Method for detecting drawing on factory-entering iron alloy wire

Abstract

The invention relates to a factory-entering iron alloy on-line drawing detection method, which comprises the following steps of: acquiring bag number information of a certain batch of raw materials, and inputting the bag number information into a system; the number of bags needing to be detected is calculated according to the total bag number; randomly generating serial numbers of the bags needing to be detected according to the number of the bags needing to be detected and the serial number of each bag; the raw materials in the corresponding bags are detected according to the serial numbers of the bags needing to be detected; judging the batch of raw materials according to the detection result, wherein the judgment result comprises qualification, rechecking and returning; the system automatically generates serial numbers of bags needing to be detected, so that the detection randomness is ensured; detection personnel perform detection work under the guidance of the system, so that communication between the detection personnel and technical personnel is reduced, and the detection efficiency is improved; compared with manual judgment, the process of judging the batch of raw materials by the system according to the detection result is higher in efficiency and less prone to errors.

Description

Technical Field

[0001] This invention relates to the field of raw material testing technology, and in particular to an online random sampling testing method for incoming ferroalloys. Background Technology

[0002] With the continuous development of information technology, the dissemination of various information technologies has become increasingly convenient and rapid. However, given the current pattern of "traditional manual labor as the mainstay, mechanization upgrades accelerated, and intelligent pilot breakthroughs" in the inspection of bulk raw materials in steel plants, and the fierce competition in the steel market, especially the higher requirements for the timeliness of the transmission and settlement of bulk raw material inspection results, the existing traditional methods of generating, entering, and transmitting data information based on manual on-site operations urgently need to be "upgraded and changed".

[0003] Currently, most ferroalloy testing is conducted by employees randomly selecting samples on-site or by superiors assigning them. This testing method not only presents the problem of human intervention in the test results, but also requires frequent communication between testing personnel and technicians during the testing process, resulting in very low testing efficiency. For example, testing personnel need to send the test results to relevant technicians, who then determine whether a retest is needed, or whether the product should be put into storage or returned.

[0004] Therefore, it is necessary to propose an online random sampling inspection method for incoming ferroalloys to solve or at least alleviate the above-mentioned defects. Summary of the Invention

[0005] The main objective of this invention is to provide a method for random sampling inspection of incoming ferroalloys on an online inspection line, in order to solve the problems in the prior art.

[0006] To achieve the above objectives, the present invention provides a method for random sampling inspection of incoming ferroalloys on an online inspection line, comprising the following steps:

[0007] S1, Obtain the bag number information of a certain batch of raw materials, and enter the bag number information into the system; the bag number information includes the total number of bags and the number of each bag;

[0008] S2, calculate the number of bags that need to be inspected based on the total number of bags. The calculation formula is as follows: Where, n 检 Let n be the number of bags that need to be inspected, and when n 检 If the value is not an integer, round it up to the nearest integer; n 总 Let k be the total number of bags, and k be the detection coefficient.

[0009] S3, Based on the number of bags to be tested and the number of each bag, randomly generate the number of the bags to be tested, and the number of the number of the bags to be tested is equal to the number of bags to be tested;

[0010] S4. According to the number of the bag to be tested, test the raw materials in the corresponding bag and enter the test results into the system;

[0011] S5, the batch of raw materials is judged based on the test results, and the judgment results include qualified, re-inspection, and return;

[0012] S6, when the judgment result is re-inspection, return to step S1 and regenerate the re-inspection bag number information; wherein, compared with the bag number information, the re-inspection bag number information reduces the number of bags that have already been inspected and updates the total number of bags; when the judgment result is qualified, all raw materials in the batch are put into storage; when the judgment result is return, all raw materials in the batch are returned to the supplier.

[0013] Preferably, the number of bags to be tested in step S2 includes the number of bags to be tested for chemical composition and the number of bags to be tested for particle size; wherein the number of bags to be tested for chemical composition is greater than or equal to the number of bags to be tested for particle size; the calculation formula is as follows: Where, n 检1 For the number of bags that need to be tested for chemical composition, and when n 检1 If the value is not an integer, round it up to the nearest integer; n 检2 For the number of bags that need to be particle size measured, and when n 检2 If the value is not an integer, round it up to the nearest integer; n 总 K is the total number of bags, k1 is the chemical composition detection coefficient, and k2 is the particle size detection coefficient.

[0014] Preferably, step S3 specifically includes the following steps:

[0015] S31, Based on the required number of bags for chemical composition testing, randomly generate the number of bags that need to be tested for chemical composition.

[0016] S32, based on the required number of particle size testing bags, randomly generate the number of the bags to be tested for particle size again from the randomly generated number of the bags to be tested for chemical composition.

[0017] Preferably, the detection results in step S5 include chemical composition detection results and particle size detection results; step S5 specifically includes the following steps:

[0018] S51, Calculate the CPK values ​​of all indicators based on the chemical composition detection results;

[0019] S52, the particle size detection result includes the proportion of defective particles;

[0020] S53 determines the minimum CPK value and the proportion of defective particles, and the determination results include qualified, re-inspection, and return.

[0021] Preferably, in step S53,

[0022] Once both the minimum CPK value and the percentage of defective particles are deemed acceptable, the product is put into storage.

[0023] If either the minimum CPK value or the proportion of defective particles results in a return, then the product is returned.

[0024] When the minimum CPK value is determined to be qualified and the proportion of defective particles is determined to be re-inspected, then return to step S1 and perform particle size detection again.

[0025] When the minimum CPK value is determined to be re-inspected and the particle size defect rate is determined to be qualified, the process returns to step S1 and the chemical composition is tested again.

[0026] If both the minimum CPK value and the proportion of defective particles are determined to be re-inspected, then return to step S1 and repeat particle size and chemical composition testing.

[0027] Preferably, the raw materials need to be pretreated before particle size detection, wherein the pretreatment includes crushing and grinding.

[0028] Preferably, the formula for calculating the CPK value is as follows: Where min represents the minimum value, USL is the maximum value in the technical indicator, and LSL is the minimum value in the technical indicator. X is the sample mean, σ is the sample standard deviation, n represents the sample size, and X i Let be the data for the i-th sample.

[0029] Preferably, in step S53, the minimum CPK value is determined, and the determination method is as follows:

[0030] Compare all CPK values ​​and take the smallest CPK value;

[0031] When the minimum CPK value is greater than or equal to the first preset CPK value, the result is deemed qualified.

[0032] When the minimum CPK value is less than the first preset CPK value and greater than or equal to the second preset CPK value, the determination result is a re-inspection;

[0033] When the minimum CPK value is less than the second preset CPK value, the result is a return.

[0034] Preferably, in step S53, the determination of the proportion of defective products in terms of particle size is carried out as follows:

[0035] Obtain the proportion of defective products in terms of particle size, where the proportion of defective products in terms of particle size includes the proportion of defective products greater than the preset upper limit and the proportion of defective products less than the preset lower limit;

[0036] When the proportion of defective products greater than the preset upper limit is less than the first preset upper limit proportion value of defective products and the proportion of defective products less than the preset lower limit is less than the first preset lower limit proportion value of defective products, it is determined as qualified;

[0037] When the proportion of defective products greater than the preset upper limit is greater than the second preset upper limit proportion value of defective products or the proportion of defective products less than the preset lower limit is greater than the second preset lower limit proportion value of defective products, it is determined as a return;

[0038] When the proportion of defective products greater than the preset upper limit is greater than or equal to the first preset upper limit proportion value of defective products and less than or equal to the second preset upper limit proportion value of defective products, and the proportion of defective products less than the preset lower limit is less than or equal to the second preset lower limit proportion value of defective products, re-inspection is carried out;

[0039] When the proportion of defective products less than the preset lower limit is greater than or equal to the first preset lower limit proportion value of defective products and less than or equal to the second preset lower limit proportion value of defective products, and the proportion of defective products greater than the preset upper limit is less than or equal to the second preset upper limit proportion value of defective products, re-inspection is carried out.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] (1) The system will automatically generate the numbers of the bags to be detected, ensuring the randomness of detection and preventing the problem of artificial intervention in the detection process by the detection personnel;

[0042] (2) The detection personnel will carry out the detection work under the guidance of the system, reducing the communication between the detection personnel and the technical personnel and improving the detection efficiency;

[0043] (3) The process of the system determining the raw materials of this batch according to the detection results is more efficient and less error-prone compared with manual determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the structures shown in these drawings without creative efforts.

[0045] Figure 1 This is a schematic diagram of a process in one embodiment of the present invention;

[0046] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0047] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0049] In this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0050] Please see the appendix Figure 1 The present invention provides a method for random sampling inspection of incoming ferroalloys on an online inspection line, comprising the following steps:

[0051] S1. Obtain the bag number information of a certain batch of raw materials and enter the bag number information into the system; the bag number information includes the total number of bags and the number of each bag; specifically, if the bags do not have number information, the bags can be numbered on-site, with the numbers being 1 to n; at the same time, if the bags have number information and the number is very long, the bags can be renumbered, with the numbers being 1 to n; in addition, in order to facilitate subsequent quality management, it is also necessary to enter the batch number of the raw materials and the manufacturer information into the system.

[0052] S2, calculate the number of bags that need to be inspected based on the total number of bags. The calculation formula is as follows: Where, n 检 Let n be the number of bags that need to be inspected, and when n 检 If the value is not an integer, round it up to the nearest integer; n 总Let n be the total number of bags, and k be the detection coefficient. Specifically, staff need to set the detection coefficient K in the system. Let's assume the detection coefficient K is 3, meaning that 1 bag out of every 3 bags is selected for detection. Let's assume the total number of bags is n. 总 If the value is 20, then the number of bags to be tested is 20 / 3. Since the result will be a decimal, we round it up to the nearest integer. Therefore, the number of bags to be tested is 7.

[0053] S3. Based on the number of bags to be tested and the number of each bag, randomly generate the number of bags to be tested, and the number of the number of bags to be tested is equal to the number of bags to be tested. Specifically, assuming there are 20 bags in total, and their numbers are 1 to 20, and 7 bags need to be tested, then the system will randomly output 7 numbers from numbers 1 to 20; the bags corresponding to these 7 numbers are the numbers of the bags to be tested.

[0054] S4. Based on the number of the bag to be tested, the raw materials inside the corresponding bag are tested, and the test results are entered into the system. Specifically, the system will automatically generate the items to be tested, and the testing personnel need to input all the test data into the system. It should be noted that the test data can be manually entered or the test data can be directly uploaded by the testing equipment. In addition, in order to ensure the accuracy of the test data, the data uploaded to the system needs to be checked by at least one other testing personnel.

[0055] S5, based on the test results, determines the batch of raw materials, with results including qualified, re-inspected, or returned. Specifically, once all data is uploaded, the system will automatically determine the order based on the test results. It should be noted that if the data uploaded by the inspector is insufficient, the system will not perform the ranking and will prompt the inspector that data is missing. That is, assuming a total of 7 bags of test data are needed, if the inspector only uploads data for 6 bags, the system will indicate that one bag of test data is missing. Furthermore, administrators can set the number of test data sets required for each bag; for example, if the administrator sets 3 sets of data per bag, then the inspector needs to take 3 samples from each bag for testing.

[0056] S6, when the judgment result is re-inspection, return to step S1 and regenerate the re-inspection bag number information; wherein, compared with the bag number information, the re-inspection bag number information is reduced by the number of bags that have already been inspected, and the total number of bags is updated; when the judgment result is qualified, all raw materials in this batch are put into storage; when the judgment result is return, all raw materials in this batch are returned to the supplier. Specifically, when the judgment result is re-inspection, the system will automatically remove the bags that have already been inspected and re-inspect the other bags that have not been inspected.

[0057] The advantages of adopting the proposed solution are as follows:

[0058] (1) The system will automatically generate the number of the bags that need to be tested, ensuring the randomness of the test and preventing human intervention in the testing process by the testers;

[0059] (2) The testing personnel will carry out the testing work under the guidance of the system, which reduces the communication between the testing personnel and the technical personnel and improves the efficiency of the testing;

[0060] (3) The process of the system judging the batch of raw materials based on the test results is more efficient and less prone to error than human judgment.

[0061] In a preferred embodiment, the number of bags to be tested in step S2 includes the number of bags to be tested for chemical composition and the number of bags to be tested for particle size; wherein the number of bags to be tested for chemical composition is greater than or equal to the number of bags to be tested for particle size; the calculation formula is as follows. Where, n 检1 For the number of bags that need to be tested for chemical composition, and when n 检1 If the value is not an integer, round it up to the nearest integer; n 检2 For the number of bags that need to be particle size measured, and when n 检2 If the value is not an integer, round it up to the nearest integer; n 总 Let k1 be the total number of bags, k2 be the chemical composition detection coefficient, and k3 be the particle size detection coefficient. Specifically, for ferroalloy raw materials, the testing items include chemical composition detection and particle size detection. Chemical composition detection typically uses equipment such as infrared carbon-sulfur analyzers, ICP spectrometers, and X-ray fluorescence spectrometers, while particle size detection is usually performed by sieving. Furthermore, for a batch of ferroalloy raw materials, it is necessary to perform chemical composition testing on a large number of bags, but only particle size testing on a small number of bags.

[0062] In a preferred embodiment, step S3 specifically includes the following steps:

[0063] S31, Based on the required number of bags for chemical composition testing, randomly generate the number of bags that need to be tested for chemical composition.

[0064] S32, based on the required number of bags for particle size testing, randomly generate a number for the bags requiring chemical composition testing from the previously randomly generated numbering list. Specifically, since the number of bags requiring chemical composition testing is greater than the number requiring particle size testing, to simplify the testing process, simply select the bags requiring particle size testing from the bags requiring chemical composition testing.

[0065] In a preferred embodiment, the detection results in step S5 include chemical composition detection results and particle size detection results; step S5 specifically includes the following steps:

[0066] S51, Calculate the CPK values ​​of all indicators based on the chemical composition detection results;

[0067] S52, the particle size detection result includes the proportion of defective particles;

[0068] S53 determines the minimum CPK value and the proportion of defective particles, with the results including acceptance, re-inspection, and return. Specifically, for ferroalloy raw materials, chemical composition testing generally includes silicon, carbon, phosphorus, and sulfur content. Therefore, at least four CPK values ​​need to be calculated: the CPK values ​​for silicon, carbon, phosphorus, and sulfur content. Particle size testing includes defective particles larger than the preset upper limit and smaller than the preset lower limit. For example, if the technical specifications set the particle size range to 10mm-50mm, particles larger than 50mm are considered defective (larger than the preset upper limit), and particles smaller than 10mm are considered defective (smaller than the preset lower limit).

[0069] In a preferred embodiment, in step S53...

[0070] Once both the minimum CPK value and the percentage of defective particles are deemed acceptable, the product is put into storage.

[0071] If either the minimum CPK value or the proportion of defective particles results in a return, then the product is returned.

[0072] When the minimum CPK value is determined to be qualified and the proportion of defective particles is determined to be re-inspected, then return to step S1 and perform particle size detection again.

[0073] When the minimum CPK value is determined to be re-inspected and the particle size defect rate is determined to be qualified, the process returns to step S1 and the chemical composition is tested again.

[0074] When the determination results of both the minimum CPK value and the proportion of defective products in terms of particle size are for re-inspection, return to step S1 and perform particle size detection and chemical composition detection again. Specifically, chemical composition detection and particle size detection are two different detection items. Therefore, it is necessary to make determinations for the two different detection items separately. Only when the results of both detection items are qualified can the product be warehoused. At the same time, as long as one detection item is determined as a return, a return is required. Also, if one detection item is qualified and the other is for re-inspection, only the item for re-inspection needs to be re-inspected.

[0075] As a preferred embodiment, before performing particle size detection, it is necessary to pre-treat the raw materials, and the pre-treatment includes crushing and grinding.

[0076] As a preferred embodiment, the calculation formula for the CPK value is where min represents taking the minimum value, USL is the maximum value in the technical specifications, LSL is the minimum value in the technical specifications, is the sample average value, σ is the sample standard deviation, n represents the sample size, and X i is the data of the i-th sample. It should be noted that this calculation formula for the CPK value is implanted into the system. Therefore, after the tester inputs all the data into the system, the system will automatically calculate the CPK value and input the corresponding number of CPK values according to the number of detection items. That is to say, after the tester inputs the silicon element content, carbon element content, phosphorus element content, and sulfur element content of all the detected raw materials, the system will automatically generate the CPK value of the silicon element content, the CPK value of the carbon element content, the CPK value of the phosphorus element content, and the CPK value of the sulfur element content.

[0077] As a preferred embodiment, in step S53, determine the minimum CPK value, and the determination method is as follows:

[0078] Compare all the CPK values and take the minimum CPK value;

[0079] When the minimum CPK value is greater than or equal to the first preset CPK value, the determination result is qualified;

[0080] When the minimum CPK value is less than the first preset CPK value and greater than or equal to the second preset CPK value, the determination result is for re-inspection;

[0081] When the minimum CPK value is less than the second preset CPK value, the determination result is for return.

[0082] Specifically, since the CPK values output by the system contain more than one, and when determining the result, only the minimum CPK value needs to be extracted for calculation. Suppose the CPK value of the silicon element content is 1.67, the CPK value of the carbon element content is 1.35, the CPK value of the phosphorus element content is 1.83, and the CPK value of the sulfur element content is 1.55. After comparison, the CPK value of the carbon element content is 1.35, which is the smallest among them. Therefore, when making a determination later, only the CPK value of 1.35 for the carbon element content needs to be compared. Among them, the first preset CPK value can be set to 1.67, and the second preset CPK value can be set to 1.33. At this time, if the minimum CPK value is greater than or equal to 1.67, it will be determined as qualified; if the minimum CPK value is less than 1.67 and greater than or equal to 1.33, it will be determined as re-inspection; if it is less than 1.33, it will be determined as return. Of course, the first preset CPK value and the second preset CPK value can also be set to other values according to the actual situation.

[0083] As a preferred embodiment, in the step S53, the proportion of defective products with abnormal particle size is determined, and the determination method is as follows:

[0084] Obtain the proportion of defective products with abnormal particle size, and the proportion of defective products with abnormal particle size includes the proportion of defective products greater than the preset upper limit and the proportion of defective products less than the preset lower limit;

[0085] When the proportion of defective products greater than the preset upper limit is less than the first preset upper limit value of defective products and the proportion of defective products less than the preset lower limit is less than the first preset lower limit value of defective products, it is determined as qualified;

[0086] When the proportion of defective products greater than the preset upper limit is greater than the second preset upper limit value of defective products or the proportion of defective products less than the preset lower limit is greater than the second preset lower limit value of defective products, it is determined as return;

[0087] When the proportion of defective products greater than the preset upper limit is greater than or equal to the first preset upper limit value of defective products and less than or equal to the second preset upper limit value of defective products, and the proportion of defective products less than the preset lower limit is less than or equal to the second preset lower limit value of defective products, it is re-inspected;

[0088] When the proportion of defective products less than the preset lower limit is greater than or equal to the first preset lower limit value of defective products and less than or equal to the second preset lower limit value of defective products, and the proportion of defective products greater than the preset upper limit is less than or equal to the second preset upper limit value of defective products, it is re-inspected.

[0089] Specifically, assume that the first preset upper limit defective product ratio value is 5%, the second preset upper limit defective product ratio value is 10%, the first preset lower limit defective product ratio value is 7%, and the second preset lower limit defective product ratio value is 10%; then when the ratio of defective products greater than the preset upper limit is less than 5% and the ratio of defective products less than the preset lower limit is less than 7%, it is determined to be qualified; when either the ratio of defective products greater than the preset upper limit or the ratio of defective products less than the preset lower limit is greater than 10%, then it is determined to be returned; for other types of ratios, it is determined to be re-inspected.

[0090] The above are only the preferred embodiments of the present invention, and do not limit the protection scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be included in the patent protection scope of the present invention by the same token.

Claims

1. A method for random sampling inspection of incoming ferroalloys on an in-plant production line, characterized in that, Includes the following steps: S1, Obtain the bag number information of a certain batch of raw materials, and enter the bag number information into the system; the bag number information includes the total number of bags and the number of each bag; S2, calculate the number of bags that need to be inspected based on the total number of bags. The calculation formula is as follows: Where, n 检 Let n be the number of bags that need to be inspected, and when n 检 If the value is not an integer, round it up to the nearest integer; n 总 Let k be the total number of bags, and k be the detection coefficient. S3, Based on the number of bags to be tested and the number of each bag, randomly generate the number of the bags to be tested, and the number of the number of the bags to be tested is equal to the number of bags to be tested; S4. According to the number of the bag to be tested, test the raw materials in the corresponding bag and enter the test results into the system; S5, the batch of raw materials is judged based on the test results, and the judgment results include qualified, re-inspection, and return; S6, when the judgment result is re-inspection, return to step S1 and regenerate the re-inspection bag number information; wherein, compared with the bag number information, the re-inspection bag number information reduces the number of bags that have already been inspected and updates the total number of bags; when the judgment result is qualified, all raw materials in the batch are put into storage; when the judgment result is return, all raw materials in the batch are returned to the supplier.

2. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 1, characterized in that, In step S2, the number of bags to be tested includes the number of bags to be tested for chemical composition and the number of bags to be tested for particle size; wherein the number of bags to be tested for chemical composition is greater than or equal to the number of bags to be tested for particle size; the calculation formula is as follows. Where, n 检1 For the number of bags that need to be tested for chemical composition, and when n 检1 If the value is not an integer, round it up to the nearest integer; n 检2 For the number of bags that need to be particle size measured, and when n 检2 If the value is not an integer, round it up to the nearest integer; n 总 K is the total number of bags, k1 is the chemical composition detection coefficient, and k2 is the particle size detection coefficient.

3. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 2, characterized in that, Step S3 specifically includes the following steps: S31, Based on the required number of bags for chemical composition testing, randomly generate the number of bags that need to be tested for chemical composition. S32, based on the required number of particle size testing bags, randomly generate the number of the bags to be tested for particle size again from the randomly generated number of the bags to be tested for chemical composition.

4. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 3, characterized in that, The detection results in step S5 include chemical composition detection results and particle size detection results; step S5 specifically includes the following steps: S51, Calculate the CPK values ​​of all indicators based on the chemical composition detection results; S52, the particle size detection result includes the proportion of defective particles; S53 determines the minimum CPK value and the proportion of defective particles, and the determination results include qualified, re-inspection, and return.

5. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 4, characterized in that, In step S53, Once both the minimum CPK value and the percentage of defective particles are deemed acceptable, the product is put into storage. If either the minimum CPK value or the proportion of defective particles results in a return, then the product is returned. When the minimum CPK value is determined to be qualified and the proportion of defective particles is determined to be re-inspected, then return to step S1 and perform particle size detection again. When the minimum CPK value is determined to be re-inspected and the particle size defect rate is determined to be qualified, the process returns to step S1 and the chemical composition is tested again. If both the minimum CPK value and the proportion of defective particles are determined to be re-inspected, then return to step S1 and repeat particle size and chemical composition testing.

6. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 4, characterized in that, Before particle size detection, the raw materials need to be pretreated, including crushing and grinding.

7. The method for random sampling inspection of incoming ferroalloy lines according to claim 4, characterized in that, The formula for calculating the CPK value is as follows: Where min represents the minimum value, USL is the maximum value in the technical indicator, and LSL is the minimum value in the technical indicator. X is the sample mean, σ is the sample standard deviation, n represents the sample size, and X i Let be the data for the i-th sample.

8. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 4, characterized in that, In step S53, the minimum CPK value is determined, and the determination method is as follows: Compare all CPK values ​​and take the smallest CPK value; When the minimum CPK value is greater than or equal to the first preset CPK value, the result is deemed qualified. When the minimum CPK value is less than the first preset CPK value and greater than or equal to the second preset CPK value, the determination result is reinspection; When the minimum CPK value is less than the second preset CPK value, the determination result is return of goods.

9. The method for random sampling inspection of incoming ferroalloys on the production line according to claim 4, characterized in that, In the step S53, the proportion of defective products in terms of particle size is determined, and the determination method is as follows: Obtain the proportion of defective products in terms of particle size, which includes the proportion of defective products greater than the preset upper limit and the proportion of defective products less than the preset lower limit; When the proportion of defective products greater than the preset upper limit is less than the first preset upper limit defective product proportion value and the proportion of defective products less than the preset lower limit is less than the first preset lower limit defective product proportion value, it is determined as qualified; When the proportion of defective products greater than the preset upper limit is greater than the second preset upper limit defective product proportion value or the proportion of defective products less than the preset lower limit is greater than the second preset lower limit defective product proportion value, it is determined as return of goods; When the proportion of defective products greater than the preset upper limit is greater than or equal to the first preset upper limit defective product proportion value and less than or equal to the second preset upper limit defective product proportion value, and the proportion of defective products less than the preset lower limit is less than or equal to the second preset lower limit defective product proportion value, it is reinspected; When the proportion of defective products less than the preset lower limit is greater than or equal to the first preset lower limit defective product proportion value and less than or equal to the second preset lower limit defective product proportion value, and the proportion of defective products greater than the preset upper limit is less than or equal to the second preset upper limit defective product proportion value, it is reinspected.

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