An intelligent replenishment system for automobile parts inventory

Abstract

The application discloses a kind of intelligent replenishment systems of auto parts inventory, including auto parts data acquisition module, vehicle population analysis module, adaptive replacement pedigree module, repair demand analysis module, complete set missing piece evaluation module, effective inventory calculation module, replenishment decision module and execution feedback module, vehicle population analysis module generates accessory failure demand according to the vehicle type, vehicle age and use intensity of in-service vehicle in service area, adaptive replacement pedigree module establishes the adaptive relationship between accessory and vehicle configuration, and records accessory replacement direction and use limit, replenishment decision module improves repair work order complete set satisfaction rate while constraining accessory stagnation risk, execution feedback module updates prediction parameters according to actual loading accessory and returned accessory, the application can reduce the problem that single commonly used accessory inventory is sufficient, but repair project is still unable to complete due to missing key accessory.

Description

Technical Field

[0001] This invention relates to the field of automotive parts inventory management technology, specifically to an intelligent automotive parts inventory replenishment system that generates replenishment plans based on in-use vehicle groups, parts compatibility relationships, and complete repair work order requirements. Background Technology

[0002] Automotive repair shops, parts distributors, and regional parts warehouses typically need to store repair parts for multiple vehicle models to ensure timely availability when vehicles malfunction or require maintenance. Automotive parts also involve part number upgrades and cross-model compatibility; old part numbers may be replaced by new ones, and some aftermarket parts can replace original parts in specific models or production batches. If the inventory system only calculates inventory based on part numbers, it's easy to continue purchasing new part numbers when old ones are still usable, or to mistakenly consider parts that don't meet vehicle compatibility requirements as available inventory. Vehicle repairs often require multiple parts simultaneously, and sufficient inventory of a single part does not guarantee the completion of the repair. When a low-value part required for a repair is out of stock, even if all other high-value parts are available, assembly cannot be completed. Existing replenishment systems primarily sort by the out-of-stock rate of individual parts, making it difficult to identify critical missing parts that hinder repair work orders.

[0003] During the diagnostic phase, repair work orders may contain multiple causes of failure. Repair personnel will reserve various possible parts in advance. If all reserved quantities are considered as confirmed needs, it can easily lead to excessive replenishment. If unconfirmed needs are not included at all, parts may not be available in time after the diagnosis is completed. Some models still require repair parts after production is discontinued, but the demand will decrease as the number of vehicles in use decreases. If the system continues to replenish according to the historical peak outbound volume, it can easily lead to long-term unsold inventory. If the system stops replenishing only because of the recent decrease in outbound volume, it may prevent vehicles still in use from obtaining critical repair parts.

[0004] Therefore, there is a need to provide an intelligent auto parts inventory replenishment system that can predict the demand for parts failure based on the usage status of the vehicle group in the service area, establish a parts spectrum with applicable conditions and alternative directions, and use the availability of the required parts in the repair work order as the basis for replenishment, thereby reducing the risk of repair disruption and auto parts inventory backlog. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent auto parts inventory replenishment system to solve the problems of existing replenishment systems that calculate the demand for individual parts separately, making it difficult to identify key missing parts for repair projects, and failing to properly handle part version substitution and diagnosis of uncertain demand.

[0006] To achieve the above objectives, the present invention provides an intelligent auto parts inventory replenishment system, including an auto parts data acquisition module, a vehicle ownership group analysis module, an adaptation and substitution spectrum module, a maintenance demand analysis module, a complete set of missing parts assessment module, an effective inventory calculation module, a replenishment decision module, an allocation coordination module, and an execution feedback module.

[0007] The auto parts data acquisition module is used to obtain auto parts replenishment-related data from vehicle service records, repair work order systems, inventory management systems, procurement management systems, and parts supply platforms, and convert vehicle and parts identifiers from different systems into a unified data format.

[0008] Auto parts replenishment data includes vehicle data, maintenance data, parts data, inventory data, and supply data. Vehicle data indicates the vehicle models and usage status of vehicles in use within the service area. Maintenance data indicates the fault type and actual parts installed on the vehicle. Parts data indicates the parts specifications and compatibility conditions. Inventory data indicates the location and occupancy status of inventory. Supply data indicates the procurement lead time and minimum order quantity.

[0009] The vehicle ownership group analysis module is used to create vehicle groups based on the vehicle model platform, production batch, power configuration, age range, and usage intensity of vehicles in use within the service area.

[0010] The vehicle ownership group analysis module prioritizes data from vehicles that have entered the repair service network or have maintenance records. It also determines whether a vehicle is still within the service area based on the vehicle's most recent visit time and vehicle status, thus avoiding including vehicles that have been scrapped or transferred out of the area for a long time in the parts demand base.

[0011] For vehicles with incomplete data, the vehicle ownership group analysis module estimates the probability of their continued use based on insurance service records, annual inspection status, or historical visit intervals, and includes them in the vehicle group size according to the stated probability.

[0012] The vehicle ownership group analysis module establishes a parts failure distribution based on the historical fault data of each vehicle group. The parts failure distribution indicates the likelihood of replacement demand for the corresponding parts when the vehicle age, cumulative mileage, or usage time changes.

[0013] When a part is mainly replaced according to a fixed maintenance cycle, the maintenance requirement is calculated based on the estimated mileage of the vehicle group. When a part is mainly replaced due to random failures, the failure requirement is calculated based on the historical failure time of the same vehicle group.

[0014] The demand for parts failure is calculated based on the size of the vehicle fleet and the distribution of parts failures, and is adjusted in conjunction with the probability of vehicles continuing to be used in the future forecast period, so that the replenishment demand can reflect the actual vehicle base in the service area.

[0015] For situations where the historical outbound volume of parts is low but the corresponding vehicle group is about to enter a concentrated failure cycle, the vehicle inventory analysis module can generate demand in advance without waiting for the parts inventory to decrease before triggering replenishment.

[0016] The Adaptation and Replacement Spectrum module is used to establish the compatibility relationship between vehicle configurations and accessories, and to record the replacement direction between accessory versions.

[0017] Each compatibility relationship includes at least the vehicle platform, production time range, power configuration, installation location, and accessory version, enabling the system to determine the set of accessories that can be assembled based on vehicle identification information.

[0018] When parts for the same vehicle model change during production, the adaptation and replacement spectrum module distinguishes the applicable scope according to the vehicle production time or configuration code, and does not directly merge the parts before and after the change into the same inventory.

[0019] Parts substitution relationships can be bidirectional or unidirectional. A bidirectional substitution relationship means that two parts can be used interchangeably under certain conditions. A unidirectional substitution relationship means that a new version of a part can replace an old version of a part, but the old version of a part cannot be used on vehicles that require the new version.

[0020] The substitution relationship can also be configured with additional conditions, such as requiring the installation accessories to be replaced or the vehicle control program to be updated when the parts are substituted. If the additional conditions are missing, the corresponding substitute parts will not be included in the effective inventory coverage.

[0021] When parts manufacturers release information about the termination of alternatives or when vehicle technical requirements change, the Adaptive Alternatives module sets an expiration time for the original alternative relationships to prevent the system from continuing to use expired alternative rules to calculate inventory.

[0022] The maintenance requirement parsing module is used to parse existing maintenance work orders and appointment work orders, and generate a set of maintenance parts corresponding to each maintenance item.

[0023] The maintenance requirement analysis module determines the parts that may be used based on the fault symptoms, diagnostic results and standard maintenance solutions, and divides the parts requirements into confirmed requirements and provisional requirements.

[0024] Confirmed requirements indicate that the repair personnel have confirmed the parts that need to be replaced, while provisional requirements indicate that the use of parts will be determined after further disassembly or testing. Each provisional requirement is configured with a corresponding probability of use.

[0025] The probability of use is calculated based on historical repair results for the same vehicle model, the same fault symptoms, and the same diagnostic stage. After the repair personnel complete the new inspection steps, the repair demand analysis module increases or decreases the probability of use of the corresponding parts based on the inspection results.

[0026] When multiple candidate components are used to solve the same fault and will not be used simultaneously, the candidate components are set as a mutually exclusive requirement group to prevent the system from accumulating all mutually exclusive components as independent requirements.

[0027] When a repair project requires the use of both main components and installation accessories, the corresponding accessories are set as a dependency requirement group, and the accessory inventory is checked simultaneously when the main component requirement is generated.

[0028] The complete missing parts assessment module is used to determine whether the existing inventory can meet the needs of a complete repair project and to calculate the repair completion coverage.

[0029] For each repair work order, the complete set of missing parts assessment module reads the set of repair parts and determines whether all confirmed requirements have available inventory. If any key confirmed part is missing, the corresponding work order is marked as unfinishable.

[0030] Repair completion coverage is used to represent the number of repair work orders or the corresponding probability that existing inventory can fully satisfy, and does not directly replace repair completion capability with the availability rate of a single part.

[0031] For provisional requirements, the complete set of missing parts assessment module calculates the work order completion risk based on the probability of use. When the probability of use of a certain provisional part is high and the procurement time after it is out of stock is long, the impact of the missing part is increased.

[0032] When a part is needed by multiple repair work orders at the same time, the complete missing parts assessment module determines the inventory allocation order based on the appointment time, the impact of vehicle downtime, and the customer's promised time.

[0033] For repair projects that affect vehicle safety or render the vehicle inoperable, the corresponding key parts have a higher priority for completion. For projects that can be delayed and do not affect the basic use of the vehicle, the corresponding parts have a relatively lower priority in terms of inventory.

[0034] The effective inventory calculation module is used to determine the effective inventory quantity that can be used for each accessory when making replenishment decisions.

[0035] Effective inventory includes spare parts in normal quality condition that are not occupied by confirmed demand in the current physical inventory, and increases the available quantity for the corresponding period based on confirmed orders in transit and estimated arrival time.

[0036] For confirmed demand, the corresponding accessories are hard-reserved from the physical inventory according to the actual quantity. Provisional demand is weighted and reserved according to the probability of use. Mutually exclusive demand groups are shared and reserved according to the total probability of use within the group.

[0037] After the repair diagnosis is completed, the provisional parts that are actually needed are converted into hard reserves, and the unselected candidate parts are released from the weight reserve, thereby avoiding the long-term occupation of inventory by all candidate parts during the diagnosis phase.

[0038] Inventory that can directly replace the target part in the adaptation alternative spectrum is included in the effective inventory according to the substitution coverage. Parts that require additional accessories to replace are only covered by substitution when the required accessories are also available.

[0039] When the same alternative part can cover multiple target parts, the effective inventory calculation module does not fully include the alternative inventory in the multiple target parts separately, but records the shared coverage relationship to prevent a single inventory part from being counted as multiple available inventory items.

[0040] For parts that have been shipped out but not yet confirmed for installation, they will be set to a maintenance-occupied status and will no longer be considered available inventory. Parts that are returned after maintenance and pass quality inspection will be restored to available inventory.

[0041] The replenishment decision module is used to generate replenishment plans based on parts failure demand, repair work order demand, effective inventory, procurement lead time, and obsolescence risk.

[0042] The replenishment decision module first identifies the key missing parts that prevent the repair work order from being completed, and then calculates the increase in repair completion coverage after replenishing different parts.

[0043] When replenishing a low-value accessory can complete multiple repair work orders that already have the main component, the corresponding accessory has a higher replenishment priority. When replenishing a high-frequency main component but still cannot complete the repair due to the lack of other key parts, the system reduces the immediate priority of replenishing the main component alone.

[0044] For future failure demand predicted by the vehicle fleet analysis module, the replenishment decision module generates a procurement plan in advance based on the procurement lead time and reserves a safe quantity to cover supply delays.

[0045] The safety quantity is not determined solely by fluctuations in historical parts sales, but also by the size of the applicable vehicle group, the concentration of parts failures, and the coverage of alternative parts.

[0046] When an accessory has multiple reliable alternative versions, the number of security measures for a single version can be reduced; when an accessory has no alternatives and the procurement lead time is long, the corresponding number of security measures can be increased.

[0047] The replenishment decision module also calculates the risk of parts obsolescence, which is determined based on the exit speed of the applicable vehicle group, the replacement trend of parts versions, historical demand intervals, and the duration that existing inventory can cover.

[0048] When older version parts can be unilaterally replaced by newer version parts, the replenishment decision module prioritizes purchasing newer version parts that can cover more vehicle configurations and gradually consumes the old version inventory.

[0049] When older versions of parts cannot be used on new models and the corresponding vehicle fleet is rapidly decreasing, the system will reduce the replenishment quantity or stop replenishing the parts, even if the parts had a high outbound volume in the past.

[0050] The replenishment plan includes parts identification, replenishment quantity, demand time, suggested supply source and reason for replenishment. The reason for replenishment can be confirmed missing parts for repairs, provisional repair risks, vehicle group failure needs or safety stock restoration.

[0051] The replenishment decision module configures evidence versions for the replenishment plan. The evidence versions record the vehicle group range, maintenance work order status, alternative spectrum version, effective inventory time point and supply lead time, so that the formation process of replenishment quantity can be queried.

[0052] The allocation and coordination module is used to compare parts inventory and transportation timeliness among multiple auto parts warehouses, and to determine whether maintenance needs can be met through inventory allocation before purchasing and replenishing.

[0053] When a neighboring warehouse has available spare parts and the transfer arrival time is earlier than the purchase arrival time, the transfer coordination module generates a transfer plan and recalculates the maintenance completion coverage of the warehouse from which the parts are transferred.

[0054] Only when transferring inventory will not cause a higher risk of critical parts shortages in the transferring warehouse will the corresponding inventory be designated as transferable inventory, so as to avoid simply solving the parts shortage in one warehouse while causing another warehouse to lose its maintenance support capabilities.

[0055] The execution feedback module is used to track the actual usage results of purchase orders, transfer orders, and repair parts, and to update system data.

[0056] After the purchased parts arrive, the feedback module verifies the part version and compatibility information. If the actual delivered parts are inconsistent with the purchased version, they are not directly added to the target part inventory. Instead, their coverage is redefined based on the compatibility and replacement spectrum.

[0057] After a repair work order is completed, the execution feedback module records the actual parts installed on the vehicle, releases the provisional reservation of unused candidate parts, and updates the usage probability of the corresponding parts according to the actual cause of the fault.

[0058] When maintenance personnel use alternative parts that are not recognized by the system, the record is sent to the adaptation and alternative spectrum module for verification. After the technical conditions are confirmed, an alternative relationship is added, and a general alternative rule is not directly established based on the result of a single manual assembly.

[0059] The execution feedback module also compares the predicted failure demand with the actual parts usage, determines whether the difference comes from changes in the vehicle fleet, changes in failure probability, or parts substitution, and updates the corresponding parameters.

[0060] This invention also provides an intelligent replenishment method for auto parts inventory. First, it collects vehicle data, maintenance data, parts data, inventory data, and supply data within the service area, and then divides the vehicles in use into groups according to vehicle model configuration.

[0061] Calculate the failure requirements of parts based on the size of the vehicle fleet, vehicle age, and usage intensity, establish the compatibility relationship between vehicle configurations and parts, and record the substitution direction and substitution conditions between parts versions.

[0062] The repair work order is parsed to generate a set of repair parts that includes confirmed and provisional requirements, and the repair completion coverage is calculated based on whether the parts are complete.

[0063] Calculate effective inventory by combining physical inventory, maintenance reserves, in-transit inventory, and alternative parts coverage, and identify key missing parts that prevent maintenance projects from being completed.

[0064] The replenishment priority and quantity are determined based on the completion impact of critical missing parts, future failure requirements, procurement lead time, and spare parts stagnation risk.

[0065] After replenishment is executed, the inventory status, the probability of provisional demand, and the spectrum of parts substitution are updated based on the actual delivered parts and the results of repair and loading.

[0066] The significant technical advantages of this invention are as follows: Compared with the prior art, this invention utilizes a vehicle fleet analysis module to predict parts failure demand based on the vehicle model composition and usage status of vehicles in use within the service area. This eliminates the complete reliance on historical outbound volumes for parts replenishment, enabling the formation of replenishment plans before the vehicle fleet enters a concentrated failure cycle. The adaptation and substitution spectrum module records the compatibility conditions and substitution directions between parts and vehicle configurations. The effective inventory calculation module calculates inventory coverage based on substitution conditions, reducing false inventory sufficiency caused by parts with the same name but unable to be assembled. The maintenance demand analysis module categorizes maintenance parts into confirmed and provisional needs. The complete set missing parts assessment module uses complete maintenance projects as the inventory fulfillment target, allowing the system to prioritize replenishing key parts that restrict maintenance completion and avoiding situations where a single high-frequency part has sufficient inventory but the vehicle still cannot be repaired. The replenishment decision module considers both maintenance completion coverage and parts stagnation risk, improving maintenance support capabilities while reducing the continuous procurement of older parts based on vehicle fleet exits and parts version upgrades. Attached Figure Description

[0067] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a schematic diagram of the module composition of the intelligent auto parts inventory replenishment system of the present invention;

[0069] Figure 2 This is a schematic diagram illustrating the relationship between the in-use vehicle fleet and the failure requirements of spare parts according to the present invention.

[0070] Figure 3 This is a schematic diagram of the vehicle configuration and accessory substitution system of the present invention;

[0071] Figure 4 This is a schematic diagram illustrating the repair parts set and the assessment of missing parts for complete sets of parts in this invention;

[0072] Figure 5 This is a schematic diagram of the effective inventory calculation process of the present invention;

[0073] Figure 6 This is a schematic diagram of the intelligent replenishment method for auto parts inventory of the present invention. Detailed Implementation

[0074] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the scope of protection of the present invention.

[0075] This embodiment takes an auto repair service network with a central auto parts warehouse and multiple repair shops as an example. The system needs to perform inventory analysis on the braking system, engine system and chassis system parts used by different models in the service area, and generate a replenishment plan based on the actual vehicle status, repair work order demand and parts substitution relationship.

[0076] The auto parts data acquisition module obtains vehicle data, repair data, parts data, inventory data, and supply data from vehicle service records, repair work order system, inventory management system, procurement management system, and parts supply platform, and converts the vehicle identification and parts number used by different business systems into a unified data relationship.

[0077] Vehicle data includes vehicle model, production year, power configuration, cumulative mileage, and the date of the most recent maintenance. Maintenance data includes vehicle fault symptoms, diagnostic results, maintenance items, and actual parts installed. Inventory data includes physical inventory, reserved inventory, and inventory in transit. Supply data includes the lead time for procurement of different parts and the minimum order quantity.

[0078] The vehicle ownership group analysis module groups vehicles within the service area according to vehicle model platform, production batch, and power configuration, and further determines the current usage status of each vehicle group by combining vehicle age, cumulative mileage, and historical usage intensity.

[0079] For vehicles that have not been in the service network for a long time, the system does not directly include them in the regional vehicle inventory. Instead, it judges the probability of their continued use based on the vehicle's last visit to the store and existing service records, so that vehicles that have been scrapped or transferred out of the service area for a long time will gradually be removed from the base of parts demand.

[0080] In this embodiment, one group of vehicles has gradually entered the concentrated replacement cycle of braking system components. The actual number of brake pads shipped out of this group of vehicles has not increased significantly in the past quarter. However, based on the vehicle age, cumulative mileage and historical failure records of similar vehicles, it is expected that a relatively concentrated demand for brake component replacement will be formed in the next two months.

[0081] The vehicle fleet analysis module calculates the failure demand of corresponding brake parts within the future prediction period based on the current vehicle fleet size and historical failure distribution. This enables the system to identify upcoming parts demand before actual inventory drops to the traditional replenishment point, rather than relying entirely on historical outbound volumes for delayed replenishment.

[0082] The adaptation and replacement spectrum module further establishes the compatibility relationship between different vehicle configurations and braking accessories. In this embodiment, the old version of brake friction pads originally used by the vehicle group has been discontinued. The new version of friction pads can be used for old models, but it is necessary to install fixed accessories that match the new version at the same time.

[0083] Therefore, the system sets the relationship as a one-way substitution relationship from the new version of the friction pad to the old version of the friction pad, and sets the availability of fixed accessories as an additional condition for the corresponding substitution relationship.

[0084] Specifically, when the central warehouse has ten sets of new version brake friction pads, but only six sets of fixed accessories can be used together, the effective inventory calculation module will not regard all ten sets of friction pads as effective replacement inventory for the old version accessories, but only determine that six of them can form a complete replacement coverage.

[0085] This avoids the problem that the inventory system judges that the inventory is sufficient only based on the quantity of main parts, but in the actual repair process, the replacement parts cannot be installed due to insufficient quantity of accessories.

[0086] During the course of a repair business, a repair shop received a vehicle with abnormal brake noise. The repair personnel initially judged that the fault might be caused by wear of the brake friction pads, or it might only require replacement of the corresponding wear warning component.

[0087] The maintenance requirement analysis module establishes a set of maintenance parts based on the current diagnostic results, sets the wear alarm parts that have been confirmed to need to be replaced as confirmed requirements, and sets the brake friction pads that still need further testing to determine whether they need to be replaced as provisional requirements.

[0088] For provisional needs, the system determines the corresponding probability of use based on historical repair data of the same vehicle model, similar fault symptoms, and the same diagnostic stage. Therefore, the provisional part will not occupy the same quantity of inventory as the parts that have been confirmed for use.

[0089] Once the maintenance personnel continue to disassemble and inspect the brake pads and confirm that they meet the replacement requirements, the maintenance requirement analysis module will change the brake pad requirement from a provisional requirement to a confirmed requirement, and at the same time change the corresponding part quantity from a weighted reserved state to a hard reserved state.

[0090] This repair project also requires corresponding fixed accessories when using the new version of brake pads. Therefore, the complete set of missing parts assessment module does not judge the individual inventory sufficiency rate of the brake pads and fixed accessories separately, but analyzes them as a whole as a set of repair parts required to meet the needs of this repair project.

[0091] A repair work order is only considered complete when both the friction pads and the mounting accessories are in stock. If the friction pads are in stock but the mounting accessories are in short supply, the repair work order is still considered to have a critical missing part.

[0092] In this embodiment, the central warehouse has a sufficient inventory of new version friction pads, but the number of fixed accessories is small. As a result, although multiple repair work orders have the main parts in stock, the vehicle repair cannot be actually completed due to the lack of fixed accessories.

[0093] The complete missing parts assessment module calculates the number of repair work orders that can be fully satisfied before and after the addition of fixed accessories, and determines that a small amount of fixed accessories can transform multiple repair work orders that already have friction plates from an incomplete state to a complete state. Therefore, fixed accessories are identified as key missing parts in the current repair system.

[0094] The replenishment decision module prioritizes replenishment of fixed accessories based on the impact of critical missing parts on repair completion coverage, so that replenishment order is no longer determined solely by the historical outbound frequency or inventory quantity of a single part.

[0095] For another type of older version parts with a high historical outbound frequency, the system further discovered that the actual number of the corresponding models of the parts in the service area has been decreasing. At the same time, new version parts are available to cover their main usage range. Therefore, even if the older version parts had a high outbound volume in the past, the replenishment volume will not be maintained at the same level as the historical peak demand.

[0096] The replenishment decision module determines the obsolescence risk of the part based on the withdrawal speed of the applicable vehicle group, the replacement capability of the new version, and the current inventory coverage period, and gradually reduces the purchase quantity of the old version part to reduce the long-term inventory backlog after the model is withdrawn.

[0097] Before generating replenishment decisions, the effective inventory calculation module also distinguishes different occupancy states in the existing inventory, confirms the hard reservation of the parts corresponding to the demand from the physical inventory, and makes weighted reservations for provisional demands according to their corresponding usage probabilities.

[0098] When multiple mutually exclusive candidate parts are used to handle the same fault, the system will not deduct all candidate parts from the inventory in full quantity. Instead, it will calculate the corresponding shared reserve quantity based on the mutual exclusion relationship and historical usage probability.

[0099] As the repair and diagnosis process progresses, the candidate parts that are actually determined to be used are converted into confirmed requirements, and the original weighted reserves of candidate parts that have been ruled out are released, so that the effective inventory can change continuously with the status of the repair work order.

[0100] For parts for which purchase orders have been placed and which are expected to arrive before the target demand time, the effective inventory calculation module includes them in the effective inventory for the corresponding time period according to the expected arrival time. For parts in transit whose expected arrival time is later than the vehicle repair demand time, they are not directly used to cover the current repair work order.

[0101] With multiple repair shops and central warehouses operating together, the system can also check whether there is available inventory in other warehouses before formal procurement.

[0102] For example, if the central warehouse is missing a key steering system component, and a nearby repair shop has two in stock, the system first analyzes the repair shop's future work orders and vehicle group failure needs. After determining that transferring one of the components will not cause the shop itself to have a critical component shortage, the system then determines that the inventory is available for transfer.

[0103] Therefore, existing network inventory can be used to address short-term maintenance needs, while avoiding creating new maintenance gaps in the warehouses that need to be transferred out in order to meet the maintenance needs of one warehouse.

[0104] The replenishment decision module ultimately integrates confirmed repair shortages, provisional repair risks, future failure needs of the vehicle fleet, effective inventory, procurement lead time, and obsolescence risks to form a replenishment plan.

[0105] For critical components with long procurement lead times and no reliable alternatives, the system can increase the corresponding safety stock quantity in advance. For components with multiple reliable alternative versions, the safety stock of a single version can be appropriately reduced based on the actual alternative coverage capability.

[0106] The replenishment plan should at least record the target parts, the recommended replenishment quantity, the time of need, and the reason for replenishment, so that warehouse or purchasing personnel can distinguish whether the purchase is triggered by the current shortage of maintenance parts or by the future demand for vehicle group failures, the restoration of safety stock, or the risk of provisional maintenance.

[0107] After the purchased parts actually arrive, the feedback module verifies the part number, part version, and applicable vehicle range. When the supplier actually delivers an upgraded version of the part, it is not directly included in the target inventory according to the original purchase number. Instead, it is re-evaluated based on the compatibility and replacement spectrum to determine the models that it can cover and the required accessory conditions.

[0108] Once a repair work order is completed, the execution feedback module records the final actual parts installed on the vehicle and releases the unused provisional parts reserved in the work order, restoring the corresponding inventory to an available state.

[0109] At the same time, the system uses the actual installation results to correct the historical usage probability of provisional requirements. For example, if a candidate part that originally had a high usage probability under a certain fault type is not actually used multiple times in a row, the inventory occupation of the candidate part in subsequent similar work orders can be reduced.

[0110] When maintenance personnel actually use alternative parts that are not yet recorded in the original system's adaptation and replacement spectrum, the system saves the installation record as information to be verified. Instead of directly establishing a universal replacement relationship based on a single maintenance operation, the system updates the adaptation and replacement spectrum after the technical conditions are confirmed.

[0111] After the prediction period ends, the execution feedback module also compares the parts failure demand generated by the vehicle ownership group analysis module with the actual maintenance parts consumption. When the actual demand continues to be higher than the prediction results, it can further analyze whether the actual usage intensity of the vehicle or the corresponding parts failure probability has changed, and update the subsequent prediction parameters.

[0112] This embodiment determines the future actual maintenance basis by using the vehicle ownership group, so that the parts replenishment can reflect the failure needs caused by the vehicle age and usage status in advance. Then, it determines the actual coverage of different versions of inventory by adapting the replacement spectrum, and identifies key missing parts by using the complete parts set of the repair work order as the object, so that the replenishment plan can prioritize solving the parts that restrict the completion of repairs, rather than simply maintaining the inventory quantity of each individual part.

[0113] It should be noted that the inventory management terminal, maintenance work order terminal, vehicle data reading terminal and data communication equipment in this invention can all be mature products in the prior art. Their specific types and communication forms can be selected according to the maintenance service network. The improvement of this invention focuses on the collaborative replenishment decision relationship between the failure demand of the vehicle fleet, the replacement spectrum of parts, the status of missing parts in the maintenance kit, effective inventory and obsolescence risk.

[0114] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. All equivalent substitutions, simple changes or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent replenishment system for auto parts inventory, characterized in that, The system includes an auto parts data acquisition module, a vehicle fleet analysis module, an adaptation and substitution spectrum module, a maintenance demand analysis module, a complete set of missing parts assessment module, an effective inventory calculation module, a replenishment decision module, and an execution feedback module. The auto parts data acquisition module acquires vehicle data, maintenance data, parts data, inventory data, and supply data. The vehicle fleet analysis module generates parts failure requirements based on the vehicle model configuration, age, and usage intensity of vehicles in use within the service area. The adaptation and substitution spectrum module establishes the compatibility relationship between vehicle configurations and parts, as well as the substitution relationship between parts versions. The maintenance demand analysis module generates a set of maintenance parts containing confirmed and provisional requirements based on maintenance work orders. The complete set of missing parts assessment module determines the maintenance completion coverage based on the maintenance parts set and inventory status. The effective inventory calculation module determines the effective parts inventory based on physical inventory, maintenance reserves, in-transit inventory, and substitution coverage. The replenishment decision module generates a replenishment plan based on parts failure requirements, maintenance completion coverage, effective inventory, and obsolescence risk. The execution feedback module updates replenishment-related parameters based on actual arrivals and vehicle loading results.

2. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The vehicle ownership group analysis module divides in-use vehicles into groups based on vehicle platform, production batch, power configuration, vehicle age range, and usage intensity, and generates corresponding parts failure requirements based on the size of the vehicle group, the historical failure distribution of parts, and the probability of continued vehicle use.

3. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The adaptation and replacement spectrum module determines the range of parts to be adapted based on the vehicle platform, production time, power configuration and part version, and records the bidirectional or unidirectional substitution relationship between different parts, as well as the corresponding substitution conditions and validity period.

4. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The maintenance requirement analysis module determines the set of maintenance parts based on the fault phenomenon, diagnosis results and maintenance plan. Parts that have been confirmed to be used are set as confirmed requirements, and parts that need further testing to determine whether they can be used are set as provisional requirements with corresponding usage probabilities.

5. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The complete set of missing parts assessment module determines whether the existing inventory can meet the repair project based on the set of parts required by the repair work order. When any key confirmed part is missing, it is determined that the corresponding repair work order cannot be completed, and the repair completion coverage is determined based on the impact of missing parts.

6. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The effective inventory calculation module determines the effective inventory of spare parts at different time points by deducting the reserved amount corresponding to confirmed demand from the physical inventory, and combining the weighted reserved amount of provisional demand, confirmed in-transit inventory, and the coverage of alternative spare parts that meet the adaptation conditions.

7. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The replenishment decision module determines the replenishment priority and quantity based on the impact of critical missing parts on maintenance completion coverage, the future parts failure demand corresponding to the vehicle group, the procurement lead time, and the risk of parts stagnation.

8. The intelligent replenishment system for auto parts inventory according to claim 1, characterized in that, The execution feedback module updates the inventory coverage relationship based on the version and compatibility information of the actual delivered parts, and releases the reserved quantity of unused provisional demand based on the actual installed parts after the repair is completed, while updating the part usage probability and failure demand parameters.

9. A method for intelligent replenishment of auto parts inventory using the system described in any one of claims 1 to 8, characterized in that, Includes the following steps: Collect vehicle, maintenance, parts, inventory, and supply data; establish a group of vehicles in use based on vehicle status within the service area and generate parts failure requirements; establish an adaptation and substitution spectrum between vehicle configurations and parts; analyze maintenance work orders and generate a set of maintenance parts; calculate maintenance completion coverage based on the set of maintenance parts; calculate effective inventory based on inventory occupancy, in-transit inventory, and substitution relationships; and generate a replenishment plan based on the impact of key missing parts, future failure requirements, and obsolescence risks.

10. The intelligent replenishment method for auto parts inventory according to claim 9, characterized in that, After the replenishment plan is implemented, the effective inventory is updated based on the actual arrival status of the purchased parts and the actual installation results of the repair work orders. The failure demand of the vehicle group, the provisional probability of parts use, and the parts compatibility and substitution relationship are corrected by using the actual parts usage.

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