CN115334024B - Instant response system and instant response method - Google Patents

Abstract

The present invention provides an instant response system and an instant response method. The instant response system includes a storage device and a processor. The storage device stores a response module, a data analysis module, a risk estimation module and a resource estimation module. The processor executes the data analysis module so that the data analysis module performs data analysis on the request data and obtains feature data. The data analysis module generates feedback data based on the feature data and the initial data template, and inputs the feedback data into the response module and the risk estimation module. The processor executes the response module to output the feedback data. The processor executes the risk estimation module to calculate a difference value based on the request data and the feedback data. The instant response system of the present invention adjusts the initial data template or the next feedback data based on the difference value.

Description

Immediate response system and instant response method

Technical Field

The invention relates to a service rapid response technology, in particular to an instant response system and an instant response method.

Background technique

In the communication mode under the network environment, there are data requesters (clients, device ends) and data providers (servers) to process data or request instructions. Data processing/data transmission through a synchronous communication architecture will increase the time of the entire process because the data provider must wait for the complete data operation to be completed before the data can be returned or processed subsequently. It may also cause the data to be returned after the set time of the data request end, resulting in a timeout and process interruption.

Summary of the invention

The present invention is directed to an instant response system and an instant response method which can quickly and automatically respond to information requesting data and output return data.

According to an embodiment of the present invention, the instant response system of the present invention includes a storage device and a processor. The storage device stores a plurality of modules, and the plurality of modules include: a response module, a data analysis module, a risk estimation module, and a resource estimation module. The processor is coupled to the storage device. The processor executes the data analysis module so that the data analysis module performs data analysis on the request data and obtains feature data. The data analysis module generates feedback data based on the feature data and the initial data template, and inputs the feedback data into the response module and the risk estimation module. The processor executes the response module to output the feedback data. The processor executes the risk estimation module to calculate a difference value based on the request data and the feedback data based on a logical rule. When the processor determines that the difference value is greater than a threshold value, the processor executes the resource estimation module to adjust the initial data template according to the difference value.

According to an embodiment of the present invention, the instant response method of the present invention comprises the following steps: using a data analysis module to analyze the request data and obtain characteristic data; using the data analysis module to generate feedback data according to the characteristic data and the initial data template, and outputting the feedback data through a response module. Using a risk estimation module to calculate a difference value according to the request data and the feedback data, and adjusting the initial data template/next feedback data according to the difference value.

Based on the above, the instant response system and the instant response method of the present invention can automatically analyze the request data to automatically determine whether the request data meets the default value, and adjust the initial data template/next return data accordingly according to the difference value, so as to maintain an instant response system with a small number of interfaces and achieve instant response at the same time.

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.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of an instant response system according to an embodiment of the present invention;

FIG2 is a flow chart of an instant response method according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of multiple modules according to an embodiment of the present invention.

Description of Reference Numerals

100: Instant response system;

110: processor;

120: storage device;

121: response module;

122: data analysis module;

123: Risk estimation module;

124: Resource estimation module;

125: Difference accumulation module;

126: Backflush module;

S210～S240: steps.

Detailed ways

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 the description to refer to the same or like parts.

FIG. 1 is a schematic diagram of an instant response system according to an embodiment of the present invention. Referring to FIG. 1 , the instant response system 100 includes a processor 110 and a storage device 120. The processor 110 is coupled to the storage device 120. The storage device 120 can store multiple modules. In this embodiment, the multiple modules include a response module 121, a data analysis module 122, a risk estimation module 123, and a resource estimation module 124. The processor 110 can access the storage device 120 to execute the response module 121, the data analysis module 122, the risk estimation module 123, and the resource estimation module 124. In another embodiment, the multiple modules also include a difference accumulation module and a backwash module. In one embodiment, the processor 110 can also be coupled to an external or internal database to read/write data templates, standard templates, judgment templates, and initial data in the database. In another embodiment, a person can input or the processor 110 can automatically read a pre-stored initial data template. Next, the instant response system 100 can also include a transceiver to receive/transmit request data transmitted by the device end/data request end. The data analysis module 122 can perform data analysis on the request data to generate feature data. The data analysis module 122 generates feedback data according to the feature data in the request data and the initial data template, and inputs the feedback data to the response module 121. Then, the response module 121 outputs the feedback data to the sending end of the request data or the receiving end of the next process. In the present invention, the risk estimation module 123 can calculate the difference between the feedback data and the operation result based on the request data and the feedback data based on the logic rule. It is worth mentioning that the instant response system 100 of the present invention can adjust the initial data template/next feedback data according to the difference value. Specifically, when the difference value is greater than the threshold value, the risk estimation module 123 starts/triggers the resource estimation module 124 so that the resource estimation module 124 adjusts the initial data template according to the difference value. When the difference value is less than or equal to the threshold value, the risk estimation module 123 inputs the difference value to the backwash module so that the backwash module accumulates the difference value in the difference accumulation module and adjusts the next feedback data according to the difference value. Thus, the instant response system 100 of the present invention can respond to the request data of the device side in real time, and adjust the subsequent/next return data according to the difference between the return data output by the instant response system 100 and the calculation result, so as to have the advantages of both synchronous data processing and asynchronous data processing.

In the present embodiment, the processor 110 may include, for example, a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessor, digital signal processor (DSP), application specific integrated circuits (ASIC), 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 for implementing various embodiments of the present invention, so that the processor 110 can access and execute to implement the relevant functions and operations described in various embodiments of the present invention. In this embodiment, the response module 121, the data analysis module 122, the risk estimation module 123, the resource estimation module 124, the difference accumulation module and the backwash module can be implemented in a programming language such as JSON (JavaScript Object Notation), Extensible Markup Language (XML) or YAML, but the present invention is not limited thereto. In this embodiment, the instant response system 100 can be specifically implemented in a personal computer (PC), a local server (Server) or a cloud server, but the present invention is not limited thereto. In one embodiment, the instant response system 100 can also be integrated into an enterprise resource planning (ERP) system to provide a real-time and automatic response request service.

FIG. 2 is a flow chart of an instant response method according to an embodiment of the present invention. Referring to FIG. 1 and FIG. 2, the instant response system 100 of the present embodiment may execute the following steps S210 to S240 to output return data in an instant response to the request data. In the present embodiment, the processor 110 may execute the response module 121, the data analysis module 122, the risk estimation module 123, and the resource estimation module 124. The processor 110 receives the request data and executes step S210. In step S210, the data analysis module 122 performs data analysis on the request data to obtain feature data/feature values.

For example, the characteristic data may be data such as the number of the request item in the request data, the factory number of the request data output end, and/or the requested quantity. Then, the data analysis module 122 generates feedback data according to the characteristic data and the initial data template, and outputs the feedback data through the response module 121. The initial data template may be a data parameter table defaulted by the user or the system. In one embodiment, the initial data template records the data of the factory, project, material number, and the quantity requested each time. In this way, the data analysis module 122 generates feedback data according to the normal distribution or the default allowable value according to the data of the characteristic data corresponding to the request data in the initial data template. For example, if the request data is a request quantity of 48 (characteristic data) for a specific material, and the corresponding quantity in the initial data template is 50 and the preset allowable value is 5%, the data analysis module 122 uses the request quantity 48 of the request data as the feedback data. Then, the data analysis module 122 inputs the feedback data into the response module 121. The processor 110 executes the response module 121 to output the feedback data. In one embodiment, the response module 121 outputs the feedback data to the corresponding external receiving port. For example, Factory A sends a material request to the immediate response system 100. Then, the immediate response system 100 generates feedback data according to the initial data template and the request data. In addition, according to the characteristic data of the material request data, the data analysis module 122 of the immediate response system 100 can analyze whether the feedback data should be returned to the original Factory A or another receiving end.

The data analysis module 122 inputs the returned data and the request data into the risk estimation module 123. Then, the processor 110 executes step S230. In step S230, the risk estimation module 123 calculates the difference value according to the request data and the returned data. Specifically, the risk estimation module 123 can calculate the difference value by operating the request data and the returned data based on the logic rule. The logic rule can be, for example, more real-time and detailed related data such as the actual inventory quantity of the material, the actual project process, the historical process data, the required quantity of the project, or the yield value of each factory, as well as the default judgment rule. For example, after comparing the returned data generated by the initial data template, there are 50 materials A. After the risk estimation module 123 compares the corresponding logic rule, the factory yield value of the corresponding request data is calculated. For example, the factory yield is 90%, so the calculation result is 55 materials A. Therefore, the difference value is 5 materials A. Then, the processor 110 adjusts the initial data template/the next returned data according to the difference value. Specifically, the risk estimation module 123 compares the difference value with the preset threshold value to adjust the initial data template or the next return data. When the risk estimation module 123 determines that the difference value is greater than the threshold value (preset threshold value), the processor 110 executes the resource estimation module 124 to adjust the initial data template according to the difference value. In this way, the instant response system 100 of this embodiment can respond to service requests efficiently and in real time, and adjust the subsequent return data according to the detailed calculation results to ensure data accuracy.

FIG3 is a schematic diagram of multiple modules of an embodiment of the present invention. Referring to FIG1 and FIG3, in this embodiment, the multiple modules further include a difference accumulation module 125 and a backwash module 126. When the risk estimation module 123 determines that the difference value is less than or equal to the threshold value, the processor 110 executes the risk estimation module 123 to input the difference value to the backwash module 126. For example, the difference value is 5, and the threshold value is preset to 10, then the risk estimation module 123 inputs the difference value 5 to the backwash module 126. Then, the backwash module 126 inputs the difference value to the difference accumulation module 125, so that the difference accumulation module 125 accumulates the difference value 5 and the subsequent received difference values to obtain the current total difference value.

In the present invention, when the current total difference value is greater than the difference threshold, the difference accumulation module 125 inputs the current total difference value to the resource estimation module 124, so that the resource estimation module 124 adjusts the initial data template according to the current total difference value. For example, the user presets the difference threshold as 20, then when the current total difference value accumulates to more than 21, the difference accumulation module 125 inputs the current total difference value 21 to the resource estimation module 124, so that the resource estimation module 124 adjusts the initial data template according to the current total difference value 21. In this example, adjusting the initial data template can be, for example, the resource estimation module 124 subtracts the current total difference value 21 from the corresponding data in the initial data template, so that the data analysis module 122 generates subsequent feedback data according to the adjusted initial data template (the initial data template subtracted by 21).

In one embodiment, when the risk estimation module 123 determines that the difference value is less than or equal to the threshold value, the processor 110 executes the risk estimation module 123 to input the difference value to the backwash module 126. Then, the backwash module 126 inputs the difference value to the response module 121, so that the response module 121 adjusts the next return data according to the difference value. For example, if the difference value is 5 and the threshold value is 10, the risk estimation module 123 inputs the difference value 5 to the response module 121 through the backwash module 126, so that the response module 121 subtracts/increases the difference value 5 from the return data output next time, so that the parameters of the multiple return data meet the logical rules/operation rules defaulted by the user.

In one embodiment, in the step where the processor 110 executes the resource estimation module 124 to adjust the initial data template according to the difference value, the resource estimation module 124 also includes adjusting the initial data template stored in the data analysis module 122 according to the difference value, and the backwash module 126 inputs the adjusted initial data template to the response module 121, so that the response module 121 adjusts the next return data according to the adjusted initial data template. For example, the backwash module 126 can actively communicate with the response module 121 to adjust the calibration regression interface in the response module 121 according to the data/initial data template provided by the data analysis module 122. In this way, the response module 121 can correspondingly adjust the next corresponding return data.

In one embodiment, the processor 110 can adjust the initial data template according to multiple historical data. In other words, the instant response system 100 of the present invention can adjust the initial data template according to multiple request data, return data, inventory data and difference values, so that the initial data template gradually approaches and conforms to the actual data and actual operation results.

The risk estimation module 123 can also calculate the difference value based on the request data and the return data based on the trend of the history request data and/or the history data. In one embodiment, the risk estimation module 123 can determine whether the difference value between the request data and the data of the normal distribution is less than a threshold value based on the normal distribution of the history data. For example, when the value in the normal distribution diagram of the history data corresponding to the feature data is 70 to 80 (plus or minus 1 standard deviation), and the value of the return data is 65, the risk estimation module 123 calculates the difference value as 5 (70 minus 65). In the present invention, the standard deviation range of the normal distribution diagram can be pre-set by the user, and the present case should not be limited to this.

In this embodiment, the step of adjusting the initial data template according to the difference value of the present invention also includes the resource estimation module 124 enlarging or reducing the initial data template according to the characteristic data and the difference value in proportion. In addition, the resource estimation module 124 adjusts the value of the initial data template adjusted in proportion according to the difference value. For example, the manufacturing quantity of material A in the initial data template corresponding to the request data is 1000. And considering the manufacturing yield, the rough estimate of the number to be prepared in the initial data template is 1100. The characteristic data in the request data is that the manufacturing quantity is 100, the request quantity is 120, the return data is 120, and the calculation result of the resource estimation module 124 is 110. Therefore, the resource estimation module 124 adjusts the data of the initial data template according to the characteristic data (manufacturing quantity 100) and the data of the initial data template (manufacturing quantity 1000) to the manufacturing quantity 100, and the number to be prepared is 110. Next, the resource estimation module 124 adjusts the value in the adjusted initial data template by 10 (the returned data 120 minus the calculation result data 110) to reduce the 10 materials that are over-authorized/output in the returned data. In this way, the instant response system 100 and the instant response method of the present invention can adjust the parameters and data ratios in the initial data template according to the characteristic data of the request data, and adjust the parameters of the initial data template according to the difference value, and then timely adjust the subsequent returned data according to the previous request data and the returned data to improve the accuracy of the calculation.

In summary, the instant response system 100 and the instant response method of the present invention can effectively improve the data/service processing efficiency, and can generate the return data (return information) of the request data (request information) of the request end (client) in real time and quickly. The instant response system 100 and the instant response method of the present invention can quickly return information to the request end or the next processing port according to the default process to overcome the defect that the overall process of conventional synchronous processing is too lengthy. In addition, the initial data template/next return data is adjusted according to the return data and the subsequent actual calculation results, thereby having the advantages of fast response and controlling inventory/data according to the calculation results. The request end can receive the response quickly, and avoid the situation that the setting of the receiving end needs to be readjusted or the receiving end cannot receive information due to the long response time, or the situation that more additional receiving ends need to be established in conventional asynchronous processing. Through the features of the instant response system 100 and the instant response method of the present invention, the user does not need to significantly adjust the architecture of the responding end, such as changing the synchronous processing architecture to the asynchronous processing architecture, and can also achieve the instant response system 100 and method with both the advantages of synchronous processing and asynchronous processing.

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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims (14)

1. A response-on-demand system, comprising:

A storage device storing an initial data template and a plurality of modules, wherein the plurality of modules comprise a response module, a data analysis module, a risk estimation module and a resource estimation module; and

A processor coupled to the memory device,

Wherein the processor executes the data analysis module to enable the data analysis module to perform data analysis on the request data and acquire the characteristic data, the data analysis module generates feedback data according to the characteristic data and the initial data template and inputs the feedback data to the response module and the risk estimation module,

Wherein the processor executes the response module to output the backhaul data,

Wherein the processor executes the risk estimation module to calculate a variance value based on the request data and the return data based on logic rules,

Wherein the processor executes the resource estimation module to adjust the initial data template based on the variance value when the risk estimation module determines that the variance value is greater than a threshold.

2. The system of claim 1, wherein the plurality of modules further comprises a difference accumulation module and a backwash module,

Wherein when the risk estimation module determines that the variance value is less than or equal to a threshold, the processor executes the risk estimation module to input the variance value to the backwash module, the backwash module inputs the variance value to the variance accumulation module such that the variance accumulation module accumulates the variance value each time to obtain a current total variance value,

When the current total difference value is greater than a difference threshold, the difference accumulation module inputs the current total difference value to the resource estimation module, so that the resource estimation module adjusts the initial data template according to the current total difference value.

3. The on-demand system of claim 1, wherein the plurality of modules further includes a backlash module, the processor executing the risk estimation module to input the difference value to the backlash module when the risk estimation module determines that the difference value is less than or equal to a threshold value,

The back flushing module inputs the difference value to the response module, so that the response module adjusts the back data of the next time according to the difference value.

4. The system of claim 1, wherein the plurality of modules further comprises a back flush module, wherein the resource estimation module adjusts the initial data template stored in the data analysis module according to the variance value, the back flush module inputting the adjusted initial data template to the response module to cause the response module to adjust the back flush data for a next time according to the adjusted initial data template.

5. The on-demand system of claim 1, wherein the processor adjusts the initial data template based on a plurality of historical data.

6. The system of claim 1, wherein the risk estimation module is further configured to calculate the variance value based on the request data and the feedback data based on historical request data and/or historical data trends.

7. The on-demand system of claim 1, wherein the resource estimation module scales up or down the initial data template according to the feature data and the variance value, and adjusts the initial data template according to the variance value.

8. A method of immediate response comprising:

carrying out data analysis on the request data through a data analysis module so as to obtain characteristic data;

generating return data according to the characteristic data and an initial data template through the data analysis module, and inputting the return data to the response module and the risk estimation module;

wherein the backhaul data is output by the response module,

Wherein a variance value is calculated by a risk estimation module based on the request data and the feedback data based on logic rules,

And when the risk estimation module judges that the difference value is larger than a threshold value, the initial data template is adjusted by a resource estimation module according to the difference value.

9. The on-demand method of claim 8, further comprising:

When the risk estimation module judges that the difference value is smaller than or equal to a threshold value, the risk estimation module is used for inputting the difference value to a backlash module;

inputting the difference value to a difference accumulating module through the back flushing module so that the difference accumulating module accumulates the difference value each time to obtain a current total difference value,

When the current total difference value is greater than a difference threshold, the difference accumulation module inputs the current total difference value to the resource estimation module, so that the resource estimation module adjusts the initial data template according to the current total difference value.

10. The on-demand method of claim 8, further comprising:

when the risk estimation module judges that the difference value is less than or equal to a threshold value, the risk estimation module is used for inputting the difference value into a back flushing module,

The back flushing module inputs the difference value to the response module, so that the response module adjusts the back data of the next time according to the difference value.

11. The method of claim 8, wherein the step of the resource estimation module adjusting the initial data template based on the variance value further comprises:

Adjusting, by the resource estimation module, the initial data template stored in the data analysis module according to the variance value;

And inputting the adjusted initial data template into the response module through a back flushing module so that the response module adjusts the back data of the next time according to the adjusted initial data template.

12. The on-demand method of claim 8, wherein the processor adjusts the initial data template based on a plurality of historical data.

13. The on-demand method of claim 8, wherein the step of calculating, by the risk estimation module, the variance value from the request data and the return data based on the logic rule, further comprises: the risk estimation module calculates the difference value according to the request data and the feedback data based on the history request data and/or the history data trend.

14. The on-demand method of claim 8, wherein the step of adjusting the initial data template according to the variance value by the resource estimation module further comprises: the resource estimation module is used for scaling up or down the initial data template according to the characteristic data and the difference value, and adjusting the initial data template according to the difference value.