High-performance hot work die steel and manufacturing process thereof

Abstract

The invention relates to the technical field of metal material processing, and particularly discloses a high-performance hot work die steel and a manufacturing process thereof, the process comprises the following steps: obtaining size data of a steel ingot, processing the data to obtain a deformation score of the steel ingot, and evaluating an abnormal condition of the steel ingot; acquiring temperature distribution data and stress distribution data in the heat treatment process; based on the abnormal condition of the steel ingot, comprehensively analyzing the temperature distribution data and the stress distribution data to obtain an influence score; marking the steel ingot based on the influence score, and adjusting production process parameters accordingly; according to the method, the dimensional change and the internal stress distribution in the steel ingot heat treatment process are monitored in real time and accurately controlled, and dynamic optimization of heat treatment process parameters is realized, so that the dimensional precision of the steel ingot is effectively improved, deformation in the heat treatment process is reduced, and finally, the overall performance of the die steel is improved, and the service life of the die steel is prolonged.

Description

Technical Field

[0001] The invention relates to the technical field of metal material processing, and in particular to a high-performance hot working die steel and a manufacturing process thereof. Background Art

[0002] In modern manufacturing, mold steel is the basic material for producing various precision parts, and its quality directly affects the performance and life of the final product. Especially in the automotive, aerospace, precision machinery and other industries, there are extremely high requirements for the dimensional accuracy, strength and toughness of mold steel. However, during the heat treatment process of the mold steel corresponding to the steel ingot, due to factors such as uneven temperature distribution and internal stress, the steel ingot often undergoes varying degrees of deformation, thus affecting product quality and service life. Traditional heat treatment processes often lack effective monitoring methods and cannot accurately predict and control the deformation of the steel ingot during the heat treatment process, which has become one of the key factors restricting the improvement of mold steel quality.

[0003] At present, most heat treatment processes on the market only focus on temperature control, but pay insufficient attention to the changes in internal stress of steel ingots and their impact on deformation. In addition, traditional heat treatment process parameters are usually set based on experience and lack scientific basis. It is difficult to make personalized adjustments for different types of mold steels and it is difficult to adapt to the modern manufacturing industry's demand for high-quality mold steel. Therefore, how to accurately control the deformation of steel ingots during heat treatment and improve the overall performance and service life of mold steel has become a technical problem that needs to be solved urgently.

[0004] In order to solve the above problems, existing technical solutions are mostly focused on improving heat treatment equipment and process parameters, such as reducing temperature gradients by optimizing heating and cooling rates, or using special cooling media to reduce thermal stress. Although these methods can improve the performance of steel ingots to a certain extent, there are still some limitations in practical applications, such as the inability to accurately predict the deformation of steel ingots during heat treatment, and the inability to detect and solve potential heat treatment problems at an early stage. Therefore, there is an urgent need for a new technology that can monitor the dimensional changes and internal stress distribution of steel ingots during heat treatment in real time, so as to take timely measures to optimize the heat treatment process and ensure high-quality output of mold steel. Summary of the invention

[0005] The purpose of the present invention is to provide a high-performance hot working die steel and a manufacturing process thereof, by monitoring and controlling the deformation of the steel ingot during the heat treatment process, as well as the temperature and stress distribution during the heat treatment process, so as to improve the overall performance and service life of the die steel; first, before the heat treatment of the steel ingot, its original dimensional data, including length, width, height, aperture length and slot width, etc., are collected as reference data; then, after the heat treatment, these dimensional data are measured again and compared with the original data, the dimensional deviation value of each part is calculated, and the deformation ratio of each part is further calculated, and weighted calculation is performed according to the preset weight to obtain the deformation score of the steel ingot ; If the deformation score exceeds the preset threshold, it is considered that the ingot has an abnormality during the heat treatment process and needs further inspection and treatment; Temperature sensors and strain gauges are deployed inside the mold to monitor the temperature and stress distribution in different areas in real time; Through statistical analysis of these data, the temperature influence factor and stress influence factor are calculated, and weighted calculation is performed according to the preset proportional factor to obtain the influence score; If the influence score exceeds the preset threshold, it means that the ingot has problems such as uneven heating or excessive internal stress during the heat treatment process. For the ingots whose influence scores exceed the preset threshold, the first marking is performed and the deformation score continues to be monitored. If the deformation score also exceeds the preset threshold, the secondary marking is performed; In a heat treatment process cycle, the proportion of the number of ingots marked twice to the number of all marked ingots is calculated, that is, the heat treatment process influence abnormality ratio. If this ratio exceeds the preset threshold, it is considered that the heat treatment process parameters have a greater impact on the deformation of the ingot, and the heat treatment process parameters need to be optimized. The optimization measures include adjusting the heating rate and cooling rate to reduce the temperature gradient and thermal stress, while ensuring a more uniform temperature distribution. Through simulation and experiment, the appropriate heating rate and cooling rate are found until the abnormal ratio of the heat treatment process of the ingot is reduced to below the preset threshold.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A manufacturing process for high-performance hot working die steel comprises the following steps:

[0008] The raw materials are added to the electric arc furnace for smelting, and then passed through the ladle refining furnace and vacuum degassing furnace for secondary refining; then they are remelted by electroslag and cast into steel ingots;

[0009] The weight percentage of each element in the raw material is: C: 0.35-0.42%, Si: 0.20-0.50%, Mn: 0.30-0.80%, Cr: 4.90-5.50%, Mo: 1.70-2.00%, V: 0.40-0.80%, Ni≤0.25;

[0010] Performing pressure processing on the steel ingot and heat treating the steel ingot after the pressure processing to obtain mold steel;

[0011] During the heat treatment process,

[0012] S1: Obtaining the size data of the steel ingot, processing the size data of the steel ingot to obtain the deformation score of the steel ingot, and evaluating the abnormality of the steel ingot;

[0013] Among them, the dimension data include ingot length, ingot width, ingot height, aperture length and slot width;

[0014] S2: obtaining the temperature distribution data and stress distribution data of the steel ingot during the heat treatment process of the steel ingot;

[0015] S3: Based on the abnormal situation of the steel ingot, the temperature distribution data and stress distribution data of the steel ingot are comprehensively analyzed to obtain the impact score and judge the abnormal situation of the heat treatment process of the steel ingot;

[0016] S4: Based on the abnormal conditions of the heat treatment process of the steel ingot, the steel ingot is marked, and according to the marking results, the abnormality ratio of the heat treatment process is obtained, and an influence degree signal is generated;

[0017] S5: Based on the impact degree signal, the production process parameters of the marked steel ingot are adjusted.

[0018] As a further solution of the present invention: the process of obtaining the deformation score εi is:

[0019] The weight of the ingot length deformation ratio Li is w1, the weight of the ingot width deformation ratio Si is w2, the weight of the ingot height deformation ratio Hi is w3, the weight of the aperture length Ai deformation ratio is w4, and the weight of the slot width deformation ratio Bi is w5.

[0020] As a further solution of the present invention: the dimension data of the steel ingot after the treatment is calculated with the dimension data of the steel ingot before the heat treatment, and the absolute value is taken to obtain the dimension data deviation value;

[0021] The deviation value of the dimensional data is calculated by ratio with the dimensional data before heat treatment to obtain the ingot length deformation ratio Li, ingot width deformation ratio Si, ingot height deformation ratio Hi, aperture length Ai deformation ratio and slot width deformation ratio Bi, where i represents the number of collected ingots, i=1, 2,..., n.

[0022] As a further solution of the present invention: the process of obtaining the influence score γi is:

[0023] The temperature data and stress data of each area of ​​the ingot are analyzed to obtain the temperature influence factor τi and the stress influence factor ρi;

[0024] The weight of the temperature influence factor τi is assigned as Wa, and the weight of the stress influence factor ρi is assigned as Wb.

[0025] As a further solution of the present invention: the process of obtaining the temperature influence factor τi is:

[0026] After the third preheating, obtain the temperature value of each area, denoted as Tij;

[0027] Wherein, j represents the number of regions divided by the i-th steel ingot, j=1, 2, ..., m;

[0028] The temperature values ​​Tij of all regions are sorted in order of size, and all the temperature values ​​Tij of all regions are integrated into a temperature value group.

[0029] As a further solution of the present invention: the process of obtaining the stress influence factor ρi is:

[0030] After the third preheating, the stress value of each area is obtained and recorded as Fij;

[0031] Sort the stress values ​​Fij of all regions in order of size, subtract the j-1st stress value from the jth stress value, and get the stress deviation value ΔFi j-1 ; Integrate all stress deviation values ​​to obtain a stress deviation value group.

[0032] As a further solution of the present invention: if the influence score γi of the steel ingot is greater than or equal to the preset influence score threshold during the heat treatment process, the steel ingot is marked for the first time to obtain the deformation score of each steel ingot, and based on the steel ingot marked for the first time, if the deformation score εi of the steel ingot is greater than or equal to the preset deformation score threshold of the steel ingot, the steel ingot is marked for the second time.

[0033] As a further solution of the present invention: the total number of secondary marked steel ingots and the total number of all marked steel ingots are calculated to obtain the heat treatment process impact abnormality ratio;

[0034] comparing the heat treatment process impact anomaly ratio with a preset heat treatment process impact anomaly ratio threshold;

[0035] If the heat treatment process impact anomaly ratio is greater than or equal to the preset heat treatment process impact anomaly ratio threshold, a high impact signal is generated; otherwise, a low impact signal is generated.

[0036] As a further solution of the present invention: based on the influence degree signal, the heating rate is increased and the temperature gradient is reduced; the cooling rate is controlled to reduce the stress concentration during the cooling process, and the stress influence factor ρi and the temperature influence factor τi are re-obtained under the new heating rate and cooling rate; and the influence score γi and the deformation score εi of the steel ingot are calculated. If the deformation score εi of the steel ingot is still greater than the threshold, the adjustment step is repeated.

[0037] A high-performance hot working die steel is prepared by the above-mentioned production process.

[0038] Beneficial effects of the present invention:

[0039] (1) The present invention can effectively monitor the dimensional changes of steel ingots during heat treatment by introducing a comprehensive and sophisticated dimensional detection system. By accurately measuring key dimensions such as length, width, height, aperture length and slot width of the steel ingots before and after heat treatment, and calculating the deformation fraction using advanced data analysis technology, abnormal deformation that may occur during heat treatment of the steel ingots can be discovered in time. This precise dimensional control technology greatly improves the dimensional accuracy of mold steel products and avoids product failures caused by dimensional changes during heat treatment. The improvement in dimensional accuracy means that mold steel products can better meet customer requirements for accuracy in subsequent applications, which is particularly important for manufacturing precision parts. In addition, since potential problems can be discovered and resolved at an early stage, production costs and scrap rates can be significantly reduced, thereby improving the economic and social benefits of the enterprise.

[0040] (2) The present invention realizes effective optimization of heat treatment process parameters by accurately monitoring the temperature distribution and stress distribution during the heat treatment of steel ingots. The temperature and stress data of each area are obtained in real time, and then the temperature influence factor and stress influence factor are calculated, and then the influence score is obtained by weighted calculation combined with the preset proportional factor. This innovative method not only helps to timely discover problems such as uneven temperature and excessive stress that may exist in the heat treatment process, but also optimizes the heat treatment process by continuously adjusting parameters such as heating rate and cooling rate, ensuring that the steel ingot obtains a good temperature distribution during the heat treatment process, reducing thermal stress, and ultimately achieving the effect of reducing deformation. This optimization measure can not only improve the quality of mold steel, but also reduce energy consumption and improve production efficiency, thereby producing a dual positive impact on environmental protection and economic benefits.

[0041] (3) The present invention effectively improves the heat treatment effect of the steel ingot through a series of scientific detection methods and process optimization measures, thereby improving the overall performance and service life of the mold steel. By strictly controlling the temperature distribution and stress distribution during the heat treatment process, not only can the deformation of the steel ingot be reduced, but also its fatigue resistance and wear resistance can be enhanced, which is directly related to the reliability and durability of the mold during actual use. The improvement in the performance of mold steel means that it can withstand higher workloads and more complex processing conditions, which is of great significance for extending the service life of the mold and reducing maintenance costs. In addition, the technical solution of the present invention also helps to reduce the frequency of mold replacement and reduce the risk of downtime and production interruption caused by mold failure, which is crucial to improving the overall efficiency of the production line. Therefore, the use of the technical solution of the present invention can significantly improve the overall performance and service life of the mold steel, bringing long-term competitive advantages to manufacturers. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention will be further described below in conjunction with the accompanying drawings.

[0043] Figure 1 It is a flowchart of the specific steps of the manufacturing process of a high-performance hot working die steel of the present invention;

[0044] Figure 2 It is a flowchart of the quality judgment standard of mold steel in the manufacturing process of a high-performance hot-working mold steel of the present invention;

[0045] Figure 3 The invention discloses a standard flow chart of heat treatment signal judgment in the manufacturing process of high-performance hot working die steel. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] See also Figure 1 As shown, the present invention is a manufacturing process of high-performance hot working die steel, comprising the following steps:

[0048] The raw materials are added into an electric arc furnace for smelting, and then secondary refined in a ladle refining furnace and a vacuum degassing furnace; and then electroslag remelting is performed to cast steel ingots;

[0049] Performing pressure processing on the steel ingot and heat treating the steel ingot after the pressure processing to obtain mold steel;

[0050] During the heat treatment process, the deformation of the steel ingot has a great influence on the quality of the product. Based on this:

[0051] During the heat treatment process, the dimensional data of the steel ingot is obtained, the dimensional data of the steel ingot is processed to obtain the deformation score of the steel ingot, and the abnormality of the steel ingot is evaluated;

[0052] Among them, the dimension data include ingot length, ingot width, ingot height, aperture length and slot width;

[0053] Obtaining temperature distribution data and stress distribution data of the steel ingot during the heat treatment process of the steel ingot;

[0054] Based on the abnormal situation of the steel ingot, the temperature distribution data and stress distribution data of the steel ingot are comprehensively analyzed to obtain the influence score, and the influence degree of the temperature distribution data and stress distribution number on the deformation score of the steel ingot is evaluated;

[0055] Based on the degree of influence, the steel ingots are marked, and according to the marking results, the production process parameters of the marked steel ingots are adjusted.

[0056] The weight percentage of each element in the mold steel is: C: 0.35-0.42%, Si: 0.20-0.50%, Mn: 0.30-0.80%, Cr: 4.90-5.50%, Mo: 1.70-2.00%, V: 0.40-0.80%, Ni≤0.25;

[0057] Example 2

[0058] See also Figure 2 As shown, on the basis of Example 1, under the same mold steel production process, within the mold steel production cycle, the dimensional data of all steel ingots are collected, the dimensional data are analyzed, the steel ingot deformation abnormality is obtained, and the qualification of the mold steel production is identified;

[0059] The dimension data include ingot length, ingot width, ingot height, aperture length and slot width;

[0060] Specific:

[0061] Collect the pre-heat treatment dimensional data of all steel ingots before the heat treatment process, including original steel ingot length, original steel ingot width, original steel ingot height, original aperture length and original slot width;

[0062] Collect the dimensional data of all steel ingots after heat treatment, including final steel ingot length, final steel ingot width, final steel ingot height, final aperture length and final slot width.

[0063] The difference between the dimension data of the steel ingot after treatment and the dimension data of the steel ingot before heat treatment is calculated, and the absolute value is taken to obtain the dimension data deviation value, including the steel ingot length deviation value, the steel ingot width deviation value, the steel ingot height deviation value, the aperture length deviation value and the slot width deviation value;

[0064] The deviation value of the dimension data is calculated by ratio with the dimension data before heat treatment to obtain the ingot length deformation ratio Li, ingot width deformation ratio Si, ingot height deformation ratio Hi, aperture length deformation ratio Ai and slot width deformation ratio Bi, where i represents the number of collected ingots, i=1, 2, ..., n;

[0065] The weight of the ingot length deformation ratio Li is assigned to w1, the weight of the ingot width deformation ratio Si is assigned to w2, the weight of the ingot height deformation ratio Hi is assigned to w3, the weight of the aperture length Ai deformation ratio is assigned to w4, and the weight of the slot width deformation ratio Bi is assigned to w5;

[0066] Among them, w1+w2+w3+w4+w5=1;

[0067] The deformation fraction εi of the steel ingot is calculated by the formula εi=Li*w1+Si*w2+Hi*w3+Ai*w4+Bi*w5;

[0068] Compare the deformation score εi of the steel ingot with a preset deformation score threshold of the steel ingot;

[0069] If the deformation fraction εi of the steel ingot is greater than or equal to the preset deformation fraction threshold of the steel ingot, it means that an abnormality occurs during the heat treatment of the corresponding steel ingot, and a steel ingot abnormality signal is generated;

[0070] If the deformation fraction εi of the steel ingot is less than the preset deformation fraction threshold of the steel ingot, it means that the corresponding heat treatment process of the steel ingot is normal, and a normal signal of the steel ingot is generated;

[0071] It should be noted that: before and after heat treatment, ensure that the same measurement methods and tools are used to ensure the accuracy of the data; the deformation fraction εi of the steel ingot is a factor in judging the quality of the steel ingot. The larger the deformation fraction εi of the steel ingot, the more serious the deformation of the steel ingot;

[0072] Among them, the heat treatment process includes:

[0073] Stress relief tempering: that is, a vacuum stress relief tempering treatment is carried out in a vacuum tempering furnace to eliminate processing stress;

[0074] Vacuum quenching: According to the complexity and size of the steel ingot, select 2 to 3 preheating, austenitization and heating, and finally cooling, so that the surface temperature of the steel ingot cools to 120℃ and then it is taken out of the furnace for air cooling;

[0075] Tempering: The number of tempering times is greater than or equal to 4 times. The first tempering temperature is 570℃. The subsequent tempering temperatures are determined according to the required hardness. Before the second, third and fourth tempering, the ingot must be cooled to room temperature before entering the furnace for tempering.

[0076] Example 3

[0077] See also Figure 3 As shown, on the basis of Example 2, during the heat treatment process of the steel ingot, due to the uneven heating and large internal stress of the steel ingot during heating, the final mold steel will be deformed. A comprehensive analysis is performed on the uneven heating and large internal stress of the steel ingot during the heat treatment process, which is convenient for the subsequent control of temperature and stress in the heat treatment process of the steel ingot, and then the heat treatment production process is optimized, thereby improving the overall performance and service life of the mold steel; in the same heat treatment process, the same batch of mold steel is produced, and the temperature data and stress data of this batch of mold steel are collected, and the temperature influence factor and stress influence factor are obtained according to the temperature data and stress data, and the internal heating condition and stress degree of the steel ingot during the heat treatment process are evaluated;

[0078] Specific:

[0079] During a heat treatment process, the temperature and stress data of the steel ingots of the same batch of mold steel are collected;

[0080] The temperature data of the hot steel ingot is monitored in real time through the temperature sensor, and each temperature sensor is calibrated to ensure the accuracy of the collected data, and the stress changes inside the steel ingot are monitored in real time and recorded;

[0081] Divide each steel ingot into a number of identical regions;

[0082] Collect temperature data of each area separately;

[0083] After the third preheating, obtain the temperature value of each area, denoted as Tij;

[0084] Wherein, j represents the number of regions divided by the i-th steel ingot, j=1, 2, ..., m;

[0085] Sort the temperature values ​​Tij of all regions in order of size, and integrate the temperature values ​​Tij of all regions into a temperature value group;

[0086] The average temperature value Tiy in the temperature value group is calculated by the mean calculation formula;

[0087] The standard deviation value αi within the temperature value group is calculated by the standard deviation calculation formula;

[0088] By formula The temperature influence factor τi is calculated;

[0089] Wherein, b1 and b2 are preset proportional factors, and both b1 and b2 are greater than 0;

[0090] Obtain the stress value of each area respectively;

[0091] After the third preheating, the stress value of each area is obtained and recorded as Fij;

[0092] Sort the stress values ​​Fij of all regions in order of size, subtract the j-1st stress value from the jth stress value, and get the stress deviation value ΔFi j-1 ; Integrate all stress deviation values ​​to obtain a stress deviation value group;

[0093] The average value ΔFiy within the stress deviation value group is calculated by the mean value calculation formula;

[0094] The standard deviation value βi within the stress deviation value group is calculated by the standard deviation calculation formula;

[0095] By formula The stress influence factor ρi is calculated;

[0096] Wherein, b3 and b4 are preset proportional factors, and both b3 and b4 are greater than 0;

[0097] Process the temperature influence factor τi and stress influence factor ρi;

[0098] The weight of the temperature influence factor τi is assigned as Wa, and the weight of the stress influence factor ρi is assigned as Wb, where Wa+Wb=1;

[0099] The influence score γi is calculated by the formula γi=τi*Wa+ρi*Wb;

[0100] Compare the influence score γi with a preset influence score threshold;

[0101] If the influence score γi is greater than or equal to the preset influence score threshold, it means that the internal stress level of the corresponding steel ingot during the heat treatment process is abnormal, which may cause the steel ingot to deform; a heat treatment abnormality signal is generated;

[0102] If the influence score γi is greater than or equal to the preset influence score threshold, it means that the internal heat stress level of the corresponding steel ingot is normal during the heat treatment process, and the steel ingot will not be deformed; a normal heat treatment signal is generated;

[0103] It should be noted that the influence fraction γi is a criterion for judging whether the heating of the steel ingot is uneven and the internal stress is large during heating. The larger the influence fraction γi is, the greater the influence of the heating and stress conditions during the heat treatment of the steel ingot on the quality of the steel ingot.

[0104] Example 4

[0105] On the basis of Example 3, during the heat treatment process, if the ingot influence score γi is greater than or equal to the preset influence score threshold, the ingot is marked for the first time, and the deformation score of each ingot is obtained. Based on the ingot marked for the first time, if the deformation score εi of the ingot is greater than or equal to the preset deformation score threshold of the ingot, the ingot is marked for the second time;

[0106] In a heat treatment production process cycle, the total number of secondary marked steel ingots is obtained, and the total number of all marked steel ingots is obtained;

[0107] The heat treatment process influence abnormality ratio is calculated by calculating the ratio of the total number of secondary marked ingots to the total number of all marked ingots;

[0108] comparing the heat treatment process impact anomaly ratio with a preset heat treatment process impact anomaly ratio threshold;

[0109] If the heat treatment process influence abnormality ratio is greater than or equal to the preset process influence abnormality ratio threshold, it means that the heat treatment process parameter abnormality has a high influence on the deformation degree of the steel ingot in the corresponding heat treatment process, and a high influence signal is generated;

[0110] If the heat treatment process influence abnormality ratio is less than the preset treatment process influence abnormality ratio threshold, it means that the heat treatment process parameter abnormality has a low influence on the deformation degree of the steel ingot in the corresponding heat treatment process, and a low influence signal is generated;

[0111] It should be noted that heat treatment process parameters refer to the temperature control process and stress control process during the heat treatment process; adjusting the heat treatment process parameters and finding the best heat treatment working environment can effectively improve the quality of mold steel, improve production efficiency and save raw materials.

[0112] Based on the high-impact signals, the heat treatment process parameters are optimized;

[0113] Specific:

[0114] Since increasing the heating rate can reduce the temperature gradient, it helps to make the temperature distribution more uniform; but too fast a heating rate may lead to increased internal stress, so a balance point needs to be found; the original temperature rise rate of X degrees per minute is adjusted to Y degrees per minute (Y>X), where the temperature rise process adjustment is based on the historical normal temperature data, and multiple simulations are performed within the normal temperature data; after the temperature adjustment process, controlling the cooling rate can reduce the stress concentration during the cooling process; a slower cooling rate helps to reduce thermal stress, but may extend the time of the entire heat treatment cycle; for example: using different cooling media (such as oil cooling, air cooling, etc.) or adjusting the cooling wind speed to achieve different cooling rates;

[0115] The stress influence factor ρi and temperature influence factor τi are re-obtained under the new heating rate and cooling rate; and the influence fraction γi and the deformation fraction εi of the steel ingot are calculated. If the steel ingot deformation fraction εi is still greater than the threshold, the adjustment steps are repeated until the situation is found where the steel ingot heat treatment process influence anomaly ratio is less than the preset treatment process influence anomaly ratio threshold.

[0116] It should be noted that by adjusting the heat treatment process parameters and repeating the adjustment operation steps, the heat treatment process can be gradually optimized until the optimal heat treatment process is found, ensuring that the steel ingot obtains better temperature distribution during the heat treatment process, reducing thermal stress and deformation, thereby improving the overall performance and service life of the mold.

[0117] Example 5

[0118] A high-performance hot working die steel is prepared by the above-mentioned production process.

[0119] The working principle of the present invention is to improve the overall performance and service life of the steel ingot by monitoring and controlling the deformation of the steel ingot during the heat treatment process, as well as the temperature and stress distribution during the heat treatment process. First, before the heat treatment of the steel ingot, its original dimensional data, including length, width, height, aperture length and slot width, etc., are collected as reference data. Subsequently, these dimensional data are measured again after heat treatment and compared with the original data to calculate the dimensional deviation value of each part, further calculate the deformation ratio of each part, and perform weighted calculation according to the pre-set weights to obtain the deformation score of the steel ingot. If the deformation score exceeds the preset threshold, it is considered that the steel ingot has an abnormality during the heat treatment process and further inspection and processing are required.

[0120] In order to more accurately grasp the temperature and stress changes during the heat treatment of the steel ingot, the present invention also deploys temperature sensors and strain gauges inside the mold to monitor the temperature and stress distribution in different areas in real time. Through statistical analysis of these data, the temperature influence factor and stress influence factor are calculated, and weighted calculation is performed according to the pre-set proportional factor to obtain the impact score. If the impact score exceeds the preset threshold, it means that the steel ingot has problems such as uneven heating or excessive internal stress during the heat treatment process, which may cause the steel ingot to deform.

[0121] For steel ingots whose impact scores exceed the preset threshold, the first marking is performed and the deformation score is continuously monitored. If the deformation score also exceeds the preset threshold, the second marking is performed. In a heat treatment process cycle, the ratio of the number of steel ingots with the second marking to the number of all marked steel ingots is counted, that is, the heat treatment process impact abnormality ratio. If this ratio exceeds the preset threshold, it is considered that the heat treatment process parameters have a greater impact on the deformation of the steel ingot, and the heat treatment process parameters need to be optimized.

[0122] Optimization measures include adjusting the heating rate and cooling rate to reduce temperature gradients and thermal stresses while ensuring a more uniform temperature distribution. Through simulation and experimentation, the appropriate heating rate and cooling rate are found until the abnormal ratio of the heat treatment process of the steel ingot is reduced to below the preset threshold. In this way, not only can the deformation of the steel ingot be effectively controlled, but also its overall performance and service life can be improved, thereby achieving the purpose of improving the quality of the steel ingot. The application of this manufacturing process can significantly improve the product quality and production efficiency of hot-working steel ingots, which has important practical significance for the precision mold manufacturing industry.

[0123] The formulas in the present invention are all dimensionless and numerically calculated. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0124] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A manufacturing process for high performance hot working die steel, characterized in that: The following steps are involved: The raw materials are added to the electric arc furnace for smelting, and then secondary refining is carried out in the ladle refining furnace and vacuum degassing furnace; After electroslag remelting, the steel ingot is cast; The weight percentage of each element in the raw material is: C: 0.35-0.42%, Si: 0.20-0.50%, Mn: 0.30-0.80%, Cr: 4.90-5.50%, Mo: 1.70-2.00%, V: 0.40-0.80%, Ni≤0.25; Performing pressure processing on the steel ingot and heat treating the steel ingot after the pressure processing to obtain die steel; During the heat treatment process, the dimensional data of the steel ingot is obtained, the dimensional data of the steel ingot is processed to obtain the deformation score of the steel ingot, and the abnormality of the steel ingot is evaluated; Among them, the dimension data include ingot length, ingot width, ingot height, aperture length and slot width; Obtaining temperature distribution data and stress distribution data of the steel ingot during the heat treatment process of the steel ingot; Based on the abnormal conditions of the steel ingot, the temperature distribution data and stress distribution data of the steel ingot are comprehensively analyzed to obtain the impact score and judge the abnormal conditions of the heat treatment process of the steel ingot; Based on the abnormal conditions of the heat treatment process of the steel ingot, the steel ingot is marked, and according to the marking results, the abnormality ratio of the heat treatment process is obtained, and an impact degree signal is generated; Based on the impact degree signal, the production process parameters of the marked steel ingot are adjusted.

2. The manufacturing process of a high performance hot working die steel according to claim 1, characterized in that: The process of obtaining the deformation fraction εi is: The weight of the ingot length deformation ratio Li is w1, the weight of the ingot width deformation ratio Si is w2, the weight of the ingot height deformation ratio Hi is w3, the weight of the aperture length Ai deformation ratio is w4, and the weight of the slot width deformation ratio Bi is w5.

3. The manufacturing process of a high performance hot working die steel according to claim 2, characterized in that: The difference between the dimension data of the steel ingot after heat treatment and the dimension data of the steel ingot before heat treatment is calculated, and the absolute value is taken to obtain the dimension data deviation value; The deviation value of the dimensional data is calculated by ratio with the dimensional data before heat treatment to obtain the ingot length deformation ratio Li, ingot width deformation ratio Si, ingot height deformation ratio Hi, aperture length Ai deformation ratio and slot width deformation ratio Bi, where i represents the number of collected ingots, i=1, 2,..., n.

4. The manufacturing process of a high performance hot working die steel according to claim 1, characterized in that: The process of obtaining the influence score γi is: The temperature data and stress data of each area of ​​the ingot are analyzed to obtain the temperature influence factor τi and the stress influence factor ρi; The weight of the temperature influence factor τi is assigned as Wa, and the weight of the stress influence factor ρi is assigned as Wb, where Wa+Wb=1.

5. The manufacturing process of a high performance hot working die steel according to claim 4, characterized in that: The process of obtaining the temperature influence factor τi is: After the third preheating, obtain the temperature value of each area, denoted as Tij; Wherein, j represents the number of regions divided by the i-th steel ingot, j=1, 2, ..., m; The temperature values ​​Tij of all regions are sorted in order of size, and all the temperature values ​​Tij of all regions are integrated into a temperature value group.

6. The manufacturing process of a high performance hot working die steel according to claim 4, characterized in that: The process of obtaining the stress influence factor ρi is: After the third preheating, the stress value of each area is obtained and recorded as Fij; Sort the stress values ​​Fij of all regions in order of size, subtract the j-1st stress value from the jth stress value, and get the stress deviation value ΔFi j-1 ; Integrate all stress deviation values ​​to obtain a stress deviation value group.

7. The manufacturing process of a high performance hot working die steel according to claim 1, characterized in that: If the influence score γi of the steel ingot is greater than or equal to the preset influence score threshold during the heat treatment process, the steel ingot is marked for the first time to obtain the deformation score of each steel ingot. Based on the steel ingot marked for the first time, if the deformation score εi of the steel ingot is greater than or equal to the preset deformation score threshold of the steel ingot, the steel ingot is marked for the second time.

8. The manufacturing process of high performance hot working die steel according to claim 7, characterized in that: The heat treatment process influence abnormality ratio is calculated by calculating the ratio of the total number of secondary marked ingots to the total number of all marked ingots; comparing the heat treatment process impact anomaly ratio with a preset heat treatment process impact anomaly ratio threshold; If the heat treatment process impact anomaly ratio is greater than or equal to the preset heat treatment process impact anomaly ratio threshold, a high impact signal is generated; otherwise, a low impact signal is generated.

9. The manufacturing process of a high performance hot working die steel according to claim 1, characterized in that: Based on the influence degree signal, the heating rate is increased and the temperature gradient is reduced; the cooling rate is controlled to reduce the stress concentration during the cooling process, and the stress influence factor ρi and the temperature influence factor τi are re-obtained under the new heating rate and cooling rate; and the influence score γi and the deformation score εi of the ingot are calculated. If the deformation score εi of the ingot is still greater than the threshold, the adjustment steps are repeated.

10. A high performance hot working die steel, characterized in that: The high-performance hot working die steel is prepared by the production process described in any one of claims 1-9.

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