Method and device for creating electric power material sampling inspection task

Abstract

The invention discloses an electric power material sampling inspection task creation method and device, and the method comprises the steps: obtaining the material information of to-be-sampled materials, and sorting the to-be-sampled materials in combination with a target sampling inspection dimension and the priority of each sorting index, thereby obtaining a first sorting result; on the basis, determining a sampling inspection probability corresponding to each value in the target sampling inspection dimension; carrying out spot check on the to-be-spot-checked materials in combination with a spot check threshold value corresponding to the target spot check dimension to obtain a first to-be-spot-checked material set; and screening the first to-be-sampled material set in combination with the priority of the secondary sampling dimension corresponding to the target sampling dimension to obtain target to-be-sampled materials and complete task creation of the target to-be-sampled materials. By adopting the target sampling inspection dimension and the secondary sampling inspection dimension, the to-be-sampled materials are sorted and screened, the sampling inspection strategy is dynamically adjusted, the coverage rate of electric power material sampling inspection is increased, meanwhile, the overall efficiency of a supply chain is improved, and intelligent sampling inspection task creation is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of physical inspection management of materials, and particularly relates to a method and device for creating a power material physical inspection task. Background Art

[0002] As an important infrastructure of the national economy, the safe and stable operation of the power system is of crucial importance. The quality of power materials is directly related to the reliability and operation efficiency of the power grid. Through physical inspection, quality problems of materials can be detected in a timely manner, and unqualified products can be prevented from entering the power grid, thus ensuring the safe operation of the power grid.

[0003] The state and the power industry have put forward clear requirements for the quality control of power grid materials. For example, the State Grid Corporation of China has proposed to achieve "100% full coverage" of physical inspections for material categories, suppliers, and production batches to ensure the quality of purchased equipment.

[0004] With the development of technologies such as the Internet of Things, big data, and artificial intelligence, the digital transformation of the power industry has accelerated. These technologies provide new means and methods for power material physical inspection, which can improve the inspection efficiency, reduce the labor cost, and realize the intelligence and informatization of the inspection process.

[0005] Patent CN116452054A discloses a method and device for power system material physical inspection management. The method includes: obtaining a list of materials to be physically inspected in the power system and retrieving the historical quality data of the materials to be physically inspected from the database; establishing a failure function of the materials to be physically inspected according to a first preset parameter and a second preset parameter; predicting the distribution of the failure function through a Bayesian network, importing the historical quality data of the materials to be physically inspected, determining the posterior distribution of the first preset parameter and the second preset parameter, and generating the average value of the first preset parameter and the second preset parameter as the quality result; performing statistics and sorting on the materials to be physically inspected from different manufacturers according to the numerical information of the first preset parameter and the second preset parameter to generate a sorting result; and performing physical inspection on the materials to be physically inspected from different manufacturers according to the sorting result and a preset physical inspection ratio coefficient to generate a physical inspection result, so as to achieve differential physical inspection of the materials to be physically inspected, improve the accuracy of material physical inspection. By analyzing the failure function to obtain the quality result, sorting the materials to be physically inspected from different manufacturers, and completing the physical inspection with a fixed physical inspection ratio coefficient, the materials to be physically inspected from some manufacturers are key-inspected, reducing the influence of other dimensions except the manufacturers on the physical inspection result.

[0006] Therefore, how to dynamically adjust the physical inspection strategy, improve the coverage rate of power material physical inspection, that is, reduce the physical inspection frequency for materials or suppliers with higher qualification rates, increase the physical inspection frequency for materials or suppliers with lower qualification rates, improve the overall efficiency of the supply chain, and realize the intelligent creation of physical inspection tasks is a problem that needs to be solved currently. Summary of the Invention

[0007] In view of the defects existing in the above-mentioned prior art, the present invention provides a method and device for creating a sampling inspection task for electric power materials. The method includes: obtaining the material information of the materials to be sampled; based on the target sampling inspection dimension, combining the material information of the materials to be sampled and the priorities of each sorting index, sorting the materials to be sampled to obtain a first sorting result; according to the first sorting result, analyzing the material information of the materials to be sampled in the first sorting result to determine the sampling probabilities corresponding to each value in the target sampling inspection dimension; obtaining the sampling threshold corresponding to the target sampling inspection dimension, and combining the sampling probabilities corresponding to each value in the target sampling inspection dimension to conduct sampling inspection on the materials to be sampled to obtain a first set of materials to be sampled; combining the priorities of the secondary sampling inspection dimensions corresponding to the target sampling inspection dimension, screening the first set of materials to be sampled to obtain the target materials to be sampled and completing the task creation for the target materials to be sampled. By adopting the target sampling inspection dimension and the secondary sampling inspection dimension, sorting and screening the materials to be sampled, and dynamically adjusting the sampling inspection strategy, the obtained target materials to be sampled are more representative, improving the coverage rate of the sampling inspection of electric power materials and also improving the overall efficiency of the supply chain, and realizing the intelligent creation of sampling inspection tasks.

[0008] In a first aspect, the present invention provides a method for creating a sampling inspection task for electric power materials, which specifically includes the following steps:

[0009] Obtaining the material information of the materials to be sampled;

[0010] Based on the target sampling inspection dimension, combining the material information of the materials to be sampled and the priorities of each sorting index, sorting the materials to be sampled to obtain a first sorting result;

[0011] According to the first sorting result, analyzing the material information of the materials to be sampled in the first sorting result to determine the sampling probabilities corresponding to each value in the target sampling inspection dimension;

[0012] Obtaining the sampling threshold corresponding to the target sampling inspection dimension, and combining the sampling probabilities corresponding to each value in the target sampling inspection dimension to conduct sampling inspection on the materials to be sampled to obtain a first set of materials to be sampled;

[0013] Combining the priorities of the secondary sampling inspection dimensions corresponding to the target sampling inspection dimension, screening the first set of materials to be sampled to obtain the target materials to be sampled and completing the task creation for the target materials to be sampled.

[0014] Further, based on the target sampling inspection dimension, combining the material information of the materials to be sampled and the priorities of each sorting index, sorting the materials to be sampled to obtain a first sorting result, specifically including:

[0015] According to the target sampling inspection dimension, combining the material information of the materials to be sampled, classifying the materials to be sampled to obtain a classification result;

[0016] Based on the classification results, obtain the ranking index values of each type of material to be sampled and inspected for each ranking index.

[0017] According to the ranking index values of each type of material to be sampled and inspected for each ranking index, rank each type of material to be sampled and inspected to obtain the first ranking result.

[0018] Further, based on the first ranking result, analyze the material information of the materials to be sampled and inspected in the first ranking result to determine the sampling probabilities corresponding to each value in the target sampling dimension, specifically including:

[0019] Based on the first ranking result, assign sampling weights to the materials to be sampled and inspected corresponding to each value in the target sampling dimension.

[0020] According to the sampling weights of the materials to be sampled and inspected corresponding to each value in the target sampling dimension, combined with the total sampling weight of the target sampling dimension, give the sampling probabilities corresponding to each value in the target sampling dimension.

[0021] Further, obtain the sampling threshold corresponding to the target sampling dimension, and combined with the sampling probabilities corresponding to each value in the target sampling dimension, sample the materials to be sampled and inspected to obtain the first set of materials to be sampled and inspected, specifically including:

[0022] Based on the sampling probabilities corresponding to each value in the target sampling dimension, and by fusing the pre-constructed sampling function, generate the sampling function values, and sample the materials to be sampled and inspected until the sampling threshold of the target sampling dimension is met to obtain the first set of materials to be sampled and inspected.

[0023] Further, fuse the sampling function, generate the sampling function values, and sample the materials to be sampled and inspected to obtain the first set of materials to be sampled and inspected, specifically including:

[0024] Determine the random value intervals corresponding to each value in the target sampling dimension.

[0025] Taking into account the sampling probabilities corresponding to each value in the target sampling dimension, obtain the first random value, and through the judgment of the random value intervals corresponding to each value in the target sampling dimension, determine the corresponding value of the target sampling dimension.

[0026] Under the determined value of the target sampling dimension, generate corresponding second random numbers for each piece of material information, and sort the sizes of each second random number, and extract a preset number of pieces of material information from the sorting.

[0027] Until the extracted material information meets the sampling threshold of the target sampling dimension, form the first set of materials to be sampled and inspected.

[0028] Among them, the preset number of pieces of material information is determined by the number of materials under the value of the target sampling dimension.

[0029] Furthermore, in combination with the priorities of the secondary sampling dimensions corresponding to the target sampling dimension, the first set of materials to be sampled is screened to obtain the target materials to be sampled and the task creation for the target materials to be sampled is completed, which specifically includes:

[0030] Based on the priorities of the secondary sampling dimensions corresponding to the target sampling dimension, determine the priority levels of each secondary sampling dimension;

[0031] Based on the secondary sampling dimensions at the current priority level, sort the intermediate screening results given by the secondary sampling dimensions at the previous priority level to obtain an intermediate sorting result, where the intermediate screening results given by the secondary sampling dimensions at the previous priority level include the first set of materials to be sampled;

[0032] According to the intermediate sorting result, analyze the material information of the materials to be sampled in the intermediate sorting result to determine the sampling probabilities corresponding to each value in the secondary sampling dimensions at the current priority level;

[0033] Analyze the sampling probabilities corresponding to each value in the secondary sampling dimensions at the current priority level, and screen the materials to be sampled in the intermediate sorting result to obtain an intermediate screening result;

[0034] Until the screening under all the secondary sampling dimensions at all priority levels is completed, the target materials to be sampled are given and the task creation for the target materials to be sampled is completed.

[0035] Furthermore, based on the secondary sampling dimensions at the current priority level, sort the intermediate screening results given by the secondary sampling dimensions at the previous priority level to obtain an intermediate sorting result, which specifically includes:

[0036] Obtain the secondary sampling dimensions at the current priority level and the corresponding secondary sampling indicators, and combine the material information of the materials to be sampled in the intermediate screening result to obtain the secondary sampling indicator values of the materials to be sampled for each secondary sampling indicator;

[0037] Based on the secondary sampling indicator values of each type of material to be sampled for each secondary sampling indicator, in combination with the balance thresholds corresponding to different secondary sampling indicators, judge the secondary sampling indicator values and the balance thresholds corresponding to the secondary sampling indicators to obtain a judgment result;

[0038] Analyze the judgment result and sort the materials to be sampled in the intermediate screening result to obtain an intermediate sorting result.

[0039] Furthermore, the balance threshold is specifically obtained through the following steps:

[0040] According to the value state distribution of different secondary sampling indicators, in combination with the preset sampling ratio, determine the first threshold corresponding to each secondary sampling indicator, where the first threshold is selected from the values of the corresponding secondary sampling indicator;

[0041] Based on a preset adjustment coefficient, the first threshold corresponding to each sub-sampling index is adjusted respectively to obtain the balance threshold corresponding to each sub-sampling index.

[0042] Further, the sorting index includes at least one of the sampling pass rate, the number of sampling times, and the quantity of materials.

[0043] In a second aspect, the present invention also provides a device for creating a power material sampling inspection task, which adopts the method for creating a power material sampling inspection task as described in any one of the above, including:

[0044] A data acquisition module for acquiring the material information of the materials to be sampled.

[0045] A material sorting module for sorting the materials to be sampled based on the target sampling dimension, combining the material information of the materials to be sampled and the priorities of each sorting index to obtain a first sorting result.

[0046] A probability determination module for analyzing the material information of the materials to be sampled in the first sorting result according to the first sorting result to determine the sampling probability corresponding to each value in the target sampling dimension.

[0047] A sampling determination module for obtaining the sampling threshold corresponding to the target sampling dimension, combining the sampling probability corresponding to each value in the target sampling dimension, and sampling the materials to be sampled to obtain a first set of materials to be sampled.

[0048] A task creation module for screening the first set of materials to be sampled in combination with the priorities of the sub-sampling dimensions corresponding to the target sampling dimension to obtain the target materials to be sampled and complete the task creation for the target materials to be sampled.

[0049] A method and device for creating a power material sampling inspection task provided by the present invention have at least the following beneficial effects:

[0050] (1) By acquiring the material information of the materials to be sampled and combining the target sampling dimension and the priorities of each sorting index, sorting the materials to be sampled, and based on the obtained sorting result, determining the sampling probability corresponding to each value in the target sampling dimension, and then sampling the materials to be sampled to obtain a first set of materials to be sampled; screening the first set of materials to be sampled in combination with the priorities of the sub-sampling dimensions corresponding to the target sampling dimension to obtain the target materials to be sampled and complete the task creation for the target materials to be sampled. By adopting the target sampling dimension and the sub-sampling dimension, sorting and screening the materials to be sampled multiple times, dynamically adjusting the sampling strategy, making the obtained target materials to be sampled more representative, improving the coverage rate of power material sampling inspection and at the same time improving the overall efficiency of the supply chain, and realizing the intelligent creation of sampling inspection tasks.

[0051] (2) Affect the sorting result by setting a balance threshold, so as to avoid the situation that the selected target materials to be sampled are the same within a certain period of time, resulting in the unreasonableness of the sampling task, and at the same time promote the healthy development of the sampling process. Description of the Drawings

[0052] Figure 1 It is a flowchart of the method for creating a power material sampling task provided by an embodiment of the present invention;

[0053] Figure 2 It is a flowchart of determining the first sorting result provided by an embodiment of the present invention;

[0054] Figure 3 It is an example diagram of screening the target sampling dimension provided by an embodiment of the present invention;

[0055] Figure 4 It is a flowchart of determining the sampling probability of the target sampling dimension provided by an embodiment of the present invention;

[0056] Figure 5 It is a flowchart of obtaining the target materials to be sampled provided by an embodiment of the present invention;

[0057] Figure 6 It is an example diagram of screening each secondary sampling dimension provided by an embodiment of the present invention;

[0058] Figure 7 It is a flowchart of obtaining the intermediate sorting result provided by an embodiment of the present invention;

[0059] Figure 8 It is a flowchart of determining the balance threshold provided by an embodiment of the present invention;

[0060] Figure 9 It is a structural block diagram of the device for creating a power material sampling task provided by an embodiment of the present invention.

[0061] Among them, 201, data acquisition module; 202, material sorting module; 203, probability determination module; 204, sampling determination module; 205, task creation module. Detailed Embodiments

[0062] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0063] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The singular forms "a", "the", and "said" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0064] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the commodity or device including said element.

[0065] In recent years, with the rapid development of economic construction, the demand for electricity has increased sharply, and the demand for power grid construction has also become increasingly strong. Whether the power grid can operate safely, stably and efficiently depends on the reliability of the quality of power materials. Therefore, power material management is required to accurately identify quality defects, avoid quality accidents, and improve the reliability of equipment operation. Among them, sampling inspection is an important tool for product quality control. An effective sampling inspection strategy can reduce the cost and time of quality inspection and conduct statistical control over the outgoing quality. At present, most of the sampling inspection strategies for power grid materials are determined based on experience. In the process of quality inspection of power equipment materials, traditional technologies often conduct sampling inspection on power equipment materials in a fixed sampling method, lacking flexibility and unable to make adaptive adjustments according to the actual situation of power equipment materials.

[0066] Sampling inspection of materials is an important means of quality management and an important working step in the power material supply chain. Reliable power grid materials are the basis for the safe and stable operation of the power grid.

[0067] A sampling inspection task needs to include multiple factors such as material category, supplier, warehouse, testing agency, sampler, and sample deliverer. The traditional sampling inspection process relies on a large amount of manual operations. After determining a sampling inspection task for a material category, it is necessary to manually confirm the in-stock situation of the materials, determine the testing agency, and contact relevant personnel such as sampling and sample delivery. Moreover, the sampling inspection strategy formulated manually lacks pertinence. The overall process is not only inefficient but also prone to errors. Therefore, formulating a reasonable, intelligent and automated creation strategy for sampling inspection tasks and realizing the dynamic adjustment of sampling inspection strategies are of great significance for the quality supervision of the power material supply chain.

[0068] The present invention provides a method and device for creating a sampling inspection task for electric power materials. The method includes: obtaining the material information of the materials to be sampled; based on the target sampling dimension, combining the material information of the materials to be sampled and the priorities of each sorting index, sorting the materials to be sampled to obtain a first sorting result; according to the first sorting result, analyzing the material information of the materials to be sampled in the first sorting result to determine the sampling probabilities corresponding to each value in the target sampling dimension; obtaining the sampling threshold corresponding to the target sampling dimension, and combining the sampling probabilities corresponding to each value in the target sampling dimension to conduct sampling inspection on the materials to be sampled to obtain a first set of materials to be sampled; combining the priorities of the secondary sampling dimensions corresponding to the target sampling dimension, screening the first set of materials to be sampled to obtain the target materials to be sampled and completing the task creation of the target materials to be sampled. By using the target sampling dimension and the secondary sampling dimension, sorting and screening the materials to be sampled, and dynamically adjusting the sampling strategy, the obtained target materials to be sampled are more representative, improving the coverage rate of the sampling inspection of electric power materials and also improving the overall efficiency of the supply chain, realizing the intelligent creation of sampling inspection tasks.

[0069] As Figure 1 shown, an embodiment of the present invention provides a method for creating a sampling inspection task for electric power materials, and the specific steps are as follows:

[0070] S101: Obtain the material information of the materials to be sampled.

[0071] Specifically, the material information of the materials to be sampled includes all information involved in the sampling process, such as material codes, material categories, supplier information, warehouse information, and testing institution information. The material code is a unique identifier of a material, and the material category represents the type of the material. For example, power generation equipment, transmission lines, distribution equipment, cables and accessories, transformers, switchgear, power instruments and meters, etc. The supplier information is the relevant information of the supplier that produces the material. For example, the supplier's qualification ability, performance evaluation, contract execution evaluation, historical quality control records, etc. The warehouse information is the relevant information of the warehouse storing the material. For example, the storage location of the material, inventory status, inbound and outbound records, etc. The testing institution information is the relevant information of the testing institution that can test the material. For example, institution name, institution qualification, business scope, testing items, etc.

[0072] S102: Based on the target sampling dimension, combine the material information of the materials to be sampled and the priorities of each sorting index, sort the materials to be sampled, and obtain a first sorting result.

[0073] Referring to Figure 2 , specifically includes:

[0074] According to the target sampling dimension, combine the material information of the materials to be sampled, classify the materials to be sampled, and obtain a classification result;

[0075] Based on the classification results, obtain the ranking index values of each type of material to be randomly inspected for each ranking index;

[0076] According to the ranking index values of each type of material to be randomly inspected for each ranking index, rank each type of material to be randomly inspected to obtain the first ranking result.

[0077] The target random inspection dimension is determined from the material information of the materials to be randomly inspected. For example, the target random inspection dimension can be any one of the material category, supplier, and warehouse. Depending on the different target random inspection dimensions, the pertinence of the random inspection tasks obtained is different. According to different actual requirements, select the target random inspection dimension, create the tasks for the target materials to be randomly inspected, and send push notifications to all relevant personnel to start the random inspection.

[0078] In a specific implementation manner, classify the materials to be randomly inspected according to the target random inspection dimension, that is, regard the materials to be randomly inspected with the same value corresponding to the target random inspection dimension in the material information of the materials to be randomly inspected as one category to obtain the classification results. Then obtain the ranking index values of each type of material to be randomly inspected for each ranking index. In the implementation manner provided by the present invention, the ranking indexes include the random inspection pass rate, the number of random inspections, and the quantity of materials. Take the random inspection pass rate as the first index, the number of random inspections as the second index, and the quantity of materials as the third index. Combine the ranking index values (random inspection pass rate values, number of random inspection values, and quantity of material values) of each type of material to be randomly inspected to sort the materials to be randomly inspected in each category in ascending or descending order to obtain the first ranking result.

[0079] For example, first sort the materials to be randomly inspected in each category in ascending order according to the random inspection pass rate values. When the random inspection pass rate values are the same, sort them in ascending order according to the number of random inspection values; when the random inspection pass rate values and the number of random inspection values are both the same, sort them in ascending order according to the quantity of material values, and finally obtain the first ranking result.

[0080] In the implementation manner provided by the present invention, the priorities of the respective ranking indexes are, from high to low, the random inspection pass rate, the number of random inspections, and the quantity of materials. In other implementation manners, according to actual requirements, the quantity and / or priority of the respective ranking indexes can be adjusted, or other information can be selected as the ranking index, which is not limited herein.

[0081] In the first specific example, when the target random inspection dimension is the material category, classify the materials to be randomly inspected, that is, regard the materials to be randomly inspected with the same material category in the material information of the materials to be randomly inspected as one category to obtain the classification results. Then obtain the random inspection pass rate values, the number of random inspection values, and the quantity of material values of each type of material to be randomly inspected. Take the random inspection pass rate as the first index, the number of random inspections as the second index, and the quantity of materials as the third index, and sort each category in ascending or descending order to obtain the first ranking result.

[0082] For example, referring to Figure 3 , the material categories of the materials to be randomly inspected include Category A, Category B, Category C, Category D, and Category E. For the materials to be randomly inspected in Category A, which include 100 materials to be randomly inspected and their material information, the total number of random inspections and the total random inspection pass rate in the 100 pieces of material information are obtained, and the number of materials is 100. Similarly, the number of materials, the total number of random inspections, and the total random inspection pass rate of Category B, Category C, Category D, and Category E are obtained. According to the random inspection pass rates of these five categories, they are sorted in ascending order. When the random inspection pass rates are the same, the number of random inspections is compared, and the one with a smaller number of random inspections is ranked higher, and the one with a larger number of random inspections is ranked lower. If the random inspection pass rates and the number of random inspections are both the same, then the number of materials is compared again, and the one with a smaller number of materials is ranked higher, and the one with a larger number of materials is ranked lower, obtaining the first sorting result, which is the ranking of different material categories. It can be understood that if the random inspection pass rates of these five categories are all different, the sorting can be completed according to the random inspection pass rates, and there is no need to compare the number of random inspections and the number of materials. Similarly, if the sorting can be completed according to the random inspection pass rates and the number of random inspections, there is no need to compare the number of materials.

[0083] In the second specific example, when the target random inspection dimension is the supplier, the materials to be randomly inspected are classified, that is, the materials to be randomly inspected produced by the same supplier are regarded as one category, obtaining the classification result. Then, the random inspection pass rate value, the number of random inspections value, and the number of materials value of each category of materials to be randomly inspected are obtained. Taking the random inspection pass rate as the first index, the number of random inspections as the second index, and the number of materials as the third index, the materials to be randomly inspected in each category are sorted in ascending order or descending order, obtaining the first sorting result. At this time, the first sorting result obtained is the ranking of different suppliers.

[0084] In the third specific example, when the target random inspection dimension is the warehouse, the materials to be randomly inspected are classified, that is, the materials to be randomly inspected stored in the same warehouse are regarded as one category, obtaining the classification result. Then, the random inspection pass rate value, the number of random inspections value, and the number of materials value of each category of materials to be randomly inspected are obtained. Taking the random inspection pass rate as the first index, the number of random inspections as the second index, and the number of materials as the third index, the materials to be randomly inspected in each category are sorted in ascending order or descending order, obtaining the first sorting result. At this time, the first sorting result obtained is the ranking of different warehouses.

[0085] S103: According to the first sorting result, analyze the material information of the materials to be randomly inspected in the first sorting result to determine the random inspection probability corresponding to each value in the target random inspection dimension.

[0086] Furthermore, referring to Figure 4 , specifically including:

[0087] Based on the first sorting result, assign sampling weights to the materials to be sampled corresponding to each value in the target sampling dimension;

[0088] According to the sampling weights of the materials to be sampled corresponding to each value in the target sampling dimension, combined with the total sampling weight of the target sampling dimension, give the sampling probabilities corresponding to each value in the target sampling dimension.

[0089] In a specific implementation manner, according to the sorting method of the first sorting result, assign corresponding sampling weights to the materials to be sampled corresponding to each value in the target sampling dimension. If the first sorting result is an ascending order sorting, then according to the first sorting result, assign the sampling weights of the materials to be sampled corresponding to each value in the target sampling dimension in a descending order. If the first sorting result is a descending order sorting, then according to the first sorting result, assign the sampling weights of the materials to be sampled corresponding to each value in the target sampling dimension in an ascending order. According to the sampling weights of the materials to be sampled corresponding to each value in the target sampling dimension, combined with the total sampling weight of the target sampling dimension, give the sampling probabilities corresponding to each value in the target sampling dimension, where the sampling probability is the quotient of the sampling weight of the materials to be sampled corresponding to each value in the target sampling dimension and the total sampling weight of the target sampling dimension.

[0090] For example, taking the material category of the materials to be sampled as the target sampling dimension, the first sorting result obtained by ascending order sorting is category A, category B, category C, category D, and category E. Therefore, when assigning sampling weights, assign them in a descending order. Then the sampling weight corresponding to the sampling materials of category A is 5, the sampling weight corresponding to the sampling materials of category B is 4, the sampling weight corresponding to the sampling materials of category C is 3, the sampling weight corresponding to the sampling materials of category D is 2, and the sampling weight corresponding to the sampling materials of category E is 1. Among them, the sampling weight is a function related to the ranking, that is, W = f(i), and different weights can also be set to log1, log2, log3, log4, log5, which is not limited here. Calculate the sampling probabilities of different material categories. Then the sampling probability corresponding to the sampling materials of category A is 5 / (5 + 4 + 3 + 2 + 1) = 1 / 3, the sampling weight corresponding to the sampling materials of category B is 4 / (5 + 4 + 3 + 2 + 1) = 4 / 15, the sampling weight corresponding to the sampling materials of category C is 3 / (5 + 4 + 3 + 2 + 1) = 1 / 5, the sampling weight corresponding to the sampling materials of category D is 2 / (5 + 4 + 3 + 2 + 1) = 2 / 15, and the sampling weight corresponding to the sampling materials of category E is 1 / (5 + 4 + 3 + 2 + 1) = 1 / 15.

[0091] S104: Obtain the sampling threshold corresponding to the target sampling dimension, and combined with the sampling probabilities corresponding to each value in the target sampling dimension, sample the materials to be sampled to obtain the first set of materials to be sampled.

[0092] For example, if the sampling threshold is 3, it means that at least three material categories need to be sampled. Different target sampling dimensions correspond to different sampling thresholds. For example, when the target sampling dimension is the supplier, the corresponding sampling threshold is 10, which means that the materials of at least 10 suppliers need to be sampled. When the target sampling dimension is the warehouse, the corresponding sampling threshold is 30, which means that the materials stored in at least 30 warehouses need to be sampled.

[0093] In a specific example, taking the material category as the target sampling dimension and the sampling threshold as 3, at least three categories need to be selected for sampling from the five material categories of A, B, C, D, and E.

[0094] Combined with the sampling probabilities corresponding to each value in the target sampling dimension, the materials to be sampled are sampled to obtain the first set of materials to be sampled. Specifically, based on the sampling probabilities corresponding to each value in the target sampling dimension and integrating the sampling function, a sampling function value is generated, and the materials to be sampled are sampled to obtain the first set of materials to be sampled. The sampling function value includes a first random value and a second random value.

[0095] Among them, integrating the sampling function, generating a sampling function value, and sampling the materials to be sampled to obtain the first set of materials to be sampled specifically include:

[0096] Determine the random value intervals corresponding to each value in the target sampling dimension;

[0097] Taking into account the sampling probabilities corresponding to each value in the target sampling dimension, obtain the first random value, and through the judgment of the random value intervals corresponding to each value in the target sampling dimension, determine the corresponding value of the target sampling dimension;

[0098] Under the determined value of the target sampling dimension, generate a corresponding second random number for each material information, sort the sizes of each second random number, and extract a preset number of material information from the sorting;

[0099] Until the extracted material information meets the sampling threshold of the target sampling dimension, form the first set of materials to be sampled.

[0100] Among them, the preset quantity of material information is determined by the quantity of materials under the value of the target sampling dimension. The preset quantity of the extracted material information under the value of each target sampling dimension is different and is positively correlated with the quantity of materials under the value of the target sampling dimension. It can be a proportional relationship or other relationships. Based on the sampling probabilities corresponding to each value in the target sampling dimension, a sampling function is constructed. For example, a sampling function can be constructed with a random number whose value range is a positive integer [1, 15]. When the first random number is within the range of [1, 5], a second random number is generated and sorted for the material information corresponding to category A, and a preset quantity of material information is extracted from the sorting into the first set of materials to be sampled. When the first random number is within the range of [6, 9], a second random number is generated and sorted for the material information corresponding to category B, and a preset quantity of material information is extracted from the sorting into the first set of materials to be sampled. When the first random number is within the range of [10, 12], a second random number is generated and sorted for the material information corresponding to category C, and a preset quantity of material information is extracted from the sorting into the first set of materials to be sampled. When the first random number is within the range of [13, 14], a second random number is generated and sorted for the material information corresponding to category D, and a preset quantity of material information is extracted from the sorting and added to the first set of materials to be sampled. When the first random number is 15, a second random number is generated and sorted for the material information corresponding to category E, and a preset quantity of material information is extracted from the sorting and added to the first set of materials to be sampled. The sampling function can be executed multiple times until the sampling requirements of the sampling threshold are completed. Of course, in other embodiments, other methods can also be used to construct the sampling function to complete the construction of the first set of materials to be sampled, and this is not limited herein.

[0101] S105: Combine the priorities of the secondary sampling dimensions corresponding to the target sampling dimension to screen the first set of materials to be sampled, obtain the target materials to be sampled, and complete the task creation for the target materials to be sampled.

[0102] Refer to Figure 5 , specifically including:

[0103] Based on the priorities of the secondary sampling dimensions corresponding to the target sampling dimension, determine the priority levels of each secondary sampling dimension;

[0104] Based on the secondary sampling dimension of the current priority level, sort the intermediate screening results given by the secondary sampling dimension of the previous priority level to obtain an intermediate sorting result, where the intermediate screening results given by the secondary sampling dimension of the previous priority level include the first set of materials to be sampled;

[0105] According to the intermediate sorting result, analyze the material information of the materials to be sampled in the intermediate sorting result to determine the sampling probabilities corresponding to each value in the secondary sampling dimension of the current priority level;

[0106] Analyze the sampling probabilities corresponding to each value in the secondary sampling dimension of the current priority level, screen each material to be sampled in the intermediate sorting result, and obtain the intermediate screening result;

[0107] Until the screening under the secondary sampling dimensions of all priority levels is completed, give the target materials to be sampled and complete the task creation for the target materials to be sampled.

[0108] In a specific implementation manner, the secondary sampling dimension includes material category, supplier, warehouse, testing institution, sampling personnel, and sample delivery personnel. In the implementation manner provided by the present invention, the priority levels of the secondary sampling dimensions are, from high to low, material category, supplier, warehouse, testing institution, sampling personnel, and sample delivery personnel, and each secondary sampling dimension is obtained in sequence.

[0109] First, obtain the first secondary sampling dimension. At this time, the first secondary sampling dimension is the secondary sampling dimension of the current priority level, and the secondary sampling dimension of the previous priority level is the target sampling dimension. Sort the first set of materials to be sampled based on the first secondary sampling dimension to obtain the intermediate sorting result. Then analyze the material information of the materials to be sampled in the intermediate sorting result, determine the sampling probabilities corresponding to each value in the secondary sampling dimension, and screen each material to be sampled in the intermediate sorting result based on different sampling probabilities to obtain the intermediate screening result. Then obtain the second secondary sampling dimension. At this time, the second sampling dimension is the secondary sampling dimension of the current priority level, and the secondary sampling dimension of the previous priority level is the first secondary sampling dimension. Perform the above sorting and screening processes on the intermediate screening result obtained from the first secondary sampling dimension to obtain a new intermediate screening result until the intermediate screening result corresponding to the last secondary sampling dimension is obtained, that is, the screening of all priority levels of the secondary sampling dimensions is completed. The materials to be sampled in the intermediate screening result corresponding to the last priority level of the secondary sampling dimension are used as the target materials to be sampled, and the task creation for the target materials to be sampled is completed.

[0110] In the first specific example, when the target sampling dimension is the material category, the secondary sampling dimension includes the supplier, warehouse, testing institution, sampling personnel, and sample delivery personnel, and the priority levels of the secondary sampling dimensions are, from high to low, the supplier, warehouse, testing institution, sampling personnel, and sample delivery personnel.

[0111] Refer to Figure 6, first obtain the suppliers, and sort the first set of materials to be sampled based on the suppliers to obtain an intermediate sorting result. Then analyze the material information of the materials to be sampled in the intermediate sorting result, determine the sampling probabilities corresponding to different suppliers, and screen each material to be sampled in the intermediate sorting result based on the different sampling probabilities to obtain an intermediate screening result. Next, obtain the warehouses, continue to sort the intermediate screening result obtained from the suppliers, determine the sampling probabilities corresponding to different warehouses, and screen based on the different sampling probabilities to obtain a new intermediate screening result. Then, based on the new intermediate screening result, sort the testing institutions that can complete the testing tasks of the materials to be sampled in the new intermediate screening result, and match suitable testing institutions. After determining the testing institutions, then determine the sampling personnel and sample delivery personnel for the materials to be sampled among the materials to be sampled for which the testing institutions have been determined, that is, complete the screening for each secondary sampling dimension. Take the materials to be sampled in the intermediate screening result corresponding to the sampling personnel and sample delivery personnel as the target materials to be sampled, and complete the task creation for the target materials to be sampled. Among them, the material to be sampled 1 in each sorting is the material to be sampled ranked first in each sorting, and does not specifically refer to the same material to be sampled, and n0≥n1≥n2≥n3.

[0112] In the second specific example, when the target sampling dimension is the supplier, the secondary sampling dimensions include material category, warehouse, testing institution, sampling personnel, and sample delivery personnel. The priority levels of the secondary sampling dimensions are, from high to low, material category, warehouse, testing institution, sampling personnel, and sample delivery personnel.

[0113] First obtain the material category, and sort the first set of materials to be sampled based on the material category to obtain an intermediate sorting result. Then analyze the material information of the materials to be sampled in the intermediate sorting result, determine the sampling probabilities corresponding to different material categories, and screen each material to be sampled in the intermediate sorting result based on the different sampling probabilities to obtain an intermediate screening result. Next, obtain the warehouses, continue to sort the intermediate screening result obtained from the material category, determine the sampling probabilities corresponding to different warehouses, and screen based on the different sampling probabilities to obtain a new intermediate screening result, until obtaining the intermediate screening result corresponding to the sample delivery personnel, that is, complete the screening for each secondary sampling dimension. Take the materials to be sampled in the intermediate screening result corresponding to the sample delivery personnel as the target materials to be sampled, and complete the task creation for the target materials to be sampled.

[0114] In the third specific example, when the target sampling dimension is the warehouse, the secondary sampling dimensions include supplier, material category, testing institution, sampling personnel, and sample delivery personnel. The priority levels of the secondary sampling dimensions are, from high to low, supplier, material category, testing institution, sampling personnel, and sample delivery personnel.

[0115] First, obtain the suppliers and sort the first set of materials to be sampled based on the suppliers to obtain an intermediate sorting result. Then, analyze the material information of the materials to be sampled in the intermediate sorting result, determine the sampling probabilities corresponding to different suppliers, and filter each material to be sampled in the intermediate sorting result based on the different sampling probabilities to obtain an intermediate filtering result. Next, obtain the material categories, continue to sort the intermediate filtering result obtained for the suppliers, determine the sampling probabilities corresponding to different material categories, and perform filtering based on the different sampling probabilities to obtain a new intermediate filtering result until the intermediate filtering result corresponding to the sample delivery personnel is obtained, that is, filtering is completed for each sampling dimension. The materials to be sampled in the intermediate filtering result corresponding to the sample delivery personnel are used as the target materials to be sampled, and the task creation for the target materials to be sampled is completed.

[0116] Further, referring to Figure 7 , based on the sampling dimension at the current priority level, sort the intermediate filtering result given by the sampling dimension at the previous priority level to obtain an intermediate sorting result, specifically including:

[0117] Obtain the sampling dimension and corresponding sampling indicators at the current priority level, and combine the material information of the materials to be sampled in the intermediate filtering result to obtain the sampling indicator values of the materials to be sampled for each sampling indicator;

[0118] Based on the sampling indicator values of each type of material to be sampled for each sampling indicator, combine the balance thresholds corresponding to different sampling indicators, and judge the sampling indicator values and the balance thresholds corresponding to the sampling indicators to obtain a judgment result;

[0119] Analyze the judgment result, sort the materials to be sampled in the intermediate filtering result to obtain an intermediate sorting result.

[0120] In a specific implementation manner, the sampling indicators corresponding to different sampling dimensions are different. Taking the suppliers as an example, the corresponding sampling indicators are the quantity of materials, the number of samplings, and the sampling qualification rate. It is necessary to judge the quantity of materials, the number of samplings, and the sampling qualification rate of each supplier. If the quantity of materials of multiple suppliers all reach the balance threshold corresponding to the quantity of materials, and the number of samplings all reach the balance threshold corresponding to the number of samplings, and the sampling qualification rate all reach the balance threshold corresponding to the number of samplings, then the rankings of the multiple suppliers are tied rankings, and an intermediate sorting result is obtained.

[0121] By setting the balance threshold to affect the sorting result, it is possible to avoid the situation where the task conditions for sampling task selection are the same for a long time, resulting in unreasonable sampling tasks, and at the same time, it can also promote the healthy development of the sampling process.

[0122] In the embodiments provided by the present invention, when the secondary sampling dimension is a warehouse or a material category, the corresponding secondary sampling indicators are the quantity of materials, the number of sampling times, and the sampling qualification rate. When the secondary sampling dimension is an experimental institution, the corresponding secondary sampling indicators are the distance from the warehouse to each experimental institution and the task volume of the experimental institution. When the secondary sampling dimension is a sampling personnel or a sample delivery personnel, the corresponding secondary sampling indicators are the time matching degree of the sampling personnel or the sample delivery personnel in the experimental institution and the task volume of the sampling task or the sample delivery task of the sampling personnel or the sample delivery personnel. In other embodiments, when the personnel in the experimental institution are limited, suitable sampling personnel or sample delivery personnel can be directly matched from the corresponding experimental institution without ranking, and there are no corresponding secondary sampling indicators at this time.

[0123] In a specific example, in any sorting process during task creation, including sorting processes based on material categories, suppliers, warehouses, experimental institutions, etc., a balance threshold will be set during ranking. When all secondary sampling indicators in the secondary sampling dimension are higher than the corresponding balance threshold, the ranking positions will be the same. For example, when ranking suppliers, there are two or more suppliers, and the secondary sampling indicators of the quantity of materials, the number of sampling times, and the sampling qualification rate are all higher than the corresponding balance threshold. The above two or more suppliers will be ranked equally.

[0124] Further, referring to Figure 8 , the balance threshold is specifically obtained through the following steps:

[0125] According to the value state distribution of different secondary sampling indicators, combined with the preset sampling ratio, determine the first threshold corresponding to each secondary sampling indicator, where the first threshold is selected from the values of the corresponding secondary sampling indicator;

[0126] Based on the preset adjustment coefficient, adjust the first threshold corresponding to each secondary sampling indicator respectively to obtain the balance threshold corresponding to each secondary sampling indicator.

[0127] In a specific embodiment, the value state distribution of the secondary sampling index is a normal distribution. In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, approximately 95% of the data falls within two standard deviations of the mean, and approximately 99.7% of the data falls within three standard deviations of the mean. When the preset sampling ratio is 50%, the first threshold given needs to ensure that 50% of the data falls within the value state distribution section of the secondary sampling index delimited by this first threshold. For example, the value range of a certain secondary sampling index is 0 - 100 and conforms to a normal distribution. The first threshold is selected as 50, and 50% of the data of the secondary sampling index falls within the range of 50 - 100. The adjustment coefficient is used to adjust the first threshold, and the adjustment coefficients in different scenarios can be different. It can be understood that for each secondary sampling dimension, there may be multiple secondary sampling indexes. If the first threshold is determined based on the sampling ratio, the final number of samples to be inspected will be less than the preset sampling ratio. Therefore, the range corresponding to the first threshold needs to be appropriately enlarged to ensure that when there are multiple secondary sampling indexes in the secondary sampling dimension, the final number of materials to be inspected meets the requirements of the sampling ratio. In the example provided by the present invention, the adjustment coefficient is the adjustment proportion corresponding to each secondary sampling index. For example, the adjustment coefficient is 10%. When there is 1 secondary sampling index, only the first threshold needs to be adjusted by 10%. When there are 2 secondary sampling indexes, the first threshold needs to be adjusted by 10% * 2 = 20%, and so on. When there is one secondary sampling index, the above first threshold is adjusted to 50 * (1 - 10%) = 45, that is, the balance threshold is 45. When there are two secondary sampling indexes, the above first threshold is adjusted to 50 * (1 - 20%) = 40, that is, the balance threshold is 40. In this way, the data falling within the range of the inspection target index 40 - 100 is increased.

[0128] Referring to Figure 9 , the embodiment of the present invention provides a device for creating a power material sampling inspection task, including:

[0129] A data acquisition module 201, configured to acquire the material information of the materials to be inspected;

[0130] A material sorting module 202, configured to sort the materials to be inspected based on the target sampling dimension, in combination with the material information of the materials to be inspected and the priorities of each sorting index, to obtain a first sorting result;

[0131] A probability determination module 203, configured to analyze the material information of the materials to be inspected in the first sorting result according to the first sorting result, and determine the sampling probabilities corresponding to each value in the target sampling dimension;

[0132] The sampling inspection determination module 204 is configured to obtain the sampling inspection threshold corresponding to the target sampling inspection dimension, combine the sampling inspection probabilities corresponding to each value in the target sampling inspection dimension, perform sampling inspection on the materials to be sampled, and obtain the first set of materials to be sampled;

[0133] The task creation module 205 is configured to screen the first set of materials to be sampled in combination with the priority of the secondary sampling inspection dimension corresponding to the target sampling inspection dimension, obtain the target materials to be sampled, and complete the task creation for the target materials to be sampled.

[0134] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the described modules can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0135] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be construed as including the preferred embodiments and all changes and modifications falling within the scope of the present invention. Obviously, those skilled in the art can make various changes and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A method for creating a power material sampling task, characterized in that: include: Obtain material information of materials to be sampled; Based on the target sampling dimension, the materials to be sampled are sorted according to the material information of the materials to be sampled and the priority of each sorting index to obtain a first sorting result; According to the first sorting result, the material information of the materials to be sampled in the first sorting result is analyzed to determine the sampling probability corresponding to each value in the target sampling dimension; Obtain the sampling threshold of the corresponding target sampling dimension, and perform sampling inspection on the materials to be sampled based on the sampling probability corresponding to each value in the target sampling dimension to obtain the first set of materials to be sampled; Combined with the priority of the secondary sampling dimension corresponding to the target sampling dimension, the first set of materials to be sampled is screened to obtain the target materials to be sampled and complete the task creation for the target materials to be sampled.

2. The method for creating a power material sampling task according to claim 1, characterized in that: Based on the target sampling dimension, combined with the material information of the materials to be sampled and the priority of each sorting index, the materials to be sampled are sorted to obtain the first sorting result, which specifically includes: According to the target sampling dimension and the material information of the materials to be sampled, the materials to be sampled are classified to obtain the classification results; Based on the classification results, obtain the ranking index values ​​of each type of materials to be sampled in each ranking index; According to the ranking index values ​​of each category of materials to be sampled in each ranking index, the various categories of materials to be sampled are sorted to obtain a first sorting result.

3. The method for creating a power material sampling task according to claim 1, characterized in that: According to the first sorting result, the material information of the materials to be sampled in the first sorting result is analyzed to determine the sampling probability corresponding to each value in the target sampling dimension, specifically including: Based on the first sorting result, assigning sampling weights to the materials to be sampled corresponding to each value in the target sampling dimension; According to the sampling weights of the materials to be sampled corresponding to each value in the target sampling dimension, combined with the total sampling weight of the target sampling dimension, the sampling probability corresponding to each value in the target sampling dimension is given.

4. The method for creating a power material sampling task according to claim 1, characterized in that: Obtain the sampling threshold of the corresponding target sampling dimension, combine the sampling probabilities corresponding to the values ​​in the target sampling dimension, perform sampling inspection on the materials to be sampled, and obtain the first set of materials to be sampled, which specifically includes: Based on the inspection probability corresponding to each value in the target inspection dimension and integrating the pre-built inspection function, the inspection function value is generated to inspect the materials to be inspected until the inspection threshold of the target inspection dimension is met, thereby obtaining the first set of materials to be inspected.

5. The method for creating a power material sampling task according to claim 4, characterized in that: The sampling function is integrated to generate the sampling function value, and the materials to be sampled are sampled to obtain the first set of materials to be sampled, which specifically includes: Determine the random value interval corresponding to each value in the target sampling dimension; Taking into account the sampling probability corresponding to each value in the target sampling dimension, a first random value is obtained, and the value of the corresponding target sampling dimension is determined by judging the random value interval corresponding to each value in the target sampling dimension; Under the determined value of the target sampling dimension, a corresponding second random number is generated for each piece of material information, and each second random number is sorted by size, and a preset number of material information is extracted from the sort; Until the extracted material information meets the sampling threshold of the target sampling dimension, the first set of materials to be sampled is formed. Among them, the preset quantity of material information is determined by the quantity of materials under the value of the target sampling dimension.

6. The method for creating a power material sampling task according to claim 1, characterized in that: Combined with the priority of the secondary sampling dimension corresponding to the target sampling dimension, the first set of materials to be sampled is screened to obtain the target materials to be sampled and complete the task creation for the target materials to be sampled, including: Based on the priority of the sub-sampling dimension corresponding to the target sampling dimension, determine the priority level of each sub-sampling dimension; Based on the secondary sampling dimension of the current priority level, the intermediate screening results given by the secondary sampling dimension of the previous priority level are sorted to obtain an intermediate sorting result, wherein the intermediate screening results given by the secondary sampling dimension of the previous priority level include the first set of materials to be sampled; According to the intermediate sorting results, the material information of the materials to be sampled in the intermediate sorting results is analyzed to determine the sampling probability corresponding to each value in the secondary sampling dimension of the current priority level; Analyze the sampling probability corresponding to each value in the secondary sampling dimension of the current priority level, screen each material to be sampled in the intermediate sorting result, and obtain the intermediate screening result; Until the screening under the secondary sampling dimensions of all priority levels is completed, the target materials to be sampled are given and the task creation for the target materials to be sampled is completed.

7. The method for creating a power material sampling task according to claim 5, characterized in that: Based on the sub-sampling dimension of the current priority level, the intermediate screening results given by the sub-sampling dimension of the previous priority level are sorted to obtain the intermediate sorting results, which specifically include: Get the sub-sampling dimension and corresponding sub-sampling index of the current priority level, and combine the material information of the materials to be sampled in the intermediate screening results to obtain the sub-sampling index values ​​of the materials to be sampled in each sub-sampling index; Based on the sub-sampling index values ​​of each type of materials to be sampled in each sub-sampling index, combined with the balance thresholds corresponding to different sub-sampling indexes, the sub-sampling index values ​​and the balance thresholds corresponding to the sub-sampling indexes are judged to obtain a judgment result; Analyze and judge the results, sort the materials to be sampled in the intermediate screening results, and obtain the intermediate sorting results.

8. The method for creating a power material sampling task according to claim 6, characterized in that: The balance threshold is obtained through the following steps: According to the value state distribution of the sampling indicators of different times, combined with the preset sampling ratio, the first threshold corresponding to each sampling indicator is determined, wherein the first threshold is selected from the value of the corresponding sampling indicator; Based on the preset adjustment coefficient, the first threshold corresponding to each sub-sampling indicator is adjusted respectively to obtain the balance threshold corresponding to each sub-sampling indicator.

9. The method for creating a power material sampling task according to claim 1, characterized in that: The ranking index includes at least one of the sampling inspection pass rate, the number of sampling inspections and the quantity of materials.

10. A device for creating a power material sampling task, characterized in that: The method for creating a power material sampling task according to any one of claims 1 to 9 comprises: A data acquisition module is used to obtain material information of materials to be sampled; The material sorting module is used to sort the materials to be inspected based on the target inspection dimension, combined with the material information of the materials to be inspected and the priority of each sorting index, to obtain a first sorting result; A probability determination module, used to analyze the material information of the materials to be sampled in the first sorting result according to the first sorting result, and determine the sampling probability corresponding to each value in the target sampling dimension; The sampling inspection determination module is used to obtain the sampling inspection threshold value corresponding to the target sampling inspection dimension, and to perform sampling inspection on the materials to be sampled in combination with the sampling inspection probabilities corresponding to the values ​​in the target sampling inspection dimension, so as to obtain the first set of materials to be sampled; The task creation module is used to screen the first set of materials to be inspected in combination with the priority of the secondary inspection dimension corresponding to the target inspection dimension, obtain the target materials to be inspected and complete the task creation for the target materials to be inspected.

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