Automobile parts inventory management system and method based on digital twinning

Abstract

The application provides a kind of based on digital twinning automobile accessory inventory management system and method, it is related to inventory management technical field.The method includes obtaining historical inventory supply and demand change data, the digital twinning of accessory inventory change model is carried out, and the digital twinning model of accessory inventory management is established;Real-time accessory demand information is collected, and based on the production supply of accessory inventory management digital twinning model, inventory optimization analysis is carried out, and inventory management optimization analysis data is formed;According to inventory management optimization analysis data, the digital twinning model of accessory inventory management is optimized and adjusted, and the accessory inventory optimization management model is formed.The method establishes a reasonable accessory inventory management model by using digital twinning technology, and then realizes the reasonable management of accessory inventory, ensures that accessories meet the demand in time, and also can reasonably control inventory cost.

Description

[0001] This application is a divisional application of the invention application filed on March 4, 2025, with Chinese application number 202510248002.0 and entitled "A Method and System for Inventory Management of Automotive Parts Based on Digital Twin". Technical Field

[0002] This invention relates to the field of inventory management technology, and more specifically, to an automotive parts inventory management system and method based on digital twins. Background Technology

[0003] With societal development, more and more people are using cars as a means of transportation, leading to a year-on-year increase in vehicle ownership. Consequently, the demand for after-sales maintenance and repairs is also rising, resulting in a corresponding increase in the demand for auto parts. Currently, the supply of auto parts mainly relies on dealers or repair shops submitting different parts requests to parts supply platforms through a demand system. The platforms then centrally procure and distribute the parts. Therefore, to ensure timely and sufficient supply of parts to dealers and repair shops, the platforms establish inventory systems to manage parts supply.

[0004] Currently, the management of spare parts inventory mainly relies on traditional on-demand procurement and forecast assessment. This makes it difficult to match the procurement volume of different spare parts with the demand, which often leads to shortages or excessive inventory. This has a negative impact on the platform's cost management and inventory management.

[0005] Therefore, designing a digital twin-based automotive parts inventory management method and system, and establishing a reasonable parts inventory management model by utilizing digital twin technology, to achieve reasonable management of parts inventory, ensuring that parts meet demand in a timely manner while also reasonably controlling inventory costs, is an urgent problem to be solved. Summary of the Invention

[0006] The purpose of this invention is to provide a digital twin-based method for managing automotive parts inventory. By combining historical inventory supply and demand change data to create a digital twin, a digital twin model for parts inventory management is established. Based on the data twin model, reasonable inventory optimization and adjustment are performed according to real-time parts demand. This ensures that the inventory level can meet the needs of the demand side in a timely manner, while avoiding unreasonable inventory backlog that leads to low inventory space utilization and adverse effects on inventory cost control.

[0007] The present invention also aims to provide an automotive parts inventory management system based on digital twins. This system is configured to utilize historical inventory supply and demand change data to create digital twins and use the digital twin model to reasonably optimize and control the current inventory level. It can effectively ensure efficient and reasonable inventory management and is an important infrastructure for achieving a better inventory management method.

[0008] In a first aspect, the present invention provides a digital twin-based method for managing automotive parts inventory, comprising: acquiring historical inventory supply and demand change data, creating a digital twin of the parts inventory change model, and establishing a parts inventory management digital twin model; collecting real-time parts demand information, and performing inventory optimization analysis based on production supply according to the parts inventory management digital twin model to form inventory management optimization analysis data; and optimizing and adjusting the parts inventory management digital twin model according to the inventory management optimization analysis data to form a parts inventory optimization management model.

[0009] In this invention, the method establishes a digital twin model for spare parts inventory management by combining historical inventory supply and demand change data to create a digital twin. Then, based on the data twin model, reasonable inventory optimization and adjustment are made according to real-time spare parts demand. This ensures that the spare parts inventory can meet the needs of the demand side in a timely manner, and also avoids the low inventory space utilization and adverse effects on inventory cost control caused by unreasonable inventory backlog.

[0010] One possible approach is to acquire historical inventory supply and demand change data, create a digital twin of the spare parts inventory change model, and establish a digital twin model for spare parts inventory management. This includes: acquiring historical inventory supply and demand change data, performing supply and demand consistency analysis to form consistent supply and demand change data; and based on the consistent supply and demand change data, creating a digital twin of the spare parts inventory change model to establish a digital twin model for spare parts inventory management.

[0011] In this invention, to establish a reasonable digital twin model for spare parts inventory management, it is first necessary to determine whether historical inventory supply and demand change data accurately reflects the matching relationship between inventory supply and spare parts demand. Therefore, it is essential to extract inventory change data and demand change data separately for consistency analysis. Through consistency analysis, the matching degree between inventory change data and demand change data is verified, and data that cannot be reasonably matched is adjusted to ensure that the data can truly reflect the supply and demand changes.

[0012] One possible approach is to acquire historical inventory supply and demand change data, perform supply and demand consistency analysis, and generate consistent supply and demand change data. This includes: extracting the historical inventory change relationship F for different components within the analysis period based on the historical inventory supply and demand change data. n(t), where n represents the serial number of different parts; based on historical inventory supply and demand data, extract the historical demand relationship of different demanders for different parts within the analysis period. m represents the number of different demanders; based on different demands, different parts are assigned to different parts according to their historical demand changes. The historical demand variation relationship H for different components was determined separately. n (t), where, Based on the historical inventory change relationship of different parts F n (t) and the relationship between the historical demand changes of different accessories H n (t) is used to perform supply and demand consistency analysis and generate consistent supply and demand change data.

[0013] In this invention, for consistency analysis, it is understood that the demand for components and inventory changes based on industry operating patterns exhibit a certain periodicity. Therefore, when conducting consistency analysis, this periodicity can be used as the time frame for analysis, reflecting the supply and demand matching relationship throughout the entire cycle. Of course, since the demand for different components varies, the consistency analysis is also based on the type of component, judging the matching of supply and demand change data for different components separately.

[0014] As one possible implementation method, based on the historical inventory change relationship F of different parts. n (t) and the relationship between the historical demand changes of different accessories H n (t), perform supply and demand consistency analysis to generate consistent supply and demand change data, including: for different components, based on the corresponding historical inventory change relationship F of the components. n The relationship between (t) and the corresponding historical demand changes for accessories H n (t), continuous integration is performed within the analysis period, and the following comparative analysis is conducted: If Then do not consider the historical inventory change relationship of parts F n (t) is adjusted, where T con Indicates that in [0, T all Any duration within the range, T all α represents the total duration of the analysis period. n This represents the supply-demand deviation threshold corresponding to accessory number n; if Based on the historical demand changes of parts, H n (t), determine the consistency adjustment function U n (t), where U n (t)=H n (t)-a, and the consistency adjustment function U n (t) satisfies 'a' represents the consistency adjustment coefficient; the consistency adjustment function U is used. n (t) Historical inventory changes of replacement parts F n The original change relationship of (t) forms a new historical inventory change relationship F for spare parts. n (t).

[0015] In this invention, the ideal supply-demand matching relationship should be that inventory levels change synchronously with changes in demand. Considering that determining inventory levels in practice also involves spare parts, production cycles, etc., there will be some discrepancies between changes in inventory levels and changes in demand. If these discrepancies are reasonable and acceptable, they fall within the scope of supply-demand matching consistency. However, if inventory changes and demand changes are mismatched, the discrepancy will increase. Therefore, it is reasonable to use a reasonable discrepancy threshold for different parts to analyze the consistency of supply-demand relationships. The supply-demand deviation threshold can be set based on actual conditions or determined based on big data analysis. If the discrepancy does not exceed the supply-demand deviation threshold, it can be determined that inventory changes and demand changes are synchronously matched. If the discrepancy exceeds the supply-demand deviation threshold, it is considered that there is some interference in inventory changes, and the matching degree needs to be adjusted. Here, by using the supply-demand deviation threshold as a reference and the rate of change in inventory levels as a guide, a new inventory change is adjusted, that is, the inventory level is reasonably increased or decreased over time to ensure that the cumulative discrepancy over the entire cycle can only reach the supply-demand deviation threshold at most.

[0016] As one possible approach, a digital twin model of spare parts inventory change is created based on consistent supply and demand change data. This model includes: creating a digital twin of spare parts inventory change based on consistent supply and demand change data, with the analysis period as the time span, and following the time dimension to establish a digital twin model of spare parts inventory management.

[0017] In this invention, after obtaining reasonable and accurate supply and demand change data, a data twin model of parts inventory management can be established in the time dimension to reflect the relationship between inventory supply and demand changes more clearly.

[0018] One possible approach is to collect real-time parts demand information and, based on a digital twin model of parts inventory management, perform inventory optimization analysis based on production supply to generate inventory management optimization analysis data. This includes: collecting real-time parts demand information, extracting demand information for different parts to generate real-time parts demand change data; and performing inventory optimization analysis based on the real-time parts demand change data and the digital twin model of parts inventory management to generate inventory management optimization analysis data.

[0019] In this invention, the data twin model for spare parts inventory management can analyze the matching of current spare parts demand with inventory levels. This matching is determined by using supply and demand change data provided by the digital twin model to ascertain whether the current inventory level meets demand and ensures reasonable cost control.

[0020] One possible implementation involves collecting real-time parts demand information, extracting demand information for different parts, and forming real-time parts demand change data. This includes: based on the real-time parts demand information, extracting the real-time demand change relationships of different parts from different demanders within the real-time analysis period. Based on the real-time demand changes of the same object's accessories for different demanders Determine the relationship between the total demand V for different components. n (t), where,

[0021] In this invention, it should be noted that, since the collection of real-time parts demand information is within a relatively short analysis period, but since the changes in parts inventory and demand exhibit obvious time characteristics, it is necessary to establish supply and demand change data for the corresponding time period when extracting real-time parts demand changes, so as to provide a reasonable and correct reference for subsequent comparative analysis of data for the corresponding time period using a digital twin model.

[0022] As one possible implementation, inventory optimization analysis is performed based on real-time spare parts demand change data and a spare parts inventory management digital twin model. This results in inventory management optimization analysis data, including: extracting the model mapping spare parts inventory change relationship W for different spare parts in the time period corresponding to the real-time analysis cycle based on the spare parts inventory management digital twin model. n (t); For different components, based on the corresponding total demand variation relationship V of the components. n (t) and the model mapping relationship of parts inventory changes W n (t) Perform inventory optimization analysis to generate inventory optimization information for different parts; combine the inventory optimization information for different parts to generate inventory management optimization analysis data.

[0023] In this invention, to optimize and adjust inventory levels based on real-time demand changes in spare parts data, it is also necessary to utilize the supply and demand relationship of the digital twin model to determine whether inventory management should still follow the supply and demand relationship of the digital twin model under actual demand conditions. Here, to ensure the comparability of the matching relationship data extracted from the digital twin model, relationship data within the corresponding time period is selected during data extraction, thereby ensuring the accuracy of the matching and comparison analysis.

[0024] As one possible implementation, for different components, the total demand V for those components is adjusted accordingly. n (t) and the model mapping relationship of parts inventory changes W n (t) Perform inventory optimization analysis to generate inventory optimization information for different components, including: for different components, based on the relationship between the total demand for those components and V. n (t) and the model mapping relationship of parts inventory changes W n (t), perform the following analysis: If Max[W] n (t)]≤Min[V n If (t)], then the current inventory of spare parts remains unchanged, where Max[W n [t] represents the extracted model mapping relationship of parts inventory changes W. n (t) is the maximum value within the real-time analysis period, Min[V] n [t] represents the relationship between the total demand for extracted components and the change in V. n (t) is the minimum value within the real-time analysis period; if Max[W] is the minimum value within the real-time analysis period; n (t)]>Min[V n [(t)], and Then determine the real-time change rate R of the parts. n And based on the real-time change rate R of the parts n Determine the inventory change rate F′ at the corresponding time point. n (t)-R n , where β n This represents the real-time analysis bias threshold corresponding to accessory number n, and β n ≥0, F′ n (t) represents the historical inventory change relationship of parts. n (t) is the first derivative with respect to time, T cur E represents any duration within the real-time analysis period. n (t) represents the relationship between the total demand for spare parts and the change in W. n (t) and the model mapping relationship of parts inventory changes W n (t) is the difference at the corresponding time point; if Max[W n (t)]>Min[V n [(t)], and Then determine the real-time change rate R of the parts. n And based on the real-time change rate R of the parts n Determine the inventory change rate F′ at the corresponding time point. n (t)+R n If Max[W] n (t)]>Min[V n [(t)], and This results in the information that the current inventory of spare parts remains unchanged.

[0025] In this invention, if the real-time spare parts demand is compatible with the supply and demand matching data in the digital twin model, then the quantity of spare parts demand and the inventory change relationship within the real-time analysis period are synergistic in both quantity and change. For the synergy in quantity, a direct way to determine this is by the potential overlap between the real-time spare parts demand and the inventory demand. This is determined by comparing the maximum real-time spare parts demand with the minimum inventory supply and demand relationship provided by the digital twin model. When the maximum real-time spare parts demand does not exceed the minimum inventory supply and demand relationship provided by the digital twin model, it can be considered that the current inventory is sufficient to meet the real-time spare parts demand, and there is no need to increase the spare parts inventory based on the supply and demand relationship of the digital twin model in the short term. Conversely, when the maximum real-time spare parts demand is greater than the minimum inventory supply and demand relationship provided by the digital twin model, it can be considered that the real-time spare parts demand may match the inventory supply and demand relationship provided by the digital twin model in terms of quantity. Therefore, the difference between the two relationships is used to determine whether to adjust the inventory change relationship. If the difference between real-time spare parts demand and the inventory level provided by the digital twin model shows a continuous change exceeding the judgment threshold, it indicates that the inventory level is changing too much and needs to be reduced. Inventory levels should be controlled by adjusting the rate of change. If the difference between real-time spare parts demand and the inventory level provided by the digital twin model shows a continuous change but does not exceed the judgment threshold, it indicates that the inventory level is not changing significantly, the current inventory is controllable, and no reduction is needed; maintaining the original inventory supply level is sufficient.

[0026] Secondly, this invention provides an automotive parts inventory management system based on digital twins, comprising: a data acquisition unit for collecting historical inventory supply and demand change data; a digital twin unit for acquiring the historical inventory supply and demand change data collected by the data acquisition unit, performing a digital twin of the parts inventory change model, and establishing a parts inventory management digital twin model; and an optimization analysis unit for collecting real-time parts demand information and performing inventory optimization analysis based on production supply according to the parts inventory management digital twin model, thereby generating inventory management optimization analysis data.

[0027] In this invention, the system is configured to create a complete system that can use historical inventory supply and demand change data to generate a digital twin and use the digital twin model to reasonably optimize and control the current inventory level. This system can effectively ensure efficient and reasonable inventory management and is an important infrastructure for achieving a better inventory management approach.

[0028] The beneficial effects of the digital twin-based automotive parts inventory management method and system provided by this invention are as follows:

[0029] This method establishes a digital twin model for spare parts inventory management by combining historical inventory supply and demand change data to create a digital twin. Based on the data twin model, reasonable inventory optimization and adjustment are made according to real-time spare parts demand. This ensures that the spare parts inventory can meet the needs of the demand side in a timely manner, while avoiding unreasonable inventory backlog that leads to low inventory space utilization and adverse effects on inventory cost control.

[0030] This system, configured to utilize historical inventory supply and demand data to create a digital twin and then use that digital twin model to optimize and control current inventory levels, effectively ensures efficient and rational inventory management. It is a crucial infrastructure for achieving superior inventory management. Attached Figure Description

[0031] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 A flowchart illustrating the steps of a digital twin-based automotive parts inventory management method provided in an embodiment of the present invention;

[0033] Figure 2 A flowchart illustrating the inventory optimization analysis steps of the digital twin-based automotive parts inventory management method provided in this embodiment of the invention;

[0034] Figure 3 This is a schematic diagram of the structure of an automotive parts inventory management system based on digital twins, provided in an embodiment of the present invention. Detailed Implementation

[0035] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention.

[0036] With societal development, more and more people are using cars as a means of transportation, leading to a year-on-year increase in vehicle ownership. Consequently, the demand for after-sales maintenance and repairs is also rising, resulting in a corresponding increase in the demand for auto parts. Currently, the supply of auto parts mainly relies on dealers or repair shops submitting different parts requests to parts supply platforms through a demand system. The platforms then centrally procure and distribute the parts. Therefore, to ensure timely and sufficient supply of parts to dealers and repair shops, the platforms establish inventory systems to manage parts supply.

[0037] Currently, the management of spare parts inventory mainly relies on traditional on-demand procurement and forecast assessment. This makes it difficult to match the procurement volume of different spare parts with the demand, which often leads to shortages or excessive inventory. This has a negative impact on the platform's cost management and inventory management.

[0038] refer to Figures 1-3 This invention provides a digital twin-based method for managing automotive parts inventory. This method establishes a digital twin model for parts inventory management by combining historical inventory supply and demand change data. Based on the data twin model, reasonable inventory optimization and adjustment are performed for real-time parts demand. This ensures that the inventory level can meet the needs of the demand side in a timely manner, while avoiding unreasonable inventory backlog that leads to low inventory space utilization and adverse effects on inventory cost control.

[0039] The digital twin-based automotive parts inventory management method specifically includes the following steps:

[0040] S1: Obtain historical inventory supply and demand change data, create a digital twin of the spare parts inventory change model, and establish a digital twin model for spare parts inventory management.

[0041] To acquire historical inventory supply and demand change data, create a digital twin of the spare parts inventory change model, and establish a digital twin model for spare parts inventory management, the following steps are taken: acquire historical inventory supply and demand change data, conduct supply and demand consistency analysis to form consistent supply and demand change data; based on the consistent supply and demand change data, create a digital twin of the spare parts inventory change model, and establish a digital twin model for spare parts inventory management.

[0042] To establish a reasonable digital twin model for spare parts inventory management, it is first necessary to determine whether historical inventory supply and demand change data accurately reflects the matching relationship between inventory supply and spare parts demand. Therefore, it is essential to extract inventory change data and demand change data separately for consistency analysis. Consistency analysis verifies the matching degree between inventory change data and demand change data while adjusting any data that does not match properly, ensuring that the data accurately reflects changes in supply and demand.

[0043] Acquire historical inventory supply and demand change data, perform supply and demand consistency analysis, and generate consistent supply and demand change data, including: extracting the historical inventory change relationship F for different components within the analysis period based on the historical inventory supply and demand change data. n (t), where n represents the serial number of different parts; based on historical inventory supply and demand data, extract the historical demand relationship of different demanders for different parts within the analysis period. m represents the number of different demanders; based on different demands, different parts are assigned to different parts according to their historical demand changes. The historical demand variation relationship H for different components was determined separately. n (t), where, Based on the historical inventory change relationship of different parts F n (t) and the relationship between the historical demand changes of different accessories H n (t) is used to perform supply and demand consistency analysis and generate consistent supply and demand change data.

[0044] For consistency analysis, it's understandable that inventory changes exhibit a certain cyclicality based on component demand and industry operating patterns. Therefore, consistency analysis can use this cyclicality as the time frame for analysis, reflecting the supply and demand matching relationship throughout the entire cycle. Of course, since the demand for different components varies, consistency analysis also assesses the matching of supply and demand data for different components based on their type.

[0045] Based on the historical inventory change relationship of different parts F n (t) and the relationship between the historical demand changes of different accessories H n (t), perform supply and demand consistency analysis to generate consistent supply and demand change data, including: for different components, based on the corresponding historical inventory change relationship F of the components. n The relationship between (t) and the corresponding historical demand changes for accessories H n (t), continuous integration is performed within the analysis period, and the following comparative analysis is conducted: If Then do not consider the historical inventory change relationship of parts F n (t) is adjusted, where T con Indicates that in [0, T all Any duration within the range, T all α represents the total duration of the analysis period. n This represents the supply-demand deviation threshold corresponding to accessory number n; if Based on the historical demand changes of parts, H n (t), determine the consistency adjustment function U n (t), where U n (t)=H n (t)-a, and the consistency adjustment function U n (t) satisfies 'a' represents the consistency adjustment coefficient; the consistency adjustment function U is used. n (t) Historical inventory changes of replacement parts F n The original change relationship of (t) forms a new historical inventory change relationship F for spare parts. n (t).

[0046] Ideally, supply and demand should match inventory levels in sync with changes in demand. However, in practice, determining inventory levels involves factors like spare parts and production cycles, leading to discrepancies between inventory changes and demand fluctuations. Reasonable and acceptable discrepancies fall within the scope of supply-demand consistency. Conversely, mismatches between inventory and demand exacerbate these discrepancies. Therefore, establishing reasonable thresholds for different components to analyze supply-demand consistency is reasonable. These thresholds can be set based on actual conditions or determined through big data analysis. If the discrepancy does not exceed the threshold, inventory and demand changes are considered synchronously matched. If the discrepancy exceeds the threshold, inventory changes may be interfering, requiring adjustment. Here, using the supply-demand deviation threshold as a reference and the rate of inventory change as a guide, a new inventory change pattern is established. This involves reasonably increasing or decreasing inventory over time to ensure that the cumulative discrepancy over the entire cycle only reaches the supply-demand deviation threshold.

[0047] Based on consistent supply and demand change data, a digital twin model of spare parts inventory change is created, and a digital twin model of spare parts inventory management is established. This includes: based on consistent supply and demand change data, using the analysis period as the time span, and following the time dimension to create a digital twin of spare parts inventory change, and establishing a digital twin model of spare parts inventory management.

[0048] Once reasonable and accurate supply and demand change data are obtained, a data twin model of spare parts inventory management can be established in the time dimension to more clearly reflect the relationship between inventory supply and demand changes.

[0049] S2: Collect real-time parts demand information and, based on the parts inventory management digital twin model, conduct inventory optimization analysis based on production supply to generate inventory management optimization analysis data.

[0050] Collect real-time spare parts demand information and, based on the spare parts inventory management digital twin model, conduct inventory optimization analysis based on production supply to generate inventory management optimization analysis data. This includes: collecting real-time spare parts demand information, extracting demand information for different spare parts to generate real-time spare parts demand change data; and conducting inventory optimization analysis based on the real-time spare parts demand change data and the spare parts inventory management digital twin model to generate inventory management optimization analysis data.

[0051] A data twin model for spare parts inventory management can analyze the matching of current spare parts demand with inventory levels. This matching is achieved by using supply and demand change data provided by the digital twin model to determine whether the current inventory level meets demand while ensuring reasonable cost control.

[0052] Collect real-time spare parts demand information, extract demand information for different spare parts, and form real-time spare parts demand change data, including: extracting the real-time demand change relationship of different spare parts for different demanders within the real-time analysis period based on the real-time spare parts demand information. Based on the real-time demand changes of the same object's accessories for different demanders Determine the relationship between the total demand V for different components. n (t), where,

[0053] It should be noted that, since the collection of real-time spare parts demand information is within a relatively short analysis period, but because the changes in spare parts inventory and demand exhibit obvious time characteristics, it is necessary to establish supply and demand change data for the corresponding time period when extracting real-time spare parts demand changes. This will provide a reasonable and accurate reference for subsequent comparative analysis of data within the corresponding time period using a digital twin model.

[0054] Based on real-time spare parts demand change data and combined with a spare parts inventory management digital twin model, inventory optimization analysis is performed to generate inventory management optimization analysis data, including: extracting the model mapping spare parts inventory change relationship W for different spare parts in the time period corresponding to the real-time analysis cycle based on the spare parts inventory management digital twin model. n (t); For different components, based on the corresponding total demand variation relationship V of the components. n (t) and the model mapping relationship of parts inventory changes W n (t) Perform inventory optimization analysis to generate inventory optimization information for different parts; combine the inventory optimization information for different parts to generate inventory management optimization analysis data.

[0055] To optimize and adjust inventory levels based on real-time spare parts demand data, it's necessary to utilize the supply and demand relationship from a digital twin model. This determines whether inventory management should still follow the digital twin's supply and demand dynamics under actual demand conditions. Here, to ensure the comparability of the matching relationship data extracted from the digital twin model, relationship data from the corresponding time period is selected during data extraction, thereby guaranteeing the accuracy of the matching and comparison analysis.

[0056] For different components, the relationship V is based on the total demand variation of the corresponding components. n(t) and the model mapping relationship of parts inventory changes W n (t) Perform inventory optimization analysis to generate inventory optimization information for different components, including: for different components, based on the relationship between the total demand for those components and V. n (t) and the model mapping relationship of parts inventory changes W n (t), perform the following analysis: If Max[W] n (t)]≤Min[V n If (t)], then the current inventory of spare parts remains unchanged, where Max[W n [t] represents the extracted model mapping relationship of parts inventory changes W. n (t) is the maximum value within the real-time analysis period, Min[V] n [t] represents the relationship between the total demand for extracted components and the change in V. n (t) is the minimum value within the real-time analysis period; if Max[W] is the minimum value within the real-time analysis period; n (t)]>Min[V n [(t)], and Then determine the real-time change rate R of the parts. n And based on the real-time change rate R of the parts n Determine the inventory change rate F′ at the corresponding time point. n (t)-R n , where β n This represents the real-time analysis bias threshold corresponding to accessory number n, and β n ≥0, F′ n (t) represents the historical inventory change relationship of parts. n (t) is the first derivative with respect to time, T cur E represents any duration within the real-time analysis period. n (t) represents the relationship between the total demand for spare parts and V. n (t) and the model mapping relationship of parts inventory changes W n (t) is the difference at the corresponding time point; if Max[W n (t)]>Min[V n [(t)], and Then determine the real-time change rate R of the parts. n And based on the real-time change rate R of the parts n Determine the inventory change rate F′ at the corresponding time point. n (t)+R n If Max[W] n (t)]>Min[V n [(t)], and This results in the information that the current inventory of spare parts remains unchanged.

[0057] If real-time spare parts demand aligns with the supply and demand matching data in the digital twin model, then the quantity of spare parts demand and inventory changes will exhibit synergy in both quantity and change within the real-time analysis period. For quantity synergy, a direct way to determine this is by comparing the maximum real-time spare parts demand with the minimum inventory supply and demand relationship provided by the digital twin model. When the maximum real-time spare parts demand does not exceed the minimum inventory supply and demand relationship provided by the digital twin model, it can be assumed that the current inventory is sufficient to meet the real-time spare parts demand, and there is no need to increase the spare parts inventory based on the supply and demand relationship of the digital twin model in the short term. Conversely, when the maximum real-time spare parts demand exceeds the minimum inventory supply and demand relationship provided by the digital twin model, it can be assumed that the real-time spare parts demand may match the inventory supply and demand relationship provided by the digital twin model in terms of quantity. Therefore, the difference between the two relationships can be used to determine whether to adjust the inventory change relationship. If the difference between real-time spare parts demand and the inventory level provided by the digital twin model shows a continuous change exceeding the judgment threshold, it indicates that the inventory level is changing too much and needs to be reduced. Inventory levels should be controlled by adjusting the rate of change. If the difference between real-time spare parts demand and the inventory level provided by the digital twin model shows a continuous change but does not exceed the judgment threshold, it indicates that the inventory level is not changing significantly, the current inventory is controllable, and no reduction is needed; maintaining the original inventory supply level is sufficient.

[0058] S3: Optimize and adjust the digital twin model of parts inventory management based on inventory management optimization analysis data to form an optimized parts inventory management model.

[0059] Once the inventory management optimization analysis data is obtained, the supply and demand matching relationship of the digital twin model can be adjusted based on the data to ensure a reasonable inventory level.

[0060] The present invention also provides an automotive parts inventory management system based on digital twins. The system includes a data acquisition unit for collecting historical inventory supply and demand change data; a digital twin unit for acquiring the historical inventory supply and demand change data collected by the data acquisition unit, creating a digital twin of the parts inventory change model, and establishing a parts inventory management digital twin model; and an optimization analysis unit for collecting real-time parts demand information and performing inventory optimization analysis based on production supply according to the parts inventory management digital twin model, forming inventory management optimization analysis data.

[0061] This system, configured to utilize historical inventory supply and demand data to create a digital twin and then use that digital twin model to optimize and control current inventory levels, effectively ensures efficient and rational inventory management. It is a crucial infrastructure for achieving superior inventory management.

[0062] In summary, the beneficial effects of the digital twin-based automotive parts inventory management method and system provided in this invention are as follows:

[0063] This method establishes a digital twin model for spare parts inventory management by combining historical inventory supply and demand change data to create a digital twin. Based on the data twin model, reasonable inventory optimization and adjustment are made according to real-time spare parts demand. This ensures that the spare parts inventory can meet the needs of the demand side in a timely manner, while avoiding unreasonable inventory backlog that leads to low inventory space utilization and adverse effects on inventory cost control.

[0064] This system, configured to utilize historical inventory supply and demand data to create a digital twin and then use that digital twin model to optimize and control current inventory levels, effectively ensures efficient and rational inventory management. It is a crucial infrastructure for achieving superior inventory management.

[0065] In the embodiments of this application, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0066] In the description of the embodiments of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0067] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0068] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0069] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0070] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0071] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0072] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0073] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0074] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0075] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0076] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0077] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A digital-twin-based automobile parts inventory management method, characterized by, include: Obtain historical inventory supply and demand change data, create a digital twin of the spare parts inventory change model, and establish a digital twin model for spare parts inventory management; Collect real-time parts demand information, and based on the aforementioned parts inventory management digital twin model, conduct inventory optimization analysis based on production supply to generate inventory management optimization analysis data; The digital twin model of spare parts inventory management is optimized and adjusted based on the inventory management optimization analysis data to form a spare parts inventory optimization management model; The step of acquiring historical inventory supply and demand change data, creating a digital twin of the spare parts inventory change model, and establishing a digital twin model for spare parts inventory management includes: Acquire the historical inventory supply and demand change data, perform supply and demand consistency analysis, and generate consistent supply and demand change data; Based on the consistent supply and demand change data, a digital twin of the spare parts inventory change model is generated, and a digital twin model for spare parts inventory management is established. The step of acquiring the historical inventory supply and demand change data, performing supply and demand consistency analysis, and forming consistent supply and demand change data includes: According to the historical inventory supply and demand change data, the historical inventory change relationship of different accessories corresponding to the accessories in an analysis period is extracted , n represents the number of different accessories; According to the historical inventory supply and demand change data, the object accessory historical demand change relationship of different accessories to different demand parties in the analysis period is extracted , m represents the number of different demand parties; According to the object accessory historical demand change relationship of different accessories of different demand parties , respectively determine the accessory historical demand change relationship of different accessories , wherein ; According to the accessory historical inventory change relationship corresponding to different accessories And the accessory historical demand change relationship corresponding to different accessories Conduct supply and demand consistency analysis to form the consistency supply and demand change data; Among them, the relationship between the historical inventory changes of different accessories is used. The relationship between the historical demand changes of the corresponding different accessories. A supply and demand consistency analysis is performed to generate the consistent supply and demand change data, including: for different accessories, according to corresponding said accessory historical inventory change relations and corresponding said accessory historical demand change relations respectively carry out continuous integration in said analysis period, and carry out the following comparative analysis: like Then the historical inventory change relationship of the aforementioned accessories will not be considered. Adjustments were made, including Indicates in [0, Any duration within the range, This indicates the total duration of the analysis cycle. This represents the supply-demand deviation threshold corresponding to accessory number n; If , then according to the accessory historical demand change relationship , a consistency adjustment function is determined, wherein , and the consistency adjustment function satisfies , represents a consistency adjustment coefficient; with the consistency adjustment function replacing the original inventory change relationship with the new inventory change relationship ;​ The step of creating a digital twin of the spare parts inventory change model based on the consistent supply and demand change data, and establishing a digital twin model for spare parts inventory management, includes: Based on the consistent supply and demand change data, and taking the analysis period as the time span, a digital twin of the changes in parts inventory is generated in chronological order to establish the parts inventory management digital twin model.

2. The digital twin-based automobile parts inventory management method according to claim 1, characterized by, The process involves collecting real-time parts demand information and performing inventory optimization analysis based on the parts inventory management digital twin model to generate inventory management optimization analysis data, including: Collect real-time parts demand information, extract demand information for different parts, and generate real-time parts demand change data; Based on the real-time spare parts demand change data, and combined with the spare parts inventory management digital twin model, inventory optimization analysis is performed to form the inventory management optimization analysis data.

3. The digital twin-based automobile parts inventory management method according to claim 2, characterized by, The process of collecting real-time parts demand information, extracting demand information for different parts, and forming real-time parts demand change data includes: Based on the real-time parts demand information, extract the real-time demand changes of different parts from different demanders within the real-time analysis period. ; According to the real-time demand change relationship of the same object accessory corresponding to different demand parties , determine the total accessory demand change relationship corresponding to different accessories , wherein .

4. The digital twin-based automobile parts inventory management method according to claim 3, characterized by, The inventory management optimization analysis data is generated by performing inventory optimization analysis based on the real-time spare parts demand change data and the spare parts inventory management digital twin model, including: According to the accessory inventory management digital twin model, the model mapping accessory inventory change relationship of different accessories in the period corresponding to the real-time analysis cycle is extracted ; According to the total demand change relationship of the corresponding accessory And the model mapping accessory inventory change relationship Carrying out inventory optimization analysis to form accessory inventory optimization information corresponding to different accessories; The inventory optimization information for different accessories is collected to form the inventory management optimization analysis data.

5. The automotive parts inventory management method based on digital twins according to claim 4, characterized in that, The different accessories, according to the corresponding total demand change relationship of the accessories And the model mapping accessory inventory change relationship Carrying out inventory optimization analysis, forming the corresponding accessory inventory optimization information of different accessories, including: for different accessories, according to the corresponding total demand change relationship of the accessories and the model mapping accessory inventory change relationship The following analysis is performed: If then form the current inventory parts quantity unchanged information, wherein, represents extracting the model mapping parts inventory change relationship the maximum value within the real-time analysis cycle, represents extracting the total demand change relationship of the parts the minimum value within the real-time analysis cycle; like > ,and > Then the real-time change rate of the parts can be determined. And based on the real-time change rate of the components. Determine the inventory change rate at the corresponding time point. ,in, This represents the real-time analysis bias threshold corresponding to accessory number n, and ≥0, This indicates the historical inventory change relationship of the aforementioned accessories. The first derivative with respect to time, This represents any duration within the real-time analysis period. This indicates the relationship between the total demand for the aforementioned components. The model maps the relationship between parts inventory changes. The difference at the corresponding time points; like > ,and < Then the real-time change rate of the parts can be determined. And based on the real-time change rate of the components. Determine the inventory change rate at the corresponding time point. ; like > ,and ≤ ≤ This will result in information indicating that the current inventory of spare parts remains unchanged.

6. A digital twin-based automotive parts inventory management system, characterized in that, include: The data acquisition unit is used to collect historical inventory supply and demand change data; A digital twin unit is used to acquire the historical inventory supply and demand change data collected by the data acquisition unit, create a digital twin of the spare parts inventory change model, and establish a digital twin model for spare parts inventory management. The optimization analysis unit is used to collect real-time parts demand information and perform inventory optimization analysis based on production supply according to the digital twin model of parts inventory management, thereby generating inventory management optimization analysis data. The digital twin unit is also used to acquire the historical inventory supply and demand change data, perform supply and demand consistency analysis, and form consistent supply and demand change data; Based on the consistent supply and demand change data, a digital twin of the spare parts inventory change model is generated, and a digital twin model for spare parts inventory management is established. The step of acquiring the historical inventory supply and demand change data, performing supply and demand consistency analysis, and forming consistent supply and demand change data includes: Based on the historical inventory supply and demand data, extract the historical inventory change relationships for different components within the analysis period. , where n represents the part number of the different parts; Based on the historical inventory supply and demand data, extract the historical demand relationship of different demanders for different components within the analysis period. , m represents the number of different demanders; Based on the historical demand changes of different demanders for different accessories, the aforementioned accessories are described. The historical demand changes for different components were determined separately. ,in, ; Based on the historical inventory change relationship of different accessories The relationship between the historical demand changes of the corresponding different accessories. A supply and demand consistency analysis is performed to generate the consistent supply and demand change data. Among them, the relationship between the historical inventory changes of different accessories is used. The relationship between the historical demand changes of the corresponding different accessories. A supply and demand consistency analysis is performed to generate the consistent supply and demand change data, including: For different components, based on the corresponding historical inventory change relationship of the component. and the corresponding relationship between the historical demand changes of the aforementioned accessories Continuous integration was performed within the analysis period, and the following comparative analysis was conducted: like Then the historical inventory change relationship of the aforementioned accessories will not be considered. Adjustments were made, including Indicates in [0, Any duration within the range, This indicates the total duration of the analysis cycle. This represents the supply-demand deviation threshold corresponding to accessory number n; like Based on the historical demand changes of the aforementioned components Determine the consistency adjustment function ,in, And the consistency adjustment function satisfy , Indicates the consistency adjustment factor; Using the consistency adjustment function Replace the historical inventory change relationship of the aforementioned parts The original change relationship is used to form a new historical inventory change relationship for the aforementioned accessories. ; The step of creating a digital twin of the spare parts inventory change model based on the consistent supply and demand change data, and establishing a digital twin model for spare parts inventory management, includes: Based on the consistent supply and demand change data, and taking the analysis period as the time span, a digital twin of the changes in parts inventory is generated in chronological order to establish the parts inventory management digital twin model.

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