retrieves the data related to the selected device from the database, which can be all the data. This data can include the structural parameters and working parameters of the device (these parameters have been input into the model and stored in the memory when building the twin factory), the updated parameters during the operation of the device (parameters updated to the device pre-selection device after establishing the twin factory), etc. These data are presented as replacement references to the factory personnel using the user terminal. The selection of the target device to be replaced and the receipt of the presented data on the user terminal can be completed within the device pre-selection device. The user terminal only needs to undertake the result display function, so the configuration cost and computing pressure of the user terminal can be reduced to a certain extent. The user terminal can be simply configured as a computer. The way of presenting this data can be in the 3D perspective of the user terminal, where the data is attached near or on the expected replacement device in the form of a 2D table or text box.

[0043] In S3, based on the data obtained from the user terminal, the factory personnel determine the working parameters of the replaced device. The determination method can be to determine the expected parameters of the replaced device based on the needs of their own factory. These expected parameters can be input into the user terminal in the form of a parameter table and uploaded to the device pre-selection device by the user terminal. The table can include parameter items and parameter set values.

[0044] In S4, the user terminal uploads expected parameters to the device pre-selection device. The user terminal establishes a communication connection with the pre-selection device through the above data interface and uploads the expected parameters to it. Preferably, when the user terminal displays data to factory personnel (see S2), the factory personnel can be given a modification channel to modify the values in the displayed data. For example, by selecting a certain item in the data (such as by clicking with the cursor), the value box of this item becomes editable, so that the parameter data can be changed by entering a value into the value box. Preferably, at least in response to the input of some parameters, the device pre-selection device can intuitively change the display mode of the target device in the digital twin factory to show the factory personnel the result after changing the parameters. For example, if the size parameter is modified in the uploaded expected parameters, the existing device model can be deformed in a stretching, magnifying, etc. manner and displayed to the factory personnel through the user terminal. At the same time, the original device model can be displayed in the form of a highlighted contour line for easy observation and comparison. The purpose of this step is to assist in the decision-making of some expected parameters, such as determining the size data by observing whether the updated size is appropriate.

[0045] After the expected parameters are input, the device pre-selection device conducts multiple screenings to obtain the "pre"-selected devices. First, the first screening is based on the selected expected replacement device type. The selected expected device type is known, and it is used as a retrieval marker to retrieve a large number of digital twin modules in the database. The digital twin module is made from the data uploaded by the supplier side. Specifically, the supplier side uploads various parameters of the product to the device pre-selection device based on the products it provides. These parameters include the three-dimensional data, process parameters, etc. of the device. The device pre-selection device also processes these data into digital twin modules using the digital twin algorithm based on the uploaded parameters. The digital twin module can be regarded as the digital twin version of the product, with the same three-dimensional size structure and process parameters. During the first screening, the digital twin module has a retrievable marker, such as a marker divided by device type. Through the expected replacement device type, the corresponding group of digital twin modules can be retrieved. After the first screening, the device pre-selection device performs a second screening based on the preset matching rules uploaded by the user side to narrow down the selectable range of the digital twin modules. The preset matching rules can be specified by the factory personnel on the user side, and its main purpose is to match at least the digital twin modules that can meet the expected parameters. Such a rule can be that the process parameters of the digital twin module are equal to or exceed the expected parameters. What is meant by exceeding the expected parameters is that the process parameters of the digital twin module have redundancy in addition to meeting the expected parameters. Through the above second screening, the number of selectable digital twin modules can be further reduced, and the selected digital twin modules are all digital twin modules that "meet the preset rules according to the comparison of the expected parameters". According to the general existing technology, when the program reaches this step, it is already close to the end, and then only the screening results need to be output to the user, because the devices that "on paper" can meet the factory's expected parameters have been found. However, this solution finds that for many products, even if the paper parameters are met, they cannot be used normally after actual installation, and there are "errors". And it is too costly to try and error through actual installation. The factory cannot bear the losses caused by purchasing, replacing, downtime due to replacement, and downtime due to the inability to use the replaced equipment. Therefore, how to perfectly select the equipment that will not have problems after actual installation during the selection phase is a problem that needs to be studied. Therefore, this solution gives a third screening, that is, step S5.

[0046] As Figure 5 shown, step S5 further includes the following contents:

[0047] S5.1 Input the parameters of multiple "pre"-selected devices into the digital twin of the factory;

[0048] S5.2 In the digital twin of the factory, perform simulation of the upstream and downstream of the production line associated with each "pre"-selected device;

[0049] S5.3 Output the results of the simulation of the upstream and downstream of the production line related to each "pre-selected" device according to at least one sorting method;

[0050] S5.4 Provide at least one order of selection suggestions for the selection results according to the sorting order of the production line simulation results and based on the simulation test results of each "pre-selected" device itself

[0051] In S5.1, the device pre-selection device assigns a copy of the digital twin factory to each digital twin model after the second screening, and replaces the target replacement device in the digital twin factory copy with the "pre-selected" device (digital twin module). This replacement includes model replacement and process parameter replacement. Model replacement means replacing the corresponding device model, and process parameter replacement means replacing the process parameters of the target device with the process parameters of the digital twin module. The replacement of process parameters mainly plays a role in the process of simulating the upstream and downstream, because the process is closely related to the upstream and downstream.

[0052] In S5.2, "perform the simulation of the upstream and downstream of the production line related to each 'pre-selected' device" means that the device pre-selection device, based on the built-in process simulation calculation model, after replacing the process parameters of the target device with the process parameters of the digital twin module, simulates the process changes of the upstream and downstream associated devices of the device. This simulation calculation model can be pre-input, belongs to a big data calculation model, and has professionalism. Taking a chemical plant as an example, it may involve multiple disciplines such as fluidics, chemistry, physics, and mechanical engineering. By integrating the opinions of experienced personnel and experts in the factory, the corresponding simulation calculation model can be compiled. There are also some basic models in the prior art that can be used as raw materials for obtaining the simulation calculation model. At least one simulation result regarding the upstream and downstream is output through the simulation.

[0053] Preferably, in step S5.3, the simulation result is related to process stability. The so-called process stability refers to the degree to which the parameters of the upstream and downstream after replacing the digital twin module exceed the expected threshold compared with the parameters before replacement. The more they exceed (for example, counted by the number of exceeded items and the exceeded values), the worse the process stability. After performing the simulation of the upstream and downstream for multiple digital twin modules, they can be sorted according to the simulation results of process stability, for example. The purpose of this solution is to simulate the upstream and downstream of the replaced device to determine whether its upstream and downstream processes will be affected after actually replacing the device. If the upstream and downstream process lines are affected (this does not refer to the changes generated by the replaced device itself), it can effectively find the incorrect digital twin module in the virtual space in the early stage.

[0054] In S5.4, simulation is also carried out for the digital twin module itself. This simulation is also carried out through a preset simulation model, and preferably, model-level simulation is also carried out based on the size data of the digital twin module. This model-level simulation can be to determine whether there is model overlap between the size of the digital twin module and other models. If there is, it means that it is not suitable in terms of size. For example, sorting in a way that is more in line with the process stability and the size of the digital twin module itself can output a recommended sequence of digital twin modules.

[0055] In S6, the DCS real-time monitoring system can be used to monitor the simulation process. This system is associated with the digital twin factory as a plugin and can compare and analyze the expected data with the simulation parameters of the real-time simulation. Fault analysis and warning can be carried out in the case of data differences. At the same time, it can also be used in combination with the material management system to preferentially recommend the equipment existing in the material management system to consume the inventory.

[0056] In S7, the results are displayed to the user. The displayed sorting can be input by the user terminal to the equipment pre-selection device, or a selection list can be provided. By changing the key of the selection list, the sorting with the corresponding key value will be automatically arranged.

[0057] It should be noted that the above specific embodiments are exemplary. Those skilled in the art can come up with various solutions inspired by the disclosed content of the present invention, and these solutions also fall within the scope of the disclosure of the present invention and within the protection scope of the present invention. Those skilled in the art should understand that the description and drawings of the present invention are illustrative and do not constitute a limitation on the claims. The protection scope of the present invention is defined by the claims and their equivalents. The description of the present invention contains multiple inventive concepts. For example, "preferably", "according to a preferred embodiment" or "optionally" all indicate that a corresponding paragraph discloses an independent concept. The applicant reserves the right to file divisional applications according to each inventive concept. Throughout the text, the features guided by "preferably" are only an optional way and should not be understood as must be set. Therefore, the applicant reserves the right to abandon or delete the relevant preferred features at any time.

Claims

1. An equipment selection system using digital twin technology, comprising: The client used by the factory, the supplier side used by the supplier, and the device pre-selection device for data interconnection between the client and the supplier side It is characterized in that The client collaborates with the device pre-selection device to build a digital twin factory of the user's factory, and the supplier side uploads process data for building digital twin modules to the device pre-selection device When the user needs to replace the device, access the digital twin factory in the device pre-selection device through the client. By selecting the device to be replaced, the device pre-selection device retrieves the working parameters of the device from the database and transmits them to the client, so that the user can determine the expected parameters of the replaced device based on the working parameters. The client provides the expected parameters of the replaced device to the device pre-selection device. The device pre-selection device filters the digital twin modules made from the data uploaded by the supplier side based on the expected parameters. The device pre-selection device assigns a digital twin factory copy to each filtered digital twin module. The device pre-selection device replaces the device to be replaced in each digital twin factory copy with a digital twin module and performs a simulation. The device pre-selection device outputs the simulation parameters obtained from the simulation to the client, so that the user can select the desired product through the client When the client uploads the expected parameters, the device pre-selection device performs a first screening based on the type of the device to be replaced. The device pre-selection device filters digital twin modules with the same device type as the device to be replaced from the database After performing the first screening, the device pre-selection device performs a second screening based on preset rules to filter digital twin modules that meet the expected parameters. The preset rules are formulated based on the expected parameters The device pre-selection device performs a third screening for several digital twin modules screened in the second screening. The third screening assigns a digital twin factory copy to each digital twin module. After the device pre-selection device replaces the device to be replaced in the copy with a digital twin module, it calculates the simulation parameters of the digital twin module based on the physical and chemical correlations in the process. When replacing the digital twin module, the device pre-selection device replaces the model of the device to be replaced and replaces the process parameters of the device to be replaced with the process parameters of the digital twin module 2. The system according to claim 1, wherein Within the time set by the client, the device pre-selection device continuously filters eligible digital twin modules and performs simulations. New digital twin modules can be constructed at any time from the process data uploaded by the supplier side to the device pre-selection device 3. The system according to claim 1, characterized in that, When building the copy, the device pre-selection device makes a backup based on the associated part where the device to be replaced is located to form a copy 4. A device selection method using digital twin technology, characterized in that The method adopts the equipment selection system with the aid of digital twin technology as described in any one of claims 1 to 3, including: establishing a digital twin of the factory based on the physical factory, namely the digital twin factory; obtaining the working parameters of the equipment to be replaced from the digital twin factory; determining the expected parameters of a replaced equipment based on the working parameters; screening digital twin modules based on the expected parameters, allocating a digital twin factory copy to each screened digital twin module based on the screening results, and replacing the equipment to be replaced in each digital twin factory copy with the digital twin module for automatic selection; conducting simulation tests on the selected equipment; monitoring the simulation process, comparing and analyzing the design data with the real-time data; and outputting the optimized selection result to the user.

5. The method according to claim 4, wherein The obtaining of the working parameters of the equipment to be replaced from the digital twin factory is to utilize the already established digital twin factory database, select the equipment to be replaced from it, and the database automatically queries various information about the equipment and displays it as the working parameters to the technicians.

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