TWI852171B - Forecast data processing system and forecast data processing method - Google Patents

Abstract

A forecast data processing system and forecast data processing method are provided. The forecast data processing system includes a storage device and a processor. The storage device stores a prediction data comparison module, a difference judgment module, and a difference processing module. The processor is coupled to the storage device, and executes the prediction data comparison module, the difference judgment module, and the difference processing module. The processor input multiple prediction data to the prediction data comparison module to make the prediction data comparison module generate prediction difference data. The processor executes the data difference judgment module to make the data difference judgment module generate a difference judgment result according to the predicted difference data. The difference processing module executes corresponding data difference processing according to the difference judgment result.

Description

Prediction data processing system and prediction data processing method

The present invention relates to a rolling forecast data technology that meets market demand, and in particular to a forecast data processing system and a forecast data processing method.

Currently, for sales forecast and order management of finished products, the host factory will send forecast data to the parts factory so that the parts factory can prepare materials and production lines in advance. However, since each finished product is manufactured through multiple materials and multiple manufacturing steps, and the manufacturing process of each work-in-progress is also different. In addition, storing a large amount of materials in the warehouse will also cause storage costs. Therefore, when the forecast data changes, the parts factory must promptly adjust the work-in-progress orders (such as work orders, production orders) and in-transit purchase orders to effectively reduce inventory costs and improve on-time delivery rates.

However, when there is a new version of forecast data or the forecast data changes, the management staff must manually analyze and adjust the relevant inventory quantity and work-in-progress quantity. Because different customers publish forecast data in different ways, release cycles, release content formats, product models, and product demand levels, the employees of the user company must compare and collect a large amount of relevant data, and spend a lot of man-hours on analysis. As a result, the time and labor costs for users to adjust inventory and related parameters according to forecast data are too high, and it is very unfriendly and inconvenient for users within the company to analyze.

The present invention provides a prediction data processing system and a prediction data processing method, which can automatically compare the difference value between at least two prediction data and user settings according to multiple prediction data and setting parameters to generate a result corresponding to the data difference value and a processing solution.

The prediction data processing system of the present invention includes a storage device and a processor. The storage device stores a prediction data comparison module, a data difference judgment module and a difference processing module. The processor is coupled to the storage device and executes the prediction data comparison module, the data difference judgment module and the difference processing module. The processor inputs a plurality of prediction data into the prediction data comparison module so that the prediction data comparison module generates prediction difference data. The processor generates a difference judgment result according to the prediction difference data through the data difference judgment module. The processor performs data difference processing according to the difference judgment result through the difference processing module.

The data difference judgment module of the present invention includes a data receiving unit and a processing judgment unit. The processor stores the difference judgment result in a storage device. The historical processing record includes historical parameter settings, historical processing settings, and historical processing results. In this way, the processing judgment unit can generate a difference judgment result according to the historical processing record, and then the difference processing module performs data difference processing according to the difference judgment result.

The prediction data processing method of the present invention includes the following steps: inputting a plurality of prediction data into a prediction data comparison module; generating prediction difference data according to the plurality of prediction data through the prediction data comparison module; generating a difference determination result according to the prediction difference data through a data difference determination module; and performing data difference processing according to the difference determination result through a difference processing module.

Based on the above, the forecast data processing system and forecast data processing method of the present invention can utilize the main accounting unit to automatically generate results and processing suggestions corresponding to the difference values in the multiple forecast data according to the multiple forecast data provided by the terminal market, so as to effectively reduce labor costs and improve processing efficiency.

In order to make the above features and advantages of the present invention more clearly understood, embodiments are given below and described in detail with reference to the accompanying drawings.

Reference will now be made in detail to exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and description to represent the same or similar parts.

FIG1 is a schematic diagram of a prediction data processing system of an embodiment of the present invention. Referring to FIG1 , the prediction data processing system 100 includes a processor 110 and a storage device 120. The processor 110 is coupled to the storage device 120. In the present embodiment, the processor 110 may include a central processing unit (CPU), a microprocessor control unit (MCU), or a field programmable gate array (FPGA), etc., or a chip having a data operation function, but the present invention is not limited thereto. The storage device 120 may be a memory, wherein the memory may be, for example, a non-volatile memory such as a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a volatile memory such as a random access memory (RAM), a hard disc drive, a semiconductor memory, and the like, and is used to store the various programs and information mentioned in the present invention. In this embodiment, the storage device 120 may store a plurality of specific modules, algorithms, and/or software, etc., for the processor 110 to read and execute them respectively. It is worth noting that the modules and units described in each embodiment of the present invention can be individually implemented by one or more corresponding algorithms and/or software, and the related functions and operations described in the embodiments can be implemented according to the execution results of one or more algorithms and/or software.

In this embodiment, the storage device 120 can store the prediction data comparison module 121, the data difference judgment module 122 and the difference processing module 123. The processor 110 can read these modules stored in the storage device 120, and detect and process the prediction rolling data for market demand by executing these modules, so as to automatically perform difference processing, message notification to relevant responsible persons or notification to suppliers and other functions. In this embodiment, the prediction data processing system 100 can be, for example, a computer host installed in an enterprise, and provide a user interface for users to operate and input prediction data. Alternatively, in one embodiment, the enterprise management system 100 can also be implemented, for example, with the architecture of a cloud server system. The user can connect to the cloud server to perform operations such as setting relevant parameters, setting thresholds, and setting processing by executing the user interface (UI) program of the electronic device. In this regard, the user can operate the content of the user interface displayed on the display screen of the electronic device so that the user interface or related programs can provide corresponding user operation instructions and setting data to the cloud server. In addition, the user can transmit multiple market forecast data to the forecast data processing system 100 through the cloud server or transceiver. The cloud server can realize the function of automatically providing data analysis and corresponding processing suggestions and/or automatically performing difference processing for the demand forecast data of the terminal market by executing the aforementioned multiple modules.

In this embodiment, the forecast data comparison module 121 can be configured to receive/collect forecast data, work order data, inventory data, and procurement data stored in the database, so that the forecast data comparison module 121 generates forecast difference data based on multiple forecast data. In addition, the forecast data comparison module 121 can perform data pre-processing on multiple forecast data according to the setting value preset by the user (for example, based on weekly, quarterly, and each working day) to extract the required data. For example, the setting value is to compare the demand forecast data of each working day, so that the forecast data comparison module 121 offsets the multiple forecast data with the shipment quantity data to generate forecast difference data including the actual unshipped quantity.

In this embodiment, the data difference judgment module 122 can generate a corresponding difference judgment result for the predicted difference data according to the threshold setting data stored in the ERP database or the storage device 120. The threshold setting data can be, for example, analysis logic, analysis rules, preset values, preset difference ratios, etc. The difference judgment result can be, for example, less than the first threshold, between the first threshold and the second threshold, between the second threshold and the third threshold, greater than the third threshold, etc.

In this embodiment, the difference processing module 123 can be configured to perform data difference processing according to the difference determination result. The data difference processing can be, for example, automatically sending a suspension supply message to the corresponding supplier to achieve the effect of automatically notifying the suspension of supply, sending a correction message to the corresponding contractor (such as the purchasing department, the business department, and the work order management department), and calculating compensation losses.

The storage device 120 is used to store the prediction data comparison module 121, the data difference judgment module 122 and the difference processing module 123. In this embodiment, the processor 110, the storage device 120 and the prediction data comparison module 121 can provide the prediction data input, threshold setting service, various parameter settings, multiple trigger conditions and processing content setting service after the conditions are triggered through a specific application programming interface (API), an interactive interface or a terminal equipment.

In other words, the responsible personnel and users can operate the application program interface of the prediction data processing system 100 and the storage device 120 to input multiple prediction data generated by the demand prediction system and various set parameter values into the storage device 120 and the processor 110, and the prediction data processing system 100 can automatically execute the prediction data comparison module 121, the data difference judgment module 122 and the difference processing module 123 according to the prediction data and the set values to generate relevant results, notification messages and processing suggestions.

In this embodiment, the prediction data processing system 100 may be, for example, set in a computing device of a terminal device or a work order management device for user operation. The terminal device may be used for adjusting the equipment of inventory data. Alternatively, the prediction data processing system 100 may be, for example, set in a cloud server for user operation and connected to an inventory server/inventory database. In this embodiment, the processor 110 may, for example, include a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessor (Microprocessor), digital signal processor (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuits, ASIC), programmable logic device (Programmable Logic Device, PLD), other similar processing circuits or a combination of these devices. The storage device 120 may include a memory and/or a database, wherein the memory may be, for example, a non-volatile memory (NVM). The storage device 120 may store relevant programs, modules, systems or algorithms useful for implementing various embodiments of the present invention, so as to be accessed and executed by the processor 110 to implement the relevant functions and operations described in various embodiments of the present invention. In this embodiment, the prediction data comparison module 121, the data difference judgment module 122 and the difference processing module 123 may be implemented, for example, in programming languages such as JSON (JavaScript Object Notation), Extensible Markup Language (XML) or YAML, but the present invention is not limited thereto.

FIG. 2 is a first flow chart of a forecast data processing method of an embodiment of the present invention. Referring to FIG. 1 and FIG. 2, the forecast data processing system 100 of the present embodiment can execute the following steps S210 to S240. In the present embodiment, the user can operate the application program interface of the forecast data comparison module 121, the data difference judgment module 122, and the difference processing module 123. In step S210, the processor 110 inputs a plurality of forecast data into the forecast data comparison module 121. In the present embodiment, the demand forecast data generated based on the evaluation of the terminal market and the historical demand forecast data can be used as the forecast data. Furthermore, the prediction data may be provided by an external prediction data demand system (eg, a client system) via a transceiver and a communication connection with the storage device 120.

In step S220, the processor 110 generates forecast difference data through the forecast data comparison module 121. In this embodiment, the forecast data comparison module 121 can sort and retrieve data according to the above-mentioned multiple forecast data and the parameter settings (settings of comparison time, setting of comparison product number, etc.) stored in the storage device 120 to find the forecast difference data that meets the user's settings. The forecast difference data may include the product number, the forecast quantity of demand in this period, the forecast quantity of demand in the previous period, and the sudden drop value (sudden drop value) of demand forecast. It is worth noting that the forecast data processing system 100 can generate corresponding notification messages and calculate data (such as compensation loss value) to the external system when the demand forecast data of the terminal market suddenly decreases significantly.

In step S230, the processor 110 generates a difference determination result according to the predicted difference data through the data difference determination module 122. In this embodiment, the data difference determination module 122 compares the predicted difference data according to the determination parameters (determination setting values) preset by the user to generate a difference determination result. The difference determination result may include determination results such as less than the first threshold, between the first threshold and the second threshold, between the second threshold and the third threshold, and greater than the third threshold.

In step S240, the processor 110 performs data difference processing according to the difference determination result through the difference processing module 123 to effectively improve the situation of sudden changes in the forecast data, thereby optimizing the management efficiency of the manufacturing end and the supply end. Therefore, the forecast data processing system 100 and the forecast data processing method of this embodiment can effectively provide corresponding processing suggestions and determination results to the electronic devices of relevant personnel (such as personal calculators, smart phones, etc.) according to the forecast data input by the external advanced planning and scheduling system or the user.

FIG3 is a second flow chart of a prediction data processing method of an embodiment of the present invention. Refer to FIG1 and FIG3. In this embodiment, the data difference judgment module 122 can be a neural network module constructed by a self-attention mechanism (SAM) model, or other similar neural network modules, and can implement a deep reinforcement learning (DRL) function. The data difference judgment module 122 can, for example, utilize a multi-layer neural network. Furthermore, the data difference judgment module 122 can be trained to learn the predicted data and processing records in the inference storage device 120, so as to further find the correlation between, for example, the corresponding product number, the predicted data, the predicted difference data, etc., from the big data to generate the corresponding difference processing correlation function. In this way, the predicted data processing system 100 of the data difference judgment module 122 realizes the function of automatically generating processing suggestions based on historical predicted data and historical processing results. In this embodiment, the predicted data processing system 100 can execute the following steps S310~S352 to achieve the generation of the difference judgment result of the predicted difference data and the execution of the data difference processing.

In step S310, the processor 110 may input the forecast data and forecast rules into the forecast data comparison module 121. The forecast data may include customer item number, delivery date, delivery quantity, customer full name, release date, customer order number, and any manufacturing information and inventory information related to the production and control of work-in-progress (WIP). In this embodiment, the forecast data may be input by the user through an interactive interface and a terminal device. Furthermore, the forecast data processing system 100 receives the forecast data through a transceiver and inputs it into the storage device 120, so that the processor 110 can read the forecast data from the storage device 120 and input it into the forecast data comparison module 121. In another embodiment, the forecast data processing system 100 further includes a demand forecast system, and the demand forecast system is coupled to the storage device 120 and the processor 110. In this way, the demand forecast system can generate multiple forecast data according to the terminal market data input by the evaluator.

In step S320, the processor 110 can generate forecast difference data based on multiple forecast data through the forecast data comparison module 121. The forecast difference data may include data such as the decline quantity, the difference quantity, the previous period quantity, the current period quantity, and the finished product number. In one embodiment, the forecast data comparison module 121 includes a data preprocessing unit and a data comparison unit. In this way, the forecast data processing system 100 preprocesses multiple forecast data according to the data sampling setting through the data preprocessing unit, so that the data preprocessing unit obtains multiple initial data. In this embodiment, the data sampling setting can be, for example, sampling and comparison setting information related to inventory management and forecast data, such as the sampling product number, the sampling forecast data interval, and the sampling type.

In one embodiment, the processor 110 compares the above-mentioned multiple initial data according to the data comparison setting through the data comparison unit, so that the data comparison unit generates multiple forecast difference data. The data comparison setting may include parameter setting information related to data comparison, such as data acquisition type, base date, analysis type, and offset cycle. For example, the forecast data comparison module 121 generates forecast difference data according to the data comparison setting and multiple forecast data. The forecast difference data may include, for example, the product number of finished product A, the forecast quantity of finished product A this week, the forecast quantity of finished product A in the previous week, and the difference between the forecast quantity of finished product A this week and the forecast quantity of the previous week.

In step S330, the processor 110 may obtain the prediction sudden drop task filtering rule setting. In this embodiment, the prediction sudden drop task filtering rule setting may include analysis model, logic, quantity, ratio, customer product number, product name, customer full name, analysis type, and operation type, etc., which are filtering rules related to the sudden drop in the forecast data. In other words, the prediction sudden drop task filtering rule includes trigger parameters for different finished products at different sudden drop amounts. For example, the prediction sudden drop task filtering rule setting may be, for example, when the sudden drop quantity of finished product A in the demand forecast does not reach 1000, it is automatically filtered out and not processed. When the sudden drop in the demand forecast quantity of finished product A is greater than 1000 and less than 10000, the corresponding operation type is to automatically adjust the quantity of work-in-process work orders (such as work orders, production orders) of finished product A; when the sudden drop in the demand forecast quantity of finished product A is greater than 10000 and less than 100000, the corresponding operation type is to send information (message) to relevant personnel for manual judgment; and when the sudden drop in the demand forecast quantity of finished product A is greater than 100000, the corresponding operation type is to automatically send messages to relevant suppliers for delivery; in addition, when the number of days of sluggishness of multiple stock preparations is greater than 180 days, the inventory loss amount is automatically calculated.

In step S340, the processor 110 can generate a difference judgment result through the data difference judgment module 122 according to the predicted difference data and the predicted sudden drop task filtering rules. The difference judgment result may include the number of work orders in process, the inventory quantity, and the number of purchases in transit. The number of purchases in transit is, for example, the number of materials/products that have been ordered by the purchasing department but have not yet been delivered to the warehouse. In one embodiment, the data difference judgment module 122 includes a data receiving unit and a processing judgment unit. In this way, the processor 110 can receive inventory data (i.e., including the number of work orders in process, the inventory quantity, the number of purchases in transit, etc.) and threshold setting data through the data receiving unit and the transceiver. It is worth noting that the difference determination result may also include outputting processing suggestions and predicted difference data to the terminal device of the relevant person in charge, and waiting for the instructions of the person in charge. In other words, the difference determination result (for example, including the corresponding operation type) generated by the prediction data processing system 100 may be first transmitted to the electronic device of the user (for example, the person in charge), and wait for the user to further confirm and adjust the issued processing instructions. Then, the prediction data processing system 100 uses the user's processing instructions as the difference determination result, so that the difference processing module 123 executes the data difference processing confirmed by the user, thereby improving the security and reliability of the prediction data processing system 100.

The processor 110 generates a difference determination result according to the predicted difference data, inventory data and threshold setting data by processing the determination unit. As described above, the difference determination result may include the corresponding operation type in the predicted sudden drop task filtering rule, so the difference determination result may include multiple trigger conditions, such as lower than the threshold, higher than the threshold, and between the first threshold and the second threshold. Moreover, each trigger condition is related to different operations, such as sending information to suppliers, calculating loss compensation amounts, and automatically adjusting work-in-progress work order parameters.

In step S350, the processor 110 can perform data difference processing according to the difference determination result through the difference processing module 123. In step S351, the processor 110 generates a task card and a solution through the difference processing module 123 according to the difference determination result that the predicted data difference is lower than the threshold and the corresponding operation type is to generate a task card and a corresponding solution. In this way, through the task card issued by the prediction data processing system 100, the responsible personnel (such as production management personnel, planners) can greatly reduce the manual inspection of each prediction data and the comparison time to know the data difference and related data of the prediction data. Furthermore, the contractor can use the solution generated by the forecast data processing system 100 as a reference to improve the processing efficiency of the contractor. The solution can be, for example, adjusting the parameters of the work in progress order and notifying the corresponding supplier. The task card can be, for example, the notification information (i.e., notification message) and processing instructions of the work dispatch system.

In step S352, the processor 110 determines that the difference of the predicted data is higher than the threshold value and the corresponding operation type is to automatically notify the supplier to suspend delivery. In this way, the processor 110 generates a notification suspension delivery information to the corresponding supplier's terminal device through the difference processing module 123. The terminal device can be, for example, an electronic device of the corresponding person in charge, such as a personal computer device, a smart phone, or other electronic device.

In one embodiment, the processor 110 generates a difference determination result through a processing determination unit according to the historical processing records stored in the storage device 120. In addition, the processor 110 may also store the difference determination result generated each time in the storage device 120. The historical processing records include historical parameter settings, historical processing settings, and historical processing results. In this way, the data difference determination module 122 can automatically generate a difference determination result including a processing suggestion (i.e., a solution) according to the existing predicted difference data and the historical processing records.

In one embodiment, the threshold setting data includes processing settings for the predicted difference data to be less than a first threshold, between the first threshold and the second threshold, between the second threshold and the third threshold, and greater than the third threshold. For example, the step of the predicted data processing system 100 generating a difference determination result according to the predicted difference data through the data difference determination module 122 may include the following four situations: Situation 1, when the processing determination unit determines that the predicted difference data is less than the first threshold, the processor 110 automatically filters out the predicted difference data through the processing determination unit without performing any processing. In case 2, when the processing judgment unit judges that the predicted difference data is between the first threshold and the second threshold, the processor 110 automatically generates information for adjusting the WIP quantity, so that the difference processing module 123 adjusts the WIP quantity corresponding to the finished product in the WIP work order. For example, when the predicted difference data is between the first threshold and the second threshold, the difference processing module 123 automatically adjusts the WIP data of the WIP work order and does not output notification information or task cards to the responsible personnel.

In case 3, when the processing and judging unit judges that the forecast difference data is between the second threshold and the third threshold, the processor 110 generates the processing process and forecast difference data information (i.e., notification information) through the processing and judging unit, and sends the task card containing the notification information to the responsible personnel (such as production management personnel, planners, purchasers, and sales personnel, etc.) to allow the responsible personnel to confirm and judge the solution. In case 4, when the processing and judging unit judges that the forecast difference data is greater than the third threshold, the processor 110 automatically generates the suspension of supply information to the corresponding supplier through the processing and judging unit, thereby reducing the proportion of manual processing of sudden drop in forecast data. In this embodiment, the third threshold is greater than the second threshold, and the second threshold is greater than the first threshold.

In one embodiment, when the supplier receives information (e.g., information about suspending supply) from the forecast data processing system 100, the supplier generates a feedback message to the forecast data processing system 100 based on the supply information and status. In this way, the processor 110 inputs the feedback message to the difference processing module 123. In addition, the processor 110 performs corresponding difference processing based on the feedback message and the threshold setting data through the difference processing module 123. The difference processing can be, for example, calculating the inventory loss value. For example, the processor 110 calculates the inventory loss value based on the feedback message, the threshold setting data, and the inventory data through the difference processing module 123. Furthermore, the processor 110 outputs the inventory loss value to the terminal device of the person in charge through the difference processing module 123. The threshold setting data may include inventory days. For example, when the supplier replies that the raw materials involved in finished product A cannot be suspended, the forecast data processing system 100 can calculate the material inventory days related to finished product A according to the inventory data based on the preset inventory days, so that the difference processing module 123 can calculate the inventory loss value.

In this way, the forecasting data system 100 of this embodiment can generate forecast difference data (such as data sudden drop values) and corresponding solutions and suggestions based on the set parameters and forecast data, and can also consider inventory data and historical processing records at the same time to provide fast and accurate processing solutions and notification information.

In summary, the prediction data processing system 100 and the prediction data processing method of the present invention allow the user to input a plurality of prediction data into the storage device 120 by inputting the prediction data into the application program interface, so as to generate prediction difference data through the prediction data comparison module 121. In addition, a difference determination result can be generated according to the prediction difference data. In this way, the prediction data processing system 100 can perform data difference processing corresponding to the prediction difference data according to the difference processing module 123, and can effectively improve the processing efficiency when the prediction data changes.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technical personnel in this field should understand that they can still modify the technical solutions described in the above embodiments, or replace part or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

100: Prediction data processing system 110: Processor 120: Storage device 121: Prediction data comparison module 122: Data difference judgment module 123: Difference processing module S210~S240, S310~S350, S351, S352: Steps

FIG1 is a schematic diagram of a prediction data processing system of an embodiment of the present invention. FIG2 is a first flow chart of a prediction data processing method of an embodiment of the present invention. FIG3 is a second flow chart of a prediction data processing method of an embodiment of the present invention.

S210, S220, S230, S240: Steps

Claims (12)

A prediction data processing system includes: a storage device storing a prediction data comparison module, a data difference judgment module and a difference processing module; and a processor coupled to the storage device and executing the prediction data comparison module, the data difference judgment module and the difference processing module, wherein the processor inputs a plurality of prediction data into the prediction data comparison module so that the prediction data comparison module generates prediction difference data, wherein the data difference judgment module generates a difference judgment result according to the prediction difference data, wherein the difference processing module performs data difference processing according to the difference judgment result, wherein the data difference judgment module generates a difference judgment result according to the prediction difference data ... The fault module includes: a data receiving unit, receiving inventory data and threshold setting data, a processing and judgment unit, generating the difference judgment result according to the predicted difference data, the inventory data and the threshold setting data, wherein the processor inputs the feedback message to the difference processing module, and the difference processing module performs corresponding difference processing according to the feedback message and the threshold setting data, wherein the threshold setting data includes inventory days, and the difference processing module calculates the inventory loss value according to the feedback message, the threshold setting data and the inventory data, wherein the difference processing module outputs the inventory loss value. The prediction data processing system as described in claim 1, wherein the prediction data comparison module includes: a data preprocessing unit, which preprocesses the multiple prediction data according to the data sampling setting to obtain multiple initial data, and a data comparison unit, which compares the multiple initial data according to the data comparison setting to generate the prediction difference data. The forecast data processing system as described in claim 1 further includes a demand forecast system coupled to the storage device and the processor, and the demand forecast system generates the plurality of forecast data based on the terminal market data. The prediction data processing system as described in claim 1, wherein the processing judgment unit also generates the difference judgment result based on the historical processing record, and the processor stores the difference judgment result in the storage device, wherein the historical processing record includes historical parameter settings, historical processing settings, and historical processing results. A prediction data processing system as described in claim 1, wherein the threshold setting data includes processing settings for the prediction difference data being less than a first threshold, between the first threshold and a second threshold, between the second threshold and a third threshold, and greater than the third threshold. The prediction data processing system as described in claim 5, wherein when the processing and judging unit judges that the prediction difference data is less than the first threshold value, the difference processing module filters the prediction difference data; when the processing and judging unit judges that the prediction difference data is between the first threshold value and the second threshold value, the processing and judging unit generates an adjustment of the work-in-progress quantity. information, so that the difference processing module adjusts the quantity in process; when the processing and judging unit judges that the predicted difference data is between the second threshold and the third threshold, the processing and judging unit generates notification information; and when the processing and judging unit judges that the predicted difference data is greater than the third threshold, the processing and judging unit generates information to contact the supplier. A prediction data processing method includes: inputting a plurality of prediction data into a prediction data comparison module; generating prediction difference data according to the plurality of prediction data by the prediction data comparison module; generating a difference determination result according to the prediction difference data by a data difference determination module; and performing data difference processing according to the difference determination result by a difference processing module, wherein the step of generating the difference determination result according to the prediction difference data by the data difference determination module includes: receiving inventory data and threshold setting data by a data receiving unit; and and generating the difference judgment result according to the predicted difference data, the inventory data and the threshold setting data through the processing judgment unit, and inputting the feedback message into the difference processing module; performing the corresponding difference processing according to the feedback message and the threshold setting data through the difference processing module, calculating the inventory loss value according to the feedback message, the threshold setting data and the inventory data through the difference processing module; and outputting the inventory loss value through the difference processing module, wherein the threshold setting data includes the inventory days. The prediction data processing method as described in claim 7, wherein the step of generating the prediction difference data according to the multiple prediction data by the prediction data comparison module includes: pre-processing the multiple prediction data according to the data sampling setting by the data pre-processing unit so that the data pre-processing unit obtains multiple initial data; comparing the multiple initial data according to the data comparison setting by the data comparison unit so that the data comparison unit generates the prediction difference data. The forecast data processing method as described in claim 7, wherein before the step of inputting the plurality of forecast data into the forecast data comparison module, includes: generating the plurality of forecast data according to the terminal market data through the demand forecasting system. The prediction data processing method as described in claim 7, wherein the step of performing the data difference processing according to the difference judgment result by the difference processing module includes: generating the difference judgment result according to the historical processing record by the processing judgment unit; and storing the difference judgment result in a storage device, wherein the historical processing record includes historical parameter settings, historical processing settings and historical processing results. The prediction data processing method as described in claim 7, wherein the threshold setting data includes processing settings for the prediction difference data being less than the first threshold, between the first threshold and the second threshold, between the second threshold and the third threshold, and greater than the third threshold. The predicted data processing method as described in claim 11, wherein the step of generating the difference judgment result according to the predicted difference data by the data difference judgment module further includes: when the processing judgment unit judges that the predicted difference data is less than the first threshold, filtering the predicted difference data by the difference processing module; when the processing judgment unit judges that the predicted difference data is between the first threshold and the second threshold, filtering the predicted difference data by the difference processing module; , the processing and judging unit generates information for adjusting the quantity in process, so that the difference processing module adjusts the quantity in process; when the processing and judging unit judges that the predicted difference data is between the second threshold and the third threshold, the processing and judging unit generates notification information; and when the processing and judging unit judges that the predicted difference data is greater than the third threshold, the processing and judging unit generates information for contacting suppliers.

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