CN117829901A - Control method and device of accessory management system and readable storage medium - Google Patents
Control method and device of accessory management system and readable storage medium Download PDFInfo
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Abstract
The present invention relates to the field of after-sales systems, and in particular, to a control method and apparatus for an accessory management system, and a readable storage medium. The method comprises the steps of receiving multi-source heterogeneous data which are transmitted by an accessory data interface and are related to equipment after sale, and generating an equipment accessory database according to the multi-source heterogeneous data; generating a fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database; after entering the accessory prediction process, the received region identifier and equipment identifier are input into the accessory demand linkage prediction model, and short-term accessory prediction results corresponding to the region identifier and the equipment identifier are generated through the accessory demand linkage prediction model. The accuracy and the dynamics of the fitting demand prediction are realized, and the accuracy of fitting storage and the timeliness of fitting supply are further improved.
Description
Technical Field
The present invention relates to the field of after-sales systems, and in particular, to a control method and apparatus for an accessory management system, and a readable storage medium.
Background
To ensure timeliness of the after-market response of the device, a reasonable inventory of the accessories of the device is required. However, because of the variety of accessories, the demands of different areas, different devices and different models of accessories are different, and the demands are predicted by means of traditional manual experience, so that the reserve amounts of various accessories are difficult to accurately grasp. If the storage is insufficient, the timeliness of the after-sales service response is affected; if the reserve is excessive, funds are occupied again and the reserve cost is increased.
The related prediction technology considers two factors of historical consumption and fault prediction, but ignores other important factors affecting spare part requirements, such as the total number of devices currently in use in each region, the accessory consumption rate of the devices in different use stages, the number of devices in use of the devices of different models, the service life condition of the devices of each model, the accessory loss in storage and maintenance and the like. Because only the historical data is used for extrapolation, there is no linkage of the association relation between the product and the accessory, the association relation between the accessory and the like, and therefore, the storage prediction method of the related equipment accessory has the defect of insufficient prediction accuracy and dynamics.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a control method of an accessory management system, which aims to solve the problems of insufficient prediction accuracy and dynamics of a storage prediction method of related equipment accessories.
In order to achieve the above object, the present invention provides a control method of an accessory management system, the control method of the accessory management system comprising the steps of:
receiving multi-source heterogeneous data which are transmitted by an accessory data interface and are related to after-sales equipment, and generating an equipment accessory database according to the multi-source heterogeneous data;
generating a fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database;
after entering the accessory prediction process, the received region identifier and equipment identifier are input into the accessory demand linkage prediction model, and short-term accessory prediction results corresponding to the region identifier and the equipment identifier are generated through the accessory demand linkage prediction model.
Optionally, after the step of generating the short-term accessory prediction result corresponding to the region identifier and the equipment identifier through the accessory demand linkage prediction model, the method further includes:
inputting the short-term fitting prediction result into the fitting demand linkage prediction model;
and outputting a medium-long term fitting prediction result based on the short term fitting prediction result after the fitting demand linkage prediction model receives the short term fitting prediction result.
Optionally, before the step of receiving the multi-source heterogeneous data related to the after-sales equipment transmitted by the accessory data interface and generating the equipment accessory database according to the multi-source heterogeneous data, the method further includes:
establishing connection of an accessory data interface with the accessory Yun Cangping station, the enterprise resource system and the client management system;
the after-market data is received based on the accessory data interface when the after-market data is updated in the accessory Yun Cangping, enterprise resource system, and the customer management system.
Optionally, the step of receiving the multi-source heterogeneous data related to the after-sales device transmitted by the accessory data interface and generating the accessory database of the equipment according to the multi-source heterogeneous data includes:
attaching a data identifier to the multi-source heterogeneous data according to the source of the multi-source heterogeneous data after the multi-source heterogeneous data is received, and generating accessory data, wherein the data identifier comprises a product attribute identifier, an accessory relation identifier and a maintenance time identifier;
the equipment accessory database is generated based on the data identification of each of the accessory data.
Optionally, before the step of generating the accessory demand linkage prediction model according to the association relation of each key accessory in the equipment accessory database, the method further includes:
invoking a preset association rule algorithm, and executing association relation analysis operation on the accessory data in the equipment accessory database;
determining the association relation corresponding to the accessory data according to the association relation analysis operation, wherein the association relation comprises the association relation between a product and an accessory and the association relation between the accessory and the accessory;
and calling a preset confidence threshold corresponding to the accessory data according to different accessory data, and determining the association relation of the key accessory in the association relation corresponding to each accessory data.
Optionally, the step of calling a preset confidence threshold corresponding to the accessory data according to different accessory data, and determining the association relationship of the key accessory in the association relationship corresponding to each accessory data further includes:
and when the equipment accessory database is updated, executing the updating action of the association relation of the key accessories.
Optionally, the step of inputting the received region identifier and the equipment identifier to the accessory demand linkage prediction model, and generating the short-term accessory prediction result corresponding to the region identifier and the equipment identifier through the accessory demand linkage prediction model includes:
after the accessory demand linkage prediction model receives the region identifier and the equipment identifier, reading historical sales data, quality assurance maintenance data and accessory consumption data of target equipment in a target region in the equipment accessory database based on the region identifier and the equipment identifier;
according to the historical sales data, the quality assurance maintenance data and the accessory consumption data, carrying out demand prediction on accessories of the target equipment to obtain the demand of each accessory of the target equipment;
and outputting the demand of each accessory of the target equipment as the short-term accessory prediction result.
Optionally, after the step of generating the accessory demand linkage prediction model according to the association relation of each key accessory in the equipment accessory database, the method further includes:
outputting historical prediction data in a preset time period based on a model checking interface every preset time period;
and adjusting the model parameters of the accessory demand linkage prediction model according to the model adjustment parameters received by the model checking interface.
In addition, in order to achieve the above object, the present invention also provides a control device of an accessory management system, the control device of the accessory management system including a memory, a processor, and a control program of the accessory management system stored on the memory and executable on the processor, the control program of the accessory management system implementing the steps of the control method of the accessory management system as described above when executed by the processor.
In addition, in order to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a control program of an accessory management system, which when executed by a processor, implements the steps of the control method of the accessory management system as described above.
The embodiment of the invention provides a control method, equipment and a readable storage medium of an accessory management system, wherein data which are related to after-sales of equipment and are of different sources can be obtained by receiving multi-source heterogeneous data transmitted by an accessory data interface. Thus, the accessory information of different channels can be comprehensively collected and integrated; by integrating the multi-source heterogeneous data and generating a device accessory database with the association relation of each key accessory, a data base is provided for realizing the accuracy of accessory demand prediction. By generating the accessory demand linkage prediction model according to the association relation of each key accessory in the equipment accessory database, the mutual influence and the demand association between accessories and between equipment and accessories can be predicted more accurately, so that the accessory demand prediction is dynamic. By inputting the region identification and the equipment identification into the accessory demand linkage prediction model, the prediction model can predict the accessory demand in time according to the latest data and the association relation, and short-term accessory prediction results corresponding to the region and the equipment are generated, so that the accuracy of accessory storage and the timeliness of supply are improved. Therefore, the control method of the accessory management system realizes the accuracy and the dynamics of accessory demand prediction through the utilization of multi-source heterogeneous data, the association relation modeling of key accessories and the generation of short-term accessory prediction results, thereby improving the accuracy of accessory storage and the timeliness of accessory supply.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention. In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic architecture diagram of a hardware operating environment of a control device of an accessory management system according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of a control method of the accessory management system of the present invention;
FIG. 3 is a flow chart of a second embodiment of a control method of the accessory management system of the present invention;
fig. 4 is a flowchart of a third embodiment of a control method of the accessory management system of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The control method of the accessory management system comprises the steps of receiving multi-source heterogeneous data which are transmitted by an accessory data interface and are related to after-sales equipment, and generating an equipment accessory database according to the multi-source heterogeneous data; generating a fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database; after entering the accessory prediction process, the received region identifier and equipment identifier are input into the accessory demand linkage prediction model, and short-term accessory prediction results corresponding to the region identifier and the equipment identifier are generated through the accessory demand linkage prediction model. The accuracy and the dynamics of the fitting demand prediction are realized, and the accuracy of fitting storage and the timeliness of fitting supply are further improved.
In order to better understand the above technical solution, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As an implementation manner, fig. 1 is a schematic architecture diagram of a hardware running environment of a control device of an accessory management system according to an embodiment of the present invention.
As shown in fig. 1, the control device of the accessory management system may include: a processor 101, such as a core processor, a memory 102, and a communication bus 103. The Memory 102 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 102 may alternatively be a storage device separate from the aforementioned processor 101. The communication bus 103 is used to enable connected communication among the components.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the control device of the accessory management system, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, a memory 102, which is a kind of computer-readable storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a control program of an accessory management system.
In the control device of the accessory management system shown in fig. 1, the processor 101, the memory 102 may be provided in the control device of the accessory management system, which invokes the control program of the accessory management system stored in the memory 102 through the processor 101, and performs the following operations:
receiving multi-source heterogeneous data which are transmitted by an accessory data interface and are related to after-sales equipment, and generating an equipment accessory database according to the multi-source heterogeneous data;
generating a fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database;
after entering the accessory prediction process, the received region identifier and equipment identifier are input into the accessory demand linkage prediction model, and short-term accessory prediction results corresponding to the region identifier and the equipment identifier are generated through the accessory demand linkage prediction model.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
inputting the short-term fitting prediction result into the fitting demand linkage prediction model;
and outputting a medium-long term fitting prediction result based on the short term fitting prediction result after the fitting demand linkage prediction model receives the short term fitting prediction result.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
establishing connection of an accessory data interface with the accessory Yun Cangping station, the enterprise resource system and the client management system;
the after-market data is received based on the accessory data interface when the after-market data is updated in the accessory Yun Cangping, enterprise resource system, and the customer management system.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
attaching a data identifier to the multi-source heterogeneous data according to the source of the multi-source heterogeneous data after the multi-source heterogeneous data is received, and generating accessory data, wherein the data identifier comprises a product attribute identifier, an accessory relation identifier and a maintenance time identifier;
the equipment accessory database is generated based on the data identification of each of the accessory data.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
invoking a preset association rule algorithm, and executing association relation analysis operation on the accessory data in the equipment accessory database;
determining the association relation corresponding to the accessory data according to the association relation analysis operation, wherein the association relation comprises the association relation between a product and an accessory and the association relation between the accessory and the accessory;
and calling a preset confidence threshold corresponding to the accessory data according to different accessory data, and determining the association relation of the key accessory in the association relation corresponding to each accessory data.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
and when the equipment accessory database is updated, executing the updating action of the association relation of the key accessories.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
after the accessory demand linkage prediction model receives the region identifier and the equipment identifier, reading historical sales data, quality assurance maintenance data and accessory consumption data of target equipment in a target region in the equipment accessory database based on the region identifier and the equipment identifier;
according to the historical sales data, the quality assurance maintenance data and the accessory consumption data, carrying out demand prediction on accessories of the target equipment to obtain the demand of each accessory of the target equipment;
and outputting the demand of each accessory of the target equipment as the short-term accessory prediction result.
In one embodiment, the processor 101 may be configured to invoke a control program of the accessory management system stored in the memory 102 and perform the following operations:
outputting historical prediction data in a preset time period based on a model checking interface every preset time period;
and adjusting the model parameters of the accessory demand linkage prediction model according to the model adjustment parameters received by the model checking interface.
Based on the hardware architecture of the control device of the accessory management system, an embodiment of the control method of the accessory management system is provided.
Referring to fig. 2, in a first embodiment, the control method of the accessory management system includes the steps of:
step S100: and receiving multi-source heterogeneous data which are transmitted by the accessory data interface and are related to equipment after sale, and generating an equipment accessory database according to the multi-source heterogeneous data.
In this embodiment, the accessory management system receives the multi-source heterogeneous data related to after-sales equipment sent by each data source through the accessory data interface, and after receiving the multi-source heterogeneous data related to after-sales equipment, performs data processing operations such as a data cleaning action and a data integration action on the multi-source heterogeneous data to obtain the processed multi-source heterogeneous data related to after-sales equipment. And then generating a device accessory database based on the multi-source heterogeneous data after data processing.
Optionally, the data sources herein include, but are not limited to, accessories Yun Cangping, enterprise resource systems, customer management systems, and the like. The multi-source heterogeneous data associated with the after-market device includes, but is not limited to, device usage information, historical spare part storage and consumption data, warranty maintenance records, device detection data, and the like.
As an alternative embodiment, after receiving the multi-source heterogeneous data, the accessory management system attaches a data identifier to the multi-source heterogeneous data according to the source of the multi-source heterogeneous data, and generates accessory data, wherein the data identifier comprises a product attribute identifier, an accessory relation identifier and a maintenance time identifier. The device accessory database is then generated based on the data identification of each of the accessory data.
By attaching the data identifier to the multi-source heterogeneous data, the accessory data related to after-sales equipment is generated, so that the related information of equipment accessories in different data sources can be integrated together, and the accessory data is more comprehensive. The data identification provides a basis for classifying and associating the accessory data, and based on the identification of each accessory data, the data can be organized and managed according to the product attribute, the accessory relation and the maintenance time, and an equipment accessory database is constructed, so that the subsequent accessory demand prediction and accessory supply management are better supported.
Further, the accessory management system needs to establish connection of the accessory data interface with the accessory Yun Cangping platform, the enterprise resource system and the client management system before receiving the multi-source heterogeneous data related to after-sales equipment transmitted by the accessory data interface; and further receives the after-market data based on the accessory data interface when the after-market data is updated in the accessory Yun Cangping, the enterprise resource system, and the customer management system.
By establishing the accessory data interface connection, the after-sale related data of the equipment can be updated into the equipment accessory database in real time. When the data in the accessory Yun Cangping station, the enterprise resource system or the client management system changes, the interface can timely transmit updated data, and the accuracy and the instantaneity of the equipment accessory database are ensured. By receiving data in the accessory Yun Cangping station, the enterprise resource system and the customer management system, after-sales related data of equipment in different systems and platforms can be obtained, the comprehensiveness of an accessory database is improved, and a more comprehensive data base is provided for subsequent accessory prediction. The automatic collection and transmission of the data can be realized by establishing the connection of the accessory data interface, the tedious process of manually collecting and inputting the data is avoided, the time and labor cost are saved, the error rate of data collection and importing is reduced, and the accuracy of the data is improved. Therefore, by establishing a connection with the accessory Yun Cangping station, the enterprise resource system and the customer management system for the accessory data interface and receiving data updates related to after-sales of the equipment based on the interface, real-time synchronization of the data, diversification of data sources and automated data collection can be achieved, thereby providing a more reliable, comprehensive and efficient data base for generating equipment accessory databases.
Step S200: and generating a fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database.
In this embodiment, after the equipment accessory database is generated, the accessory demand linkage prediction model is generated according to the association relation of each key accessory in the equipment accessory database. For example, the association of the key accessories may be "the increase in the replacement demand of the accessory Y caused by the increase in the sales of the device model X".
Further, in generating the fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database, the association relation of the key fitting needs to be determined first. Specifically, a preset association rule algorithm is called first, and association relation analysis operation is executed on the accessory data in the equipment accessory database; then, according to the association analysis operation, determining the association corresponding to each accessory data, wherein the association comprises the association of the product and the accessory and the association of the accessory and the accessory; and further, according to different accessory data, calling a preset confidence threshold corresponding to the accessory data, and determining the association relation of the key accessory in the association relation corresponding to each accessory data. It should be noted that, the preset association rule algorithm performs association analysis through indexes such as frequent item sets and confidence level, and analyzes association relations between accessory data in the accessory database of the device. The association relationship corresponding to each accessory data describes the correlation and dependence between different accessories. Alternatively, the preset association rule algorithm may be an Apriori algorithm or an FP-growth algorithm, etc.
By calling a preset association rule algorithm to execute association relation analysis operation, the association relation between the product and the accessories is determined, namely, which accessories are needed by different products, and the association relation between the accessories and equipment, the change condition of the requirements of the accessories under the condition that the requirements of certain equipment are increased or decreased can be predicted better. By determining the correlation and dependency between accessories, the change in demand of other accessories in the event of an increase or decrease in demand of a certain accessory can be better predicted. Influences among different accessories and influences among equipment and accessories are comprehensively considered, and accuracy of accessory demand prediction is improved. By calling a preset confidence threshold corresponding to the fitting data, the fitting association relationship obtained through association relationship analysis can determine which fittings are key fittings, namely fittings with larger influence on other fitting requirements. The aim of the method is to further improve the accuracy of the fitting demand linkage prediction model in prediction in order to achieve the mutual influence and the dependency relationship between the fittings and the association relationship between the fittings and the equipment.
Further, when the equipment accessory database is updated, an updating action of the association relation of the key accessories is executed. It can be understood that, the updating action of the association relation of the key accessory refers to executing and calling a preset association rule algorithm, and executing association relation analysis operation on accessory data in the updated equipment accessory database; then according to the association analysis operation, determining the association corresponding to each accessory data; and further, calling a preset confidence threshold corresponding to the accessory data according to different accessory data, and determining the association relation of the key accessory in the association relation corresponding to each accessory data.
When new accessories or old accessories change, the equipment accessory database is updated, and if the association relation of the key accessories is not updated in time, the outdated or inaccurate data is used when the accessory demand prediction is carried out, so that the prediction result is inaccurate. By executing the updating action of the association relation of the key accessories to reflect the latest association and dependency relation between the accessories and the association relation between the accessories and the equipment, the accessory demand prediction model can better predict the actual accessory demand condition, and further the accuracy and instantaneity of the accessory demand prediction model prediction result are ensured.
Step S300: after entering the accessory prediction process, the received region identifier and equipment identifier are input into the accessory demand linkage prediction model, and short-term accessory prediction results corresponding to the region identifier and the equipment identifier are generated through the accessory demand linkage prediction model.
Optionally, after entering the accessory prediction process, outputting a region selection interface and a device selection interface, and then receiving the region identification and the device identification selected by the user based on the region selection interface and the device selection interface. It will be appreciated that the region selection interface herein provides region options for user selection and the device selection interface provides device options for user selection. The purpose of this is to avoid that the received region identification and the device identification do not have a corresponding region or a corresponding device.
As an optional implementation manner, after the accessory demand linkage prediction model receives the region identifier and the equipment identifier, based on the region identifier and the equipment identifier, historical sales data, quality assurance maintenance data and accessory consumption data of the target equipment in the target region are read from the equipment accessory database; then, according to the historical sales data, the quality assurance maintenance data and the accessory consumption data, carrying out demand prediction on accessories of the target equipment to obtain the demand of each accessory of the target equipment; and further outputs the required amounts of the respective accessories of the target device as the short-term accessory prediction result.
The accessory demand linkage prediction model is based on historical sales data, quality assurance maintenance data and accessory consumption data of target equipment in a target area, and can obtain demand trend and change rule of each accessory of the target equipment in the target area, so that demand of the accessory in a short period can be predicted more accurately. It will be appreciated that the short-term fitting forecast herein may be used for the management of fitting inventory to avoid excessive fitting occupancy in inventory, improving fitting utilization and capital utilization, while ensuring adequate fitting supply to meet after-market service requirements. The purpose of this is to allow the parts management system to predict and determine the number of parts needed for reasonable inventory control based on the regional and equipment needs.
In the technical scheme provided by the embodiment, the multi-source heterogeneous data transmitted by the accessory data interface can be received, so that the after-sale related data of different sources can be obtained. Thus, the accessory information of different channels can be comprehensively collected and integrated; by integrating the multi-source heterogeneous data and generating a device accessory database with the association relation of each key accessory, a data base is provided for realizing the accuracy of accessory demand prediction. By generating the accessory demand linkage prediction model according to the association relation of each key accessory in the equipment accessory database, the mutual influence and the demand association between accessories and between equipment and accessories can be predicted more accurately, so that the accessory demand prediction is dynamic. By inputting the region identification and the equipment identification into the accessory demand linkage prediction model, the prediction model can predict the accessory demand in time according to the latest data and the association relation, and short-term accessory prediction results corresponding to the region and the equipment are generated, so that the accuracy of accessory storage and the timeliness of supply are improved. Therefore, the control method of the accessory management system realizes the accuracy and the dynamics of accessory demand prediction through the utilization of multi-source heterogeneous data, the association relation modeling of key accessories and the generation of short-term accessory prediction results, thereby improving the accuracy of accessory storage and the timeliness of accessory supply.
Referring to fig. 3, based on the foregoing embodiment, in a second embodiment, after the step of generating, by the accessory demand linkage prediction model, a short-term accessory prediction result corresponding to the region identifier and the equipment identifier, the method further includes:
step S410: inputting the short-term fitting prediction result into the fitting demand linkage prediction model;
step S420: and outputting a medium-long term fitting prediction result based on the short term fitting prediction result after the fitting demand linkage prediction model receives the short term fitting prediction result.
In this embodiment, a deep learning prediction framework supporting multi-source heterogeneous data input is constructed based on a neural network. The deep learning prediction framework comprises two layers, short-term prediction is firstly carried out based on historical sales data, quality assurance maintenance data and accessory consumption data, and a short-term accessory prediction result is obtained; and then transmitting the short-term fitting prediction result to a fitting demand linkage prediction model to obtain a medium-long term fitting prediction result.
As an optional implementation mode, firstly, system modeling is carried out on configuration lists and assembly relations of various devices, and a structural tree and graph database corresponding to the devices is constructed. And then according to the structure tree corresponding to the equipment, calculating and obtaining the importance of each accessory, the characteristics of the equipment and the like, and fusing the importance of each accessory, the characteristics of the equipment and the like into an original data set of the association analysis. And then, on the basis of a preset association rule algorithm, increasing the weight associated with the key accessory according to the structural tree corresponding to the equipment to obtain the association relation of the key accessory.
When new equipment exists, multi-source heterogeneous data of the new equipment are received based on the accessory data interface, an updating action is performed on the equipment accessory database, and then, according to the updated equipment accessory database, the updating action of the association relation of the key accessories is performed, so that the updated association relation of the key accessories is obtained. And then, predicting the fitting demand of the new equipment based on the updated association relation of the key fittings to obtain a preliminary fitting predicting result so as to avoid cold start failure.
By continuously updating the association relation of each key accessory, the combination of new and old equipment is tighter, and the accuracy of the prediction result is further improved. By introducing the structural tree corresponding to the equipment, the problem of cold start of the association rule algorithm can be solved, and the accuracy of the new product accessory demand prediction result is improved.
In the technical solution provided in this embodiment, the outputting of the medium-and-long-term fitting prediction result based on the short-term fitting prediction result is to predict the fitting demand for a longer period through a model. Short-term fitting predictions are mainly used to meet recent fitting demands, while medium-long term demand predictions can be used to formulate supply chain strategies and make fitting reserves. By means of the medium-long term fitting forecast, fitting demand in a longer time range in the future can be forecast, and production and inventory can be better arranged to meet future fitting demands. The accessory reserve and supply flow of the accessory management system is further optimized, and the accuracy, timeliness and efficiency of accessory supply are improved.
Referring to fig. 4, based on the foregoing embodiment, in a third embodiment, after the step of generating the fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database, the method further includes:
step S510: outputting historical prediction data in a preset time period based on a model checking interface every preset time period;
step S520: and adjusting the model parameters of the accessory demand linkage prediction model according to the model adjustment parameters received by the model checking interface.
In the present embodiment, after the accessory demand linkage prediction model is generated, the history prediction data within the preset time period is output every interval of the preset time period. The historical prediction data are used for evaluating the prediction result of the accessory demand linkage prediction model by accessory prediction expert groups, analyzing the accuracy and the error of the historical prediction data, detecting the prediction deviation of the accessory demand linkage prediction model in different time periods and areas, determining the defects of the accessory demand linkage prediction model, and further determining the model adjustment parameters. The model adjustment parameters can be input into the model adjustment tool by the accessory prediction expert group through the model checking interface, and the model parameters of the accessory demand linkage prediction model, such as weight adjustment or influence factors, are adjusted. It will be appreciated that the weights herein may be weights associated with the device and the key accessory; the influencing factors here may be historical sales data, warranty repair data, accessory consumption data, etc. of the target device in the target region.
In the technical scheme provided by the embodiment, the model parameters of the accessory demand linkage prediction model are adjusted by outputting historical prediction data and receiving model adjustment parameters and then according to the model adjustment parameters received by the model checking interface. And further, the optimization of the accessory demand linkage prediction model is realized, and the accuracy of the accessory demand linkage prediction model prediction is further improved.
Furthermore, it will be appreciated by those of ordinary skill in the art that implementing all or part of the processes in the methods of the above embodiments may be accomplished by computer programs to instruct related hardware. The computer program comprises program instructions, and the computer program may be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in the control device of the accessory management system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a computer-readable storage medium storing a control program of an accessory management system, which when executed by a processor, implements the steps of the control method of the accessory management system as described in the above embodiments.
The computer readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, etc. which may store the program code.
It should be noted that, because the storage medium provided in the embodiments of the present application is a storage medium used to implement the method in the embodiments of the present application, based on the method described in the embodiments of the present application, a person skilled in the art can understand the specific structure and the modification of the storage medium, and therefore, the description thereof is omitted herein. All storage media used in the methods of the embodiments of the present application are within the scope of protection intended in the present application.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second and third, et cetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A control method of an accessory management system, characterized in that the control method of the accessory management system comprises the steps of:
receiving multi-source heterogeneous data which are transmitted by an accessory data interface and are related to after-sales equipment, and generating an equipment accessory database according to the multi-source heterogeneous data;
generating a fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database;
after entering the accessory prediction process, the received region identifier and equipment identifier are input into the accessory demand linkage prediction model, and short-term accessory prediction results corresponding to the region identifier and the equipment identifier are generated through the accessory demand linkage prediction model.
2. The method of claim 1, wherein after the step of generating the short-term fitting forecast results corresponding to the region identifier and the equipment identifier by the fitting demand linkage forecast model, further comprising:
inputting the short-term fitting prediction result into the fitting demand linkage prediction model;
and outputting a medium-long term fitting prediction result based on the short term fitting prediction result after the fitting demand linkage prediction model receives the short term fitting prediction result.
3. The method of claim 1, wherein the step of receiving the after-market equipment related multi-source heterogeneous data transmitted by the accessory data interface and generating the equipment accessory database from the multi-source heterogeneous data further comprises:
establishing connection of an accessory data interface with the accessory Yun Cangping station, the enterprise resource system and the client management system;
the after-market data is received based on the accessory data interface when the after-market data is updated in the accessory Yun Cangping, enterprise resource system, and the customer management system.
4. The method of claim 1, wherein the step of receiving the after-market equipment-related multi-source heterogeneous data transmitted by the accessory data interface and generating the equipment accessory database from the multi-source heterogeneous data comprises:
attaching a data identifier to the multi-source heterogeneous data according to the source of the multi-source heterogeneous data after the multi-source heterogeneous data is received, and generating accessory data, wherein the data identifier comprises a product attribute identifier, an accessory relation identifier and a maintenance time identifier;
the equipment accessory database is generated based on the data identification of each of the accessory data.
5. The method for controlling a fitting management system according to claim 1, wherein before the step of generating the fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database, the method further comprises:
invoking a preset association rule algorithm, and executing association relation analysis operation on the accessory data in the equipment accessory database;
determining the association relation corresponding to the accessory data according to the association relation analysis operation, wherein the association relation comprises the association relation between a product and an accessory and the association relation between the accessory and the accessory;
and calling a preset confidence threshold corresponding to the accessory data according to different accessory data, and determining the association relation of the key accessory in the association relation corresponding to each accessory data.
6. The method for controlling a parts management system according to claim 5, wherein the step of calling a preset confidence threshold corresponding to the parts data according to different parts data, and determining the association relation of the key parts in the association relation corresponding to the parts data further comprises:
and when the equipment accessory database is updated, executing the updating action of the association relation of the key accessories.
7. The method for controlling a parts management system according to claim 1, wherein the step of inputting the received region identifier and equipment identifier into the parts demand linkage prediction model and generating short-term parts prediction results corresponding to the region identifier and equipment identifier by the parts demand linkage prediction model comprises:
after the accessory demand linkage prediction model receives the region identifier and the equipment identifier, reading historical sales data, quality assurance maintenance data and accessory consumption data of target equipment in a target region in the equipment accessory database based on the region identifier and the equipment identifier;
according to the historical sales data, the quality assurance maintenance data and the accessory consumption data, carrying out demand prediction on accessories of the target equipment to obtain the demand of each accessory of the target equipment;
and outputting the demand of each accessory of the target equipment as the short-term accessory prediction result.
8. The method for controlling a fitting management system according to claim 1, wherein after the step of generating the fitting demand linkage prediction model according to the association relation of each key fitting in the equipment fitting database, the method further comprises:
outputting historical prediction data in a preset time period based on a model checking interface every preset time period;
and adjusting the model parameters of the accessory demand linkage prediction model according to the model adjustment parameters received by the model checking interface.
9. A control device of an accessory management system, characterized in that the control device of the accessory management system comprises: a memory, a processor, and a control program of an accessory management system stored on the memory and executable on the processor, the control program of the accessory management system configured to implement the steps of the control method of the accessory management system of any one of claims 1 to 8.
10. A readable storage medium, wherein a control program of an accessory management system is stored on the readable storage medium, which when executed by a processor, implements the steps of the control method of the accessory management system of any one of claims 1 to 8.
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