Material early warning method, device and equipment and storage medium

Abstract

The invention discloses a material early warning method, device and equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining the identification information of a material used during the production of a product, and determining the batch information of the material according to the identification information; determining the quantity of characteristic values of products corresponding to each batch of materials according to the batch information; when the number of the characteristic values is greater than a preset number threshold value, determining a current test statistic according to the characteristic values and the number of the characteristic values; when the current test statistic is greater than or equal to a preset threshold value, carrying out material early warning; through the above mode, after the batch information of the materials is determined by using the identification information, the number of the characteristic values of the products corresponding to each batch of the materials is further determined, then whether there is significant abnormality is judged by using the comparison result of the test statistics in the significance hypothesis verification and the preset threshold value, if yes, material early warning is performed, and if not, material early warning is performed. Therefore, the accuracy and timeliness of material early warning can be effectively improved, and the qualified rate of product production is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a material early warning method, device, equipment and storage medium. Background Art

[0002] Assembly lines are used to produce products from materials. However, in the actual production process, there will be performance differences between batches, and abnormal material performance will lead to unqualified products. Therefore, it is particularly important to provide timely and accurate warnings for materials. At present, the common method for material warnings is based on the material control system to grab materials used for products with poor performance. However, due to timeliness reasons, when the material control system is used to grab the materials, the batch of materials has all been put into the assembly line. On the other hand, after grabbing the materials used for products with poor performance, engineers need to judge the probability of poor product performance based on experience, and then issue warnings based on the judgment results. However, empirical judgments are more or less wrong and will waste a lot of time. Therefore, the above method of material warning is not accurate and timely enough.

[0003] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of this application is to provide a material warning method, device, equipment and storage medium, aiming to solve the technical problem that the existing technology of material warning is not accurate and timely enough.

[0005] To achieve the above purpose, the present application proposes a material early warning method, which includes:

[0006] Obtaining identification information of materials used in product production, and determining batch information of the materials based on the identification information;

[0007] Determine the quantity of characteristic values ​​of the product corresponding to each batch of materials according to the batch information;

[0008] When the number of the characteristic values ​​is greater than a preset number threshold, determining a current test statistic according to the characteristic value and the number of the characteristic values;

[0009] When the current inspection statistic is greater than or equal to a preset threshold, a material warning is issued.

[0010] In one embodiment, when the number of the characteristic values ​​is greater than a preset number threshold, the step of determining the current test statistic according to the characteristic value and the number of the characteristic values ​​includes:

[0011] When the number of the characteristic values ​​is greater than a preset number threshold, calculating a current characteristic value mean value according to the characteristic value and the number of the characteristic values;

[0012] Calculate the sample standard deviation according to the current characteristic value mean and the characteristic value;

[0013] A current test statistic is determined according to the sample standard deviation and the current characteristic value mean.

[0014] In one embodiment, the step of determining the current test statistic according to the sample standard deviation and the current characteristic value mean includes:

[0015] Get the characteristic values ​​of the products corresponding to each historical batch of materials;

[0016] Calculate the mean of historical characteristic values ​​according to the characteristic values ​​of the products corresponding to each historical batch of materials;

[0017] A current test statistic is calculated according to the historical characteristic value mean, the current characteristic value mean, and the sample standard deviation.

[0018] In one embodiment, the step of performing a material early warning when the current test statistic is greater than or equal to a preset threshold value includes:

[0019] Generate a threshold comparison object according to the current test statistic, batch information of the material, and the number of characteristic values;

[0020] Determine the significance level data according to the target hypothesis verification principle;

[0021] Determining a preset threshold value according to the significance level data;

[0022] When the threshold comparison object is greater than or equal to a preset threshold, material warning information is generated;

[0023] A material warning is performed according to the material warning information.

[0024] In one embodiment, the step of determining the quantity of characteristic values ​​of products corresponding to each batch of materials according to the batch information includes:

[0025] Determine whether each batch of materials is put into the assembly line according to the batch information;

[0026] If yes, then grab the target batch data table;

[0027] Writing the characteristic values ​​of the products corresponding to each batch of materials into the target batch data table;

[0028] Count the number of characteristic values ​​in the target batch data table.

[0029] In one embodiment, after the step of determining whether the corresponding batch material is put into use according to the batch information, the method further includes:

[0030] If not, create a new batch data table;

[0031] Name the newly created batch data table as the latest batch data table;

[0032] Writing the characteristic values ​​of the products corresponding to each batch of materials into the latest batch data table;

[0033] Count the number of characteristic values ​​in the latest batch data table.

[0034] In one embodiment, after the step of performing a material warning when the current test statistic is greater than or equal to a preset threshold, the method further includes:

[0035] When receiving the verification request of the target object, the remaining materials of the current batch are subjected to performance test to obtain the current performance test result;

[0036] When the current performance test result does not meet the preset performance requirement, the remaining material is determined to be a material with abnormal performance.

[0037] In addition, to achieve the above purpose, the present application also proposes a material early warning device, which includes:

[0038] An acquisition module, used to acquire identification information of materials used in product production, and determine batch information of the materials according to the identification information;

[0039] A determination module, used to determine the quantity of characteristic values ​​of products corresponding to each batch of materials according to the batch information;

[0040] The determination module is further configured to determine a current test statistic according to the characteristic value and the number of the characteristic values ​​when the number of the characteristic values ​​is greater than a preset number threshold;

[0041] The early warning module is used to issue a material early warning when the current inspection statistic is greater than or equal to a preset threshold.

[0042] In addition, to achieve the above-mentioned purpose, the present application also proposes a material warning device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the material warning method described above.

[0043] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the material warning method described above are implemented.

[0044] One or more technical solutions proposed in the present application have at least the following technical effects: by obtaining the identification information of the materials used in the production of the products, the batch information of the materials is determined according to the identification information; the number of characteristic values ​​of the products corresponding to each batch of materials is determined according to the batch information; when the number of the characteristic values ​​is greater than a preset quantity threshold, the current test statistic is determined according to the characteristic value and the number of the characteristic values; when the current test statistic is greater than or equal to the preset threshold, a material warning is issued; through the above method, after determining the batch information of the materials using the identification information, the number of characteristic values ​​of the products corresponding to each batch of materials is further determined, and then the comparison result of the test statistic in the significance hypothesis verification with the preset threshold is used to determine whether there is a significant abnormality. If so, a material warning is issued, thereby effectively improving the accuracy and timeliness of material warnings, as well as improving the qualified rate of product production and reducing product costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings herein are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the description, are used to explain the principles of the present application.

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0047] Figure 1 A flow chart of the first embodiment of the material warning method of this application;

[0048] Figure 2 A flow chart of the second embodiment of the material warning method of this application;

[0049] Figure 3 A brief flow chart of the material warning method provided in Example 2 of the present application;

[0050] Figure 4 This is a schematic diagram of the module structure of the material warning device of the embodiment of the present application;

[0051] Figure 5 Schematic diagram of the equipment structure of the hardware operating environment involved in the material early warning method in the embodiment of the present application.

[0052] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a material early warning device, etc. The following takes the material early warning device as an example to illustrate this embodiment and the following embodiments.

[0054] Based on this, the present application embodiment provides a material early warning method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the material early warning method of the present application.

[0055] In this embodiment, the material early warning method includes steps S10 to S40:

[0056] Step S10, obtaining identification information of materials used in product production, and determining batch information of the materials according to the identification information.

[0057] It should be noted that the identification information refers to the information of the materials used when the assembly line produces products. The identification information can be a serial number (SN). The product can be a 1Pcs product. In addition, the material can be a single material, multiple materials, processing components, etc. The batch information refers to the batch information of the material when the product is produced. The batches of materials used to produce different products are different. After determining the identification information, it is necessary to use the material's coding rules to capture the batch information of the material, and the batch information can be expressed in yyyymmdd.

[0058] Step S20, determining the quantity of characteristic values ​​of products corresponding to each batch of materials according to the batch information.

[0059] It can be understood that the quantity refers to the total number of characteristic values ​​of the products corresponding to each batch of materials. The characteristic values ​​of the products can be expressed using y i It means that after the batch information is determined, the number of characteristic values ​​of the products corresponding to each batch of materials is counted.

[0060] Further, step S20 includes: determining whether each batch of materials is put into the assembly line according to the batch information; if so, grabbing the target batch data table; writing the characteristic values ​​of the products corresponding to each batch of materials into the target batch data table; and counting the number of characteristic values ​​in the target batch data table.

[0061] It should be understood that the target batch data table refers to a data table used to record the characteristic values ​​of the products. The target batch data table can be represented as sheet1. After determining the batch information of the material, it is determined whether the corresponding batch material is put into the assembly line, that is, whether it is produced as a product, based on the batch information. If so, it indicates that it has been produced as a product. At this time, the target batch data table is captured, and the characteristic values ​​of the products corresponding to each batch of materials are written into the target batch data table. At this time, the characteristic values ​​of multiple products will be recorded in the target batch data table.

[0062] Furthermore, after the step of determining whether the corresponding batch material is put into use according to the batch information, it also includes: if not, creating a new batch data table; naming the new batch data table as the latest batch data table; writing the characteristic values ​​of the products corresponding to each batch of materials into the latest batch data table; and counting the number of characteristic values ​​in the latest batch data table.

[0063] It can be understood that when it is determined that each batch of materials has not been put into the assembly line, it means that they have not been produced as products. At this time, it is necessary to create a new data table for recording the characteristic values ​​of the products, and name the newly created batch data table as the latest batch data table. Then, in the same way, write the characteristic values ​​of the products corresponding to each batch of materials into the latest batch data table. At this time, the latest batch data table will also record the characteristic values ​​of multiple products.

[0064] Step S30, when the number of the characteristic values ​​is greater than a preset number threshold, determine a current test statistic according to the characteristic value and the number of the characteristic values.

[0065] It should be understood that in order to ensure the validity of calculating the current test statistic, the number of characteristic values ​​recorded cumulatively needs to be greater than a preset threshold, which can be set to 100. The current test statistic refers to a value used in hypothesis testing to decide whether to reject the null hypothesis.

[0066] Step S40: When the current inspection statistic is greater than or equal to a preset threshold, a material warning is issued.

[0067] It can be understood that the preset threshold refers to the threshold determined by the target hypothesis verification principle. After determining the current test statistic, it is judged whether the current test statistic is greater than or equal to the preset threshold. If so, it indicates that there may be performance differences between material batches. At this time, material warning is required to prompt the need to test the performance of the material.

[0068] Further, step S40 includes: generating a threshold comparison object according to the current test statistic, batch information of the material and the number of characteristic values; determining significance level data according to the target hypothesis verification principle; determining a preset threshold according to the significance level data; generating material warning information when the threshold comparison object is greater than or equal to the preset threshold; and performing material warning according to the material warning information.

[0069] It should be understood that the threshold comparison object refers to the object to be compared with the preset threshold. After the current test statistic is determined, the threshold comparison object is generated by combining the batch information of the material and the number of characteristic values. For example, the current test statistic is represented by Z, the batch information of the material is represented by yyyymmdd, and the number of characteristic values ​​is represented by n, then the threshold comparison object is represented by Z. yyyymmdd_n .

[0070] It can be understood that the target hypothesis verification principle can be a significance hypothesis verification principle, and the null hypothesis H0 of the target hypothesis verification principle is: Alternative hypothesis H1: Select the significance level α = 0.05 and the rejection region as |Z| ≥ Z 1-α / 2 , that is, the preset threshold value can be 1.96. After generating the threshold comparison object and determining the preset threshold value, it is determined whether the threshold comparison object is greater than or equal to the preset threshold value. If so, a material warning information is generated and immediately sent to the terminal of a professional engineer, who decides whether to verify the material.

[0071] Furthermore, after step S40, it also includes: when receiving a verification request from the target object, performing a performance test on the remaining materials of the current batch to obtain a current performance test result; when the current performance test result does not meet the preset performance requirements, determining that the remaining materials are materials with abnormal performance.

[0072] It is understandable that the target object may be a professional engineer of the assembly line. When receiving the verification request from the target object, it indicates that the material needs to be verified, that is, the performance of the remaining materials in the current batch is tested, and then it is determined whether the test results meet the preset performance requirements. If not, it indicates that there are performance differences between the batches of materials, and then the materials with abnormal performance are further determined, so that the current batch of materials can be returned.

[0073] This embodiment obtains identification information of materials used in product production, determines batch information of the materials according to the identification information; determines the number of characteristic values ​​of products corresponding to each batch of materials according to the batch information; determines the current test statistic according to the characteristic value and the number of characteristic values ​​when the number of the characteristic values ​​is greater than a preset quantity threshold; and issues a material warning when the current test statistic is greater than or equal to the preset threshold. In the above manner, after determining the batch information of the materials using the identification information, the number of characteristic values ​​of products corresponding to each batch of materials is further determined, and then the comparison result of the test statistic in the significance hypothesis verification with the preset threshold is used to determine whether there is a significant abnormality. If so, a material warning is issued, thereby effectively improving the accuracy and timeliness of material warnings, improving the qualified rate of product production, and reducing product costs.

[0074] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , step S30 includes steps S301 to S303:

[0075] Step S301, when the number of the characteristic values ​​is greater than a preset number threshold, calculating a current characteristic value mean according to the characteristic value and the number of the characteristic values.

[0076] It should be noted that the current characteristic value mean refers to the average value of the characteristic values ​​of the products corresponding to each batch of materials. When it is determined that the number of characteristic values ​​is greater than the preset quantity threshold, the current characteristic value mean is calculated, specifically:

[0077]

[0078] in, represents the current feature value mean, n represents the number of feature values, y i Indicates the characteristic values ​​of the products corresponding to each batch of materials.

[0079] Step S302: Calculate the sample standard deviation according to the current characteristic value mean and the characteristic value.

[0080] It can be understood that after calculating the mean of the current characteristic value, the sample standard deviation is calculated in combination with the characteristic value, specifically:

[0081]

[0082] Where s represents the sample standard deviation, represents the current feature value mean, n represents the number of feature values, y i Indicates the characteristic values ​​of the products corresponding to each batch of materials.

[0083] Step S303: determining a current test statistic according to the sample standard deviation and the current characteristic value mean.

[0084] Further, step S303 includes: obtaining characteristic values ​​of products corresponding to each historical batch of materials; calculating the mean of historical characteristic values ​​according to the characteristic values ​​of products corresponding to each historical batch of materials; and calculating the current test statistic according to the mean of historical characteristic values, the mean of current characteristic values ​​and the sample standard deviation.

[0085] It can be understood that since this embodiment uses the current test statistic in the significance hypothesis verification principle to test whether the batch of materials causes significant anomalies between the product characteristics and the historical mean, it is also necessary to use the characteristic values ​​of the products corresponding to each historical batch of materials to calculate the mean of the historical characteristic values. At this time, the current test statistic is calculated in combination with the current characteristic value mean and the sample standard deviation, specifically:

[0086]

[0087] Among them, Z represents the current test statistic, represents the current characteristic value mean, μ0 represents the historical characteristic value mean, and s represents the sample standard deviation.

[0088] This embodiment calculates the current characteristic value mean according to the characteristic value and the number of characteristic values ​​when the number of the characteristic values ​​is greater than a preset number threshold; calculates the sample standard deviation according to the current characteristic value mean and the characteristic value; determines the current test statistic according to the sample standard deviation and the current characteristic value mean; through the above method, when it is determined that the number of characteristic values ​​is greater than the preset number threshold, calculates the current characteristic value mean in combination with the characteristic value, then calculates the sample standard deviation in combination with the characteristic value, and then determines the current test statistic in combination with the current characteristic value mean, thereby effectively improving the accuracy of determining the current test statistic.

[0089] For example, in order to help understand the implementation process of the material early warning method obtained by combining this embodiment with the above-mentioned embodiment 1, please refer to Figure 3 , Figure 3 A brief flow chart of a material early warning method is provided, specifically:

[0090] First, input the identification information of the materials used in product production and the characteristic values ​​of the products, then use the material coding rules to capture the batch information of the materials, and determine whether the materials of the batch information have been put into use. If not, create a new annotation data table and name the newly created annotation data table as the latest annotation data table sheet2. If not, capture the target batch data table and name the target batch data table sheet1. Then count the number of characteristic values ​​in the target batch data table sheet1. When it is determined that the number of characteristic values ​​is greater than the preset quantity threshold, calculate the current test statistic based on the historical characteristic value mean, the current characteristic value mean and the sample standard deviation. Then determine whether the current test statistic is greater than or equal to the preset threshold. If so, issue a material warning.

[0091] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the material warning method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0092] This application also provides a material warning device, please refer to Figure 4 , the material early warning device comprises:

[0093] The acquisition module 10 is used to acquire identification information of materials used in product production, and determine batch information of the materials according to the identification information.

[0094] The determination module 20 is used to determine the quantity of characteristic values ​​of the products corresponding to each batch of materials according to the batch information.

[0095] The determination module 20 is further configured to determine a current test statistic according to the characteristic value and the number of the characteristic values ​​when the number of the characteristic values ​​is greater than a preset number threshold.

[0096] The early warning module 30 is used to issue a material early warning when the current inspection statistic is greater than or equal to a preset threshold.

[0097] This embodiment obtains identification information of materials used in product production, determines batch information of the materials according to the identification information; determines the number of characteristic values ​​of products corresponding to each batch of materials according to the batch information; determines the current test statistic according to the characteristic value and the number of characteristic values ​​when the number of the characteristic values ​​is greater than a preset quantity threshold; and issues a material warning when the current test statistic is greater than or equal to the preset threshold. In the above manner, after determining the batch information of the materials using the identification information, the number of characteristic values ​​of products corresponding to each batch of materials is further determined, and then the comparison result of the test statistic in the significance hypothesis verification with the preset threshold is used to determine whether there is a significant abnormality. If so, a material warning is issued, thereby effectively improving the accuracy and timeliness of material warnings, improving the qualified rate of product production, and reducing product costs.

[0098] The material warning device provided by the present application adopts the material warning method in the above embodiment, which can solve the technical problem that the material warning in the prior art is not accurate and timely. Compared with the prior art, the beneficial effects of the material warning device provided by the present application are the same as the beneficial effects of the material warning method provided by the above embodiment, and the other technical features in the material warning device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0099] In one embodiment, the determination module 20 is also used to determine whether each batch of materials is put into the assembly line based on the batch information; if so, grab the target batch data table; write the characteristic values ​​of the products corresponding to each batch of materials into the target batch data table; and count the number of characteristic values ​​in the target batch data table.

[0100] In one embodiment, the determination module 20 is also used to, if not, create a new batch data table; name the new batch data table as the latest batch data table; write the characteristic values ​​of the products corresponding to each batch of materials into the latest batch data table; and count the number of characteristic values ​​in the latest batch data table.

[0101] In one embodiment, the determination module 20 is also used to calculate the current characteristic value mean based on the characteristic value and the number of the characteristic values ​​when the number of the characteristic values ​​is greater than a preset number threshold; calculate the sample standard deviation based on the current characteristic value mean and the characteristic value; and determine the current test statistic based on the sample standard deviation and the current characteristic value mean.

[0102] In one embodiment, the determination module 20 is also used to obtain the characteristic values ​​of the products corresponding to each historical batch of materials; calculate the mean of the historical characteristic values ​​based on the characteristic values ​​of the products corresponding to each historical batch of materials; and calculate the current test statistic based on the mean of the historical characteristic values, the mean of the current characteristic values ​​and the sample standard deviation.

[0103] In one embodiment, the early warning module 30 is also used to generate a threshold comparison object based on the current test statistic, batch information of the material, and the number of characteristic values; determine the significance level data according to the target hypothesis verification principle; determine a preset threshold based on the significance level data; generate material early warning information when the threshold comparison object is greater than or equal to the preset threshold; and perform material early warning based on the material early warning information.

[0104] In one embodiment, the early warning module 30 is also used to perform a performance test on the remaining materials of the current batch to obtain the current performance test results when a verification request from the target object is received; when the current performance test results do not meet the preset performance requirements, determine that the remaining materials are materials with abnormal performance.

[0105] The present application provides a material warning device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the material warning method in the above-mentioned embodiment one.

[0106] Reference below Figure 5 , which shows a schematic diagram of the structure of a material warning device suitable for implementing the embodiment of the present application. The material warning device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The material warning device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0107] like Figure 5As shown, the material warning device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the material warning device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the material warning device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a material warning device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0108] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. The computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0109] The material warning device provided by the present application adopts the material warning method in the above embodiment, which can solve the technical problem that the material warning in the prior art is not accurate and timely. Compared with the prior art, the beneficial effects of the material warning device provided by the present application are the same as the beneficial effects of the material warning method provided by the above embodiment, and the other technical features in the material warning device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0110] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0111] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0112] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the material early warning method in the above-mentioned embodiment.

[0113] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-ReadOnly Memory), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination thereof.

[0114] The computer-readable storage medium may be included in the material early warning device; or it may exist independently without being assembled into the material early warning device.

[0115] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system and method according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0117] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0118] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned material early warning method, and can solve the technical problem that the material early warning in the prior art is not accurate and timely. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the material early warning method provided in the above-mentioned embodiment, and will not be repeated here.

[0119] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A material early warning method, characterized in that: The method comprises: Obtaining identification information of materials used in product production, and determining batch information of the materials based on the identification information; Determine the quantity of characteristic values ​​of the product corresponding to each batch of materials according to the batch information; When the number of the characteristic values ​​is greater than a preset number threshold, determining a current test statistic according to the characteristic value and the number of the characteristic values; When the current inspection statistic is greater than or equal to a preset threshold, a material warning is issued.

2. The method according to claim 1, characterized in that The step of determining the current test statistic according to the characteristic value and the number of the characteristic values ​​when the number of the characteristic values ​​is greater than a preset number threshold comprises: When the number of the characteristic values ​​is greater than a preset number threshold, calculating a current characteristic value mean value according to the characteristic value and the number of the characteristic values; Calculate the sample standard deviation according to the current characteristic value mean and the characteristic value; A current test statistic is determined according to the sample standard deviation and the current characteristic value mean.

3. The method according to claim 2, characterized in that The step of determining the current test statistic according to the sample standard deviation and the current characteristic value mean includes: Get the characteristic values ​​of the products corresponding to each historical batch of materials; Calculate the mean of historical characteristic values ​​according to the characteristic values ​​of the products corresponding to each historical batch of materials; A current test statistic is calculated according to the historical characteristic value mean, the current characteristic value mean, and the sample standard deviation.

4. The method according to claim 1, characterized in that The step of performing a material early warning when the current inspection statistic is greater than or equal to a preset threshold value includes: Generate a threshold comparison object according to the current test statistic, batch information of the material, and the number of characteristic values; Determine the significance level data according to the target hypothesis verification principle; Determining a preset threshold value according to the significance level data; When the threshold comparison object is greater than or equal to a preset threshold, material warning information is generated; A material warning is performed according to the material warning information.

5. The method according to claim 1, characterized in that The step of determining the quantity of characteristic values ​​of products corresponding to each batch of materials according to the batch information comprises: Determine whether each batch of materials is put into the assembly line according to the batch information; If yes, then grab the target batch data table; Writing the characteristic values ​​of the products corresponding to each batch of materials into the target batch data table; Count the number of characteristic values ​​in the target batch data table.

6. The method according to claim 5, characterized in that After the step of determining whether the corresponding batch material is put into use according to the batch information, the method further includes: If not, create a new batch data table; Name the newly created batch data table as the latest batch data table; Writing the characteristic values ​​of the products corresponding to each batch of materials into the latest batch data table; Count the number of characteristic values ​​in the latest batch data table.

7. The method according to any one of claims 1 to 6, characterized in that After the step of performing a material early warning when the current test statistic is greater than or equal to a preset threshold, the method further includes: When receiving the verification request of the target object, the remaining materials of the current batch are subjected to performance test to obtain the current performance test result; When the current performance test result does not meet the preset performance requirement, the remaining material is determined to be a material with abnormal performance.

8. A material early warning device, characterized in that: The device comprises: An acquisition module, used to acquire identification information of materials used in product production, and determine batch information of the materials according to the identification information; A determination module, used to determine the quantity of characteristic values ​​of products corresponding to each batch of materials according to the batch information; The determination module is further configured to determine a current test statistic according to the characteristic value and the number of the characteristic values ​​when the number of the characteristic values ​​is greater than a preset number threshold; The early warning module is used to issue a material early warning when the current inspection statistic is greater than or equal to a preset threshold.

9. A material early warning device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the material early warning method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the material early warning method according to any one of claims 1 to 7 are implemented.

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