Production parameter optimization method of high-hardness high-speed tool steel for high-temperature bearing manufacturing

Abstract

The invention discloses a high-hardness high-speed tool steel production parameter optimization method for high-temperature bearing manufacturing, and relates to the technical field of metallurgy, and the method comprises the following steps: obtaining a correlation coefficient of a production index relative to a correlated mechanical performance index; obtaining influence factors of the production steps on the production indexes; target mechanical parameters of the mechanical performance indexes of the bearing are obtained; obtaining a to-be-compensated mechanical parameter of the mechanical performance index; generating at least one parameter preparation adjustment scheme for the production step; key coefficients of the estimated processing time, the estimated processing cost and the variation degree are formed; and calculating adaptability coefficients of the parameter preparation adjustment schemes, and selecting the parameter preparation adjustment scheme with the minimum adaptability coefficient. By generating at least one parameter preparation adjustment scheme for the production steps and calculating the adaptability coefficient of the parameter preparation adjustment scheme, the influence of the multiple production steps of the tool steel on the mechanical performance indexes of the bearing can be determined, and then accurate regulation and control can be carried out.

Description

Technical Field

[0001] The invention relates to the technical field of metallurgy, and in particular to a method for optimizing production parameters of high-hardness high-speed tool steel used for manufacturing high-temperature bearings. Background Art

[0002] Tool steel is a steel used to make cutting tools, gauges, molds and wear-resistant tools. Tool steel has high hardness and can maintain high hardness and red hardness at high temperatures, as well as high wear resistance and appropriate toughness. Tool steel is generally divided into carbon tool steel, alloy tool steel and high-speed tool steel. Tool steel is also widely used in bearing manufacturing.

[0003] Bearings have high requirements for mechanical properties such as wear resistance and hardness, but the production of tool steel involves many parameters. The impact of adjusting these parameters on the performance of the tool steel itself is difficult to determine, and thus the impact on the bearings is also difficult to determine. Therefore, when the performance of the bearing does not meet the requirements, it is difficult to make reasonable optimization. Summary of the invention

[0004] In order to solve the above technical problems, a method for optimizing the production parameters of high-hardness and high-speed tool steel for high-temperature bearing manufacturing is provided. This technical solution solves the problem that the bearings proposed in the above background technology have high requirements for mechanical properties such as wear resistance and hardness, but the production of tool steel involves many parameters, and the influence of the adjustment of its parameters on the performance of the tool steel itself is difficult to determine, thereby causing the influence on the bearings to be difficult to determine. Therefore, when the performance of the bearing does not meet the requirements, it is difficult to perform reasonable optimization.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing, comprising:

[0007] Obtain at least one mechanical performance index of bearing manufacturing and at least one production index of tool steel;

[0008] Correlate the production index with the mechanical performance index to obtain the correlation coefficient of the production index relative to the correlated mechanical performance index. The correlation coefficient of the production index relative to the uncorrelated mechanical performance index is 0. Combine the two situations to obtain the correlation coefficient of the production index relative to the mechanical performance index.

[0009] Obtain at least one production step in the tool steel production process, and obtain an influence factor of the production step on the production index, where the influence factor is 0, a negative number, or a positive number;

[0010] Acquire current production parameters of the production step, and acquire current mechanical parameters of mechanical performance indicators of the bearing made of tool steel produced according to the current production parameters;

[0011] Obtaining target mechanical parameters of the mechanical performance index of the bearing, and when there is a target mechanical parameter of the mechanical performance index that is greater than the current mechanical parameter, optimizing the current production parameter of the production step, otherwise, not optimizing;

[0012] During optimization, the target mechanical parameters of the mechanical performance index are subtracted from the current mechanical parameters to obtain the mechanical parameters to be compensated for the mechanical performance index;

[0013] generating at least one preliminary parameter adjustment plan for a production step, calculating an estimated processing time of the preliminary parameter adjustment plan, calculating an estimated processing cost of the preliminary parameter adjustment plan, and calculating a degree of change of the preliminary parameter adjustment plan;

[0014] Form critical coefficients for estimated processing time, estimated processing cost and degree of variation;

[0015] The adaptability coefficient of the preliminary parameter adjustment scheme is calculated, and the preliminary parameter adjustment scheme with the smallest adaptability coefficient is selected as the parameter adjustment scheme, and the production steps are optimized according to the parameters in the parameter adjustment scheme.

[0016] Preferably, associating the production index with the mechanical performance index comprises the following steps:

[0017] Randomly number production indicators;

[0018] Generate a first value assignment scheme and a second value assignment scheme for the production index;

[0019] In the first value assignment scheme, the production index is taken as the basic value. In the second value assignment scheme, the production index numbered j is taken as the sum of the basic value and j times the preset amplitude.

[0020] Under the value conditions of the first value assignment scheme, obtaining a reference value of at least one mechanical performance index;

[0021] Under the value conditions of the second value assignment scheme, obtaining a corrected value of at least one mechanical property index;

[0022] Using the first proportion formula, calculate the first change proportion of the production index;

[0023] Using the second proportion formula, calculate the second change proportion of the mechanical performance index;

[0024] Difference of the first change ratios of adjacent production indicators is taken and divided by 2 to obtain the sample gap;

[0025] The production index and the mechanical performance index that satisfy the correlation mechanism are correlated. The condition of the correlation mechanism is that the difference between the first change ratio of the production index and the second change ratio of the mechanical performance index is smaller than the sample difference.

[0026] The first ratio formula is as follows:

[0027]

[0028] Wherein, A is the first change ratio of the production index, j is the number of the production index, and F is the sum of the numbers of the production index;

[0029] Second ratio formula:

[0030]

[0031] Among them, B is the second change ratio of the mechanical property index, b is the correction value of the mechanical property index, a is the reference value of the mechanical property index, c is the sum of the correction value of at least one mechanical property index, and d is the sum of the reference value of at least one mechanical property index.

[0032] Preferably, the step of obtaining the correlation coefficient between the production index and the associated mechanical property index comprises the following steps:

[0033] The second change ratio of the mechanical property index is divided by the first change ratio of the associated production index to obtain a correlation coefficient of the production index with respect to the associated mechanical property index.

[0034] Preferably, obtaining the influencing factors of the production steps on the production indicators comprises the following steps:

[0035] Obtaining the change value of the production index when the parameter of a single production step changes by a preset range, wherein when the parameter of a single production step changes, the parameters of the other production steps remain unchanged;

[0036] When a single production step traverses at least one production step, at least one change value of the production index is obtained;

[0037] Use the impact factor formula to calculate the impact factor of the production step on the production index;

[0038] The impact factor formula is as follows:

[0039]

[0040] Among them, C is the impact factor of the production step on the production index, D is the sum of at least one change value of the production index, and e is the change value of the production index caused by the change of the production step.

[0041] Preferably, generating at least one parameter adjustment plan for the production step comprises the following steps:

[0042] Obtaining adjustment constraints satisfied by parameter changes of production indicators, and using Gaussian elimination method to solve and obtain at least one set of preliminary compensation values ​​of production indicators satisfying the adjustment constraints;

[0043] The preliminary compensation value of each group of production indicators is used as a preliminary parameter adjustment plan;

[0044] Adjust the restrictions as follows:

[0045]

[0046] in, is the preparatory compensation value of the i-th production step, i, j and p are all subscripts, is the impact factor of the i-th production step on the j-th production index, m is the total number of at least one production step, is the correlation coefficient of the jth production index relative to the pth mechanical property index, k is the total number of at least one mechanical property index, is the mechanical parameter to be compensated for the pth mechanical performance index.

[0047] Preferably, the estimated processing time of the calculation parameter preparation adjustment scheme comprises the following steps:

[0048] In the actual production process of the current production parameters of the production step, the processing time of the unit parameters of the production step is obtained;

[0049] The preparatory compensation value of the production step is superimposed on the current production parameter to obtain the pre-adjustment parameter of the production step;

[0050] The pre-adjusted parameter is divided by the unit parameter and multiplied by the processing time to obtain the estimated processing time.

[0051] Preferably, the estimated processing cost of the calculation parameter preparation adjustment scheme comprises the following steps:

[0052] In the actual production process of the current production parameters of the production step, the processing cost of the unit parameters of the production step is obtained;

[0053] The pre-adjusted parameter is divided by the unit parameter and multiplied by the processing cost to obtain the estimated processing cost.

[0054] Preferably, the calculation of the variation degree of the preliminary parameter adjustment scheme comprises the following steps:

[0055] Use the change estimation formula to calculate the degree of change of the parameter preparation adjustment plan;

[0056] The change estimation formula is as follows:

[0057]

[0058] Among them, E is the degree of change of the parameter preparation adjustment plan, is the preliminary compensation value of the i-th production step, m is the total number of at least one production step, and i is a subscript.

[0059] Preferably, the forming of the critical coefficients of the estimated processing time, the estimated processing cost and the degree of variation comprises the following steps:

[0060] The reciprocal of the unit time is used as the critical coefficient for estimating the processing time;

[0061] Based on historical data, obtain the average cost of processing per unit time;

[0062] The inverse of the average cost is used as the key factor for estimating processing costs;

[0063] Based on historical data, obtain the time-consuming plan for parameter control of production steps as a benchmark production step adjustment plan;

[0064] Obtaining the degree of change of the baseline production step adjustment plan as the baseline change degree;

[0065] The inverse of the benchmark change degree is taken as the key coefficient of the change degree.

[0066] Preferably, the calculation of the adaptability coefficient of the preliminary parameter adjustment scheme comprises the following steps:

[0067] Use the adaptability formula to calculate the adaptability coefficient of the parameter preparation adjustment plan;

[0068] The adaptability formula is as follows:

[0069]

[0070] Among them, G is the adaptability coefficient of the parameter preparation adjustment plan, X is the estimated processing time, is the critical coefficient for estimating processing time, Y is the estimated processing cost, is the key coefficient for estimating processing cost, E is the degree of change of the parameter adjustment plan, is the critical coefficient of the degree of change.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] By obtaining the correlation coefficient of the production index with respect to the associated mechanical performance index, obtaining the influencing factor of the production step on the production index, generating at least one parameter preparation adjustment scheme for the production step and calculating the adaptability coefficient of the parameter preparation adjustment scheme, the influence of the numerous production steps of tool steel on the mechanical performance index of the bearing can be determined, and then accurate regulation can be performed. At the same time, the changes in cost and time caused by the regulation are taken into consideration during regulation, so as to select the scheme with less comprehensive cost and time consumption for optimization, thereby improving the rationality of optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a schematic flow chart of the method for optimizing production parameters of high-hardness high-speed tool steel for manufacturing high-temperature bearings of the present invention;

[0074] Figure 2 It is a schematic diagram of the process of associating production indicators with mechanical performance indicators of the present invention;

[0075] Figure 3 A schematic diagram of a process for obtaining the influencing factors of production steps on production indicators of the present invention;

[0076] Figure 4 A schematic diagram of a process for generating at least one parameter preparatory adjustment scheme for a production step of the present invention;

[0077] Figure 5 A schematic diagram of a process flow for estimating processing time of a calculation parameter preparation adjustment scheme of the present invention;

[0078] Figure 6 A schematic diagram of a process flow for estimating processing costs for a calculation parameter preparation adjustment scheme of the present invention;

[0079] Figure 7 The figure is a flow chart of forming the critical coefficients of estimated processing time, estimated processing cost and degree of variation according to the present invention. DETAILED DESCRIPTION

[0080] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0081] Reference Figure 1 As shown, a method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing includes:

[0082] Obtain at least one mechanical performance index of bearing manufacturing and at least one production index of tool steel;

[0083] Correlate the production index with the mechanical performance index to obtain the correlation coefficient of the production index relative to the correlated mechanical performance index. The correlation coefficient of the production index relative to the uncorrelated mechanical performance index is 0. Combine the two situations to obtain the correlation coefficient of the production index relative to the mechanical performance index.

[0084] Obtain at least one production step in the tool steel production process, and obtain an influence factor of the production step on the production index, where the influence factor is 0, a negative number, or a positive number;

[0085] Acquire current production parameters of the production step, and acquire current mechanical parameters of mechanical performance indicators of the bearing made of tool steel produced according to the current production parameters;

[0086] Obtaining target mechanical parameters of the mechanical performance index of the bearing, and when there is a target mechanical parameter of the mechanical performance index that is greater than the current mechanical parameter, optimizing the current production parameter of the production step, otherwise, not optimizing;

[0087] During optimization, the target mechanical parameters of the mechanical performance index are subtracted from the current mechanical parameters to obtain the mechanical parameters to be compensated for the mechanical performance index;

[0088] generating at least one preliminary parameter adjustment plan for a production step, calculating an estimated processing time of the preliminary parameter adjustment plan, calculating an estimated processing cost of the preliminary parameter adjustment plan, and calculating a degree of change of the preliminary parameter adjustment plan;

[0089] Form critical coefficients for estimated processing time, estimated processing cost and degree of variation;

[0090] The adaptability coefficient of the preliminary parameter adjustment scheme is calculated, and the preliminary parameter adjustment scheme with the smallest adaptability coefficient is selected as the parameter adjustment scheme, and the production steps are optimized according to the parameters in the parameter adjustment scheme.

[0091] When tool steel is produced, the parameters of its production steps will affect its own production indicators, and the different production indicators of tool steel will affect the mechanical performance indicators of the bearing. Since the production steps will affect multiple production indicators, and the production indicators will also affect multiple mechanical performance indicators, the staggered influence will make it more difficult to determine the parameters for optimization and adjustment. At the same time, the adjustment will cause changes in processing time and processing costs. There are also large and small degrees of adjustment changes. The greater the degree of adjustment, the longer the adjustment time is, and the greater the processing time and processing cost are, the adjustment is unreasonable. Therefore, when adjusting, these factors must also be taken into consideration to obtain a more reasonable optimization plan. In this plan, a corresponding algorithm is set to solve the above-mentioned problems.

[0092] Reference Figure 2As shown, correlating production indicators with mechanical performance indicators includes the following steps:

[0093] Randomly number production indicators;

[0094] Generate a first value assignment scheme and a second value assignment scheme for the production index;

[0095] In the first value assignment scheme, the production index is taken as the basic value. In the second value assignment scheme, the production index numbered j is taken as the sum of the basic value and j times the preset amplitude.

[0096] Under the value conditions of the first value assignment scheme, obtaining a reference value of at least one mechanical performance index;

[0097] Under the value conditions of the second value assignment scheme, obtaining a corrected value of at least one mechanical property index;

[0098] Using the first proportion formula, calculate the first change proportion of the production index;

[0099] Using the second proportion formula, calculate the second change proportion of the mechanical performance index;

[0100] Difference of the first change ratios of adjacent production indicators is taken and divided by 2 to obtain the sample gap;

[0101] The production index and the mechanical performance index that satisfy the correlation mechanism are correlated. The condition of the correlation mechanism is that the difference between the first change ratio of the production index and the second change ratio of the mechanical performance index is smaller than the sample difference.

[0102] The first ratio formula is as follows:

[0103]

[0104] Wherein, A is the first change ratio of the production index, j is the number of the production index, and F is the sum of the numbers of the production index;

[0105] Second ratio formula:

[0106]

[0107] Among them, B is the second change ratio of the mechanical property index, b is the correction value of the mechanical property index, a is the reference value of the mechanical property index, c is the sum of the correction value of at least one mechanical property index, and d is the sum of the reference value of at least one mechanical property index.

[0108] The way to associate the production index with the mechanical performance index is through the setting of the first assignment scheme and the second assignment scheme. In the second assignment scheme, the value of the production index numbered j is set to be the sum of the basic value and j times the preset amplitude. Therefore, the value of each production index is different. Therefore, the proportion of the change of the production index in the first assignment scheme and the second assignment scheme can be calculated. The first proportion formula is the result of the preset amplitude in the numerator and denominator being canceled. At the same time, the second change ratio of the mechanical performance index is also calculated. Then, the first change ratio and the second change ratio of the associated production index and the mechanical performance index must be closest. Since the difference in the first change ratio of production indicators with adjacent numbers is twice the sample difference, therefore, when the difference between the second change ratio and the first change ratio is smaller than the sample difference, then the second change ratio and the first change ratio must be closest. Therefore, the corresponding production index and the mechanical performance index can be associated. It should be noted that there may be multiple second change ratios whose difference with the first change ratio is smaller than the sample difference. Therefore, the production index is associated with at least one mechanical performance index.

[0109] Obtaining the correlation coefficient of the production index with respect to the associated mechanical property index includes the following steps:

[0110] The second change ratio of the mechanical property index is divided by the first change ratio of the associated production index to obtain a correlation coefficient of the production index with respect to the associated mechanical property index.

[0111] For the convenience of subsequent calculations, the correlation coefficients of the production indicators with respect to the mechanical performance indicators are obtained. However, there are two cases here: the correlation coefficients of the production indicators with respect to the associated mechanical performance indicators and the correlation coefficients of the production indicators with respect to the unassociated mechanical performance indicators. Obviously, the correlation coefficient of the production indicators with respect to the unassociated mechanical performance indicators is 0. Therefore, it is only necessary to obtain the correlation coefficients of the production indicators with respect to the associated mechanical performance indicators.

[0112] Reference Figure 3 As shown, obtaining the influencing factors of the production steps on the production indicators includes the following steps:

[0113] Obtaining the change value of the production index when the parameter of a single production step changes by a preset range, wherein when the parameter of a single production step changes, the parameters of the other production steps remain unchanged;

[0114] When a single production step traverses at least one production step, at least one change value of the production index is obtained;

[0115] Use the impact factor formula to calculate the impact factor of the production step on the production index;

[0116] The impact factor formula is as follows:

[0117]

[0118] Among them, C is the impact factor of the production step on the production index, D is the sum of at least one change value of the production index, and e is the change value of the production index caused by the change of the production step.

[0119] Here, the control variable method is used to calculate the influencing factors. When the production step has a greater impact on the production index, the greater the impact factor is. Therefore, the change value of the production index corresponding to the preset amplitude of the parameter change of a single production step is used to calculate the influencing factor. Therefore, the calculation result is synchronized with the impact of the production step on the production index. Therefore, the result can be used as the influencing factor.

[0120] Reference Figure 4 As shown, generating at least one parameter adjustment plan for a production step includes the following steps:

[0121] Obtaining adjustment constraints satisfied by parameter changes of production indicators, and using Gaussian elimination method to solve and obtain at least one set of preliminary compensation values ​​of production indicators satisfying the adjustment constraints;

[0122] The preliminary compensation value of each group of production indicators is used as a preliminary parameter adjustment plan;

[0123] Adjust the restrictions as follows:

[0124]

[0125] in, is the preparatory compensation value of the i-th production step, i, j and p are all subscripts, is the impact factor of the i-th production step on the j-th production index, m is the total number of at least one production step, is the correlation coefficient of the jth production index relative to the pth mechanical property index, k is the total number of at least one mechanical property index, is the mechanical parameter to be compensated for the pth mechanical performance index.

[0126] Here, j is a subscript, while before, j was the number of the production indicator. This does not cause any inconsistency, because, here, j as a subscript still counts the production indicator, so it is the same kind of mark as the number of the production indicator, and therefore, it is represented by the same letter;

[0127] According to the matrix calculation method, the first matrix is ​​multiplied by the second matrix to obtain a matrix with 1 row and n columns, and then multiplied by the third matrix to obtain a matrix with 1 row and k columns. Since the second matrix is ​​composed of influencing factors and the third matrix is ​​composed of correlation coefficients, the matrix multiplication is equivalent to calculating the adjustment of the mechanical performance indicators by the preliminary compensation value of the production step, and then corresponding to the known mechanical parameters to be compensated for the k mechanical performance indicators, thereby obtaining k equations, among which, is an unknown number, so its solution that satisfies the conditions can be found, but the solution of this set of equations may be infinite. Therefore, for this case, select any combination of finite solutions as the preliminary compensation value of at least one set of production indicators that meet the adjustment constraints.

[0128] Reference Figure 5 As shown, the estimated processing time for calculating the parameter preparation adjustment plan includes the following steps:

[0129] In the actual production process of the current production parameters of the production step, the processing time of the unit parameters of the production step is obtained;

[0130] The preparatory compensation value of the production step is superimposed on the current production parameter to obtain the pre-adjustment parameter of the production step;

[0131] The pre-adjusted parameter is divided by the unit parameter and multiplied by the processing time to obtain the estimated processing time.

[0132] During regulation, time needs to be controlled, which will affect the processing efficiency. Therefore, it is necessary to calculate the estimated processing time.

[0133] Reference Figure 6 As shown, the estimated processing cost of calculating the parameter preparation adjustment plan includes the following steps:

[0134] In the actual production process of the current production parameters of the production step, the processing cost of the unit parameters of the production step is obtained;

[0135] The pre-adjusted parameter is divided by the unit parameter and multiplied by the processing cost to obtain the estimated processing cost.

[0136] When making adjustments, costs need to be controlled, so it is necessary to calculate the estimated processing costs.

[0137] Calculating the degree of change of the preliminary parameter adjustment plan includes the following steps:

[0138] Use the change estimation formula to calculate the degree of change of the parameter preparation adjustment plan;

[0139] The change estimation formula is as follows:

[0140]

[0141] Among them, E is the degree of change of the parameter preparation adjustment plan, is the preliminary compensation value of the i-th production step, m is the total number of at least one production step, and i is a subscript.

[0142] The greater the degree of change, the longer the adjustment time will be. Therefore, in order to ensure the rationality of the plan, the degree of change needs to be considered.

[0143] Reference Figure 7 As shown, the critical factors for forming the estimated processing time, estimated processing cost and degree of variation include the following steps:

[0144] The reciprocal of the unit time is used as the critical coefficient for estimating the processing time;

[0145] Based on historical data, obtain the average cost of processing per unit time;

[0146] The inverse of the average cost is used as the key factor for estimating processing costs;

[0147] Based on historical data, obtain the time-consuming plan for parameter control of production steps as a benchmark production step adjustment plan;

[0148] Obtaining the degree of change of the baseline production step adjustment plan as the baseline change degree;

[0149] The inverse of the benchmark change degree is taken as the key coefficient of the change degree.

[0150] Since the estimated processing time, estimated processing cost and degree of variation are different quantities, their results cannot be directly summarized. They need to be summarized by assigning weights. Here, the weights are determined in an equal manner, and the reciprocal of the average cost is used as the critical coefficient of the estimated processing cost. Since the unit time corresponds to the average cost, the estimated processing cost is multiplied by the critical coefficient of the estimated processing cost, which means the number of unit times included in the estimated processing cost. Similarly, the baseline degree of variation corresponds to the unit time. Therefore, the reciprocal of the baseline degree of variation is used as the critical coefficient of the degree of variation. The critical coefficient of the degree of variation is multiplied by the degree of variation, which means the number of unit times included in the degree of variation. The estimated processing time is multiplied by the critical coefficient of the estimated processing time, which means the number of unit times included in the estimated processing time. This is the principle of the adaptability formula, so the adaptability formula is reasonable and can be used to calculate the adaptability coefficient of the parameter preparation adjustment plan.

[0151] Calculating the adaptability coefficient of the parameter preparation adjustment scheme includes the following steps:

[0152] Use the adaptability formula to calculate the adaptability coefficient of the parameter preparation adjustment plan;

[0153] The adaptability formula is as follows:

[0154]

[0155] Among them, G is the adaptability coefficient of the parameter preparation adjustment plan, X is the estimated processing time, is the critical coefficient for estimating processing time, Y is the estimated processing cost, is the key coefficient for estimating processing cost, E is the degree of change of the parameter adjustment plan, is the critical coefficient of the degree of change.

[0156] Furthermore, the present solution also proposes a storage medium on which a computer-readable program is stored, and when the computer-readable program is called, the above-mentioned method for optimizing production parameters of high-hardness and high-speed tool steel for high-temperature bearing manufacturing is executed.

[0157] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0158] In summary, the advantages of the present invention are: by obtaining the correlation coefficient of the production index with respect to the associated mechanical performance index, obtaining the influencing factor of the production step on the production index, generating at least one parameter preparation adjustment scheme for the production step and calculating the adaptability coefficient of the parameter preparation adjustment scheme, the influence of numerous production steps of tool steel on the mechanical performance index of the bearing can be determined, and then accurate regulation can be performed. At the same time, the changes in cost and time caused by the regulation are taken into consideration during regulation, so as to select the scheme with less comprehensive cost and time consumption for optimization, thereby improving the rationality of optimization.

[0159] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing, characterized in that: include: Obtain at least one mechanical performance index of bearing manufacturing and at least one production index of tool steel; Correlate the production index with the mechanical performance index to obtain the correlation coefficient of the production index relative to the correlated mechanical performance index. The correlation coefficient of the production index relative to the uncorrelated mechanical performance index is 0. Combine the two situations to obtain the correlation coefficient of the production index relative to the mechanical performance index. Obtain at least one production step in the tool steel production process, and obtain an influence factor of the production step on the production index, where the influence factor is 0, a negative number, or a positive number; Acquire current production parameters of the production step, and acquire current mechanical parameters of mechanical performance indicators of the bearing made of tool steel produced according to the current production parameters; Obtaining target mechanical parameters of the mechanical performance index of the bearing, and when there is a target mechanical parameter of the mechanical performance index that is greater than the current mechanical parameter, optimizing the current production parameter of the production step, otherwise, not optimizing; During optimization, the target mechanical parameters of the mechanical performance index are subtracted from the current mechanical parameters to obtain the mechanical parameters to be compensated for the mechanical performance index; generating at least one preliminary parameter adjustment plan for a production step, calculating an estimated processing time of the preliminary parameter adjustment plan, calculating an estimated processing cost of the preliminary parameter adjustment plan, and calculating a degree of change of the preliminary parameter adjustment plan; Form critical coefficients for estimated processing time, estimated processing cost and degree of variation; The adaptability coefficient of the preliminary parameter adjustment scheme is calculated, and the preliminary parameter adjustment scheme with the smallest adaptability coefficient is selected as the parameter adjustment scheme, and the production steps are optimized according to the parameters in the parameter adjustment scheme.

2. The method for optimizing production parameters of high-hardness and high-speed tool steel for high-temperature bearing manufacturing according to claim 1, characterized in that: The step of associating the production index with the mechanical performance index comprises the following steps: Randomly number production indicators; Generate a first value assignment scheme and a second value assignment scheme for the production index; In the first value assignment scheme, the production index is taken as the basic value. In the second value assignment scheme, the production index numbered j is taken as the sum of the basic value and j times the preset amplitude. Under the value conditions of the first value assignment scheme, obtaining a reference value of at least one mechanical performance index; Under the value conditions of the second value assignment scheme, obtaining a corrected value of at least one mechanical property index; Using the first proportion formula, calculate the first change proportion of the production index; Using the second ratio formula, calculate the second variation ratio of the mechanical performance index; Difference of the first change ratios of adjacent production indicators is taken and divided by 2 to obtain the sample gap; The production index and the mechanical performance index that satisfy the correlation mechanism are correlated. The condition of the correlation mechanism is that the difference between the first change ratio of the production index and the second change ratio of the mechanical performance index is smaller than the sample difference. The first ratio formula is as follows: Wherein, A is the first change ratio of the production index, j is the number of the production index, and F is the sum of the numbers of the production index; Second ratio formula: Among them, B is the second change ratio of the mechanical property index, b is the correction value of the mechanical property index, a is the reference value of the mechanical property index, c is the sum of the correction value of at least one mechanical property index, and d is the sum of the reference value of at least one mechanical property index.

3. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 2, characterized in that: The step of obtaining the correlation coefficient between the production index and the associated mechanical performance index comprises the following steps: The second change ratio of the mechanical property index is divided by the first change ratio of the associated production index to obtain a correlation coefficient of the production index with respect to the associated mechanical property index.

4. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 3, characterized in that: The obtaining of the influencing factors of the production steps on the production indicators comprises the following steps: Obtaining the change value of the production index when the parameter of a single production step changes by a preset range, wherein when the parameter of a single production step changes, the parameters of the other production steps remain unchanged; When a single production step traverses at least one production step, at least one change value of the production index is obtained; Use the impact factor formula to calculate the impact factor of the production step on the production index; The impact factor formula is as follows: Among them, C is the impact factor of the production step on the production index, D is the sum of at least one change value of the production index, and e is the change value of the production index caused by the change of the production step.

5. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 4, characterized in that: The generating of at least one parameter adjustment plan for the production step comprises the following steps: Obtaining adjustment constraints satisfied by parameter changes of production indicators, and using Gaussian elimination method to solve and obtain at least one set of preliminary compensation values ​​of production indicators satisfying the adjustment constraints; The preliminary compensation value of each group of production indicators is used as a preliminary parameter adjustment plan; Adjust the restrictions as follows: in, is the preparatory compensation value of the i-th production step, i, j and p are all subscripts, is the impact factor of the i-th production step on the j-th production index, m is the total number of at least one production step, is the correlation coefficient of the jth production index relative to the pth mechanical property index, k is the total number of at least one mechanical property index, is the mechanical parameter to be compensated for the pth mechanical performance index.

6. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 5, characterized in that: The estimated processing time of the calculation parameter preparation adjustment scheme includes the following steps: In the actual production process of the current production parameters of the production step, the processing time of the unit parameters of the production step is obtained; The preparatory compensation value of the production step is superimposed on the current production parameter to obtain the pre-adjustment parameter of the production step; The pre-adjusted parameter is divided by the unit parameter and multiplied by the processing time to obtain the estimated processing time.

7. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 6, characterized in that: The estimated processing cost of the calculation parameter preparation adjustment scheme includes the following steps: In the actual production process of the current production parameters of the production step, the processing cost of the unit parameters of the production step is obtained; The pre-adjusted parameter is divided by the unit parameter and multiplied by the processing cost to obtain the estimated processing cost.

8. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 7, characterized in that: The calculation of the variation degree of the preliminary adjustment scheme of the parameters comprises the following steps: Use the change estimation formula to calculate the degree of change of the parameter preparation adjustment plan; The change estimation formula is as follows: Among them, E is the degree of change of the parameter preparation adjustment plan, is the preliminary compensation value of the i-th production step, m is the total number of at least one production step, and i is a subscript.

9. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 8, characterized in that: The critical coefficients for forming the estimated processing time, estimated processing cost and degree of variation include the following steps: The reciprocal of the unit time is used as the critical coefficient for estimating the processing time; Based on historical data, obtain the average cost of processing per unit time; The inverse of the average cost is used as the key factor for estimating processing costs; Based on historical data, obtain the time-consuming plan for parameter control of production steps as a benchmark production step adjustment plan; Obtaining the degree of change of the baseline production step adjustment plan as the baseline change degree; The inverse of the benchmark change degree is taken as the key coefficient of the change degree.

10. The method for optimizing production parameters of high-hardness high-speed tool steel for high-temperature bearing manufacturing according to claim 9, characterized in that: The calculation of the adaptability coefficient of the preliminary parameter adjustment scheme comprises the following steps: Use the adaptability formula to calculate the adaptability coefficient of the parameter preparation adjustment plan; The adaptability formula is as follows: Among them, G is the adaptability coefficient of the parameter preparation adjustment plan, X is the estimated processing time, is the critical coefficient for estimating processing time, Y is the estimated processing cost, is the key coefficient for estimating processing cost, E is the degree of change of the parameter adjustment plan, is the critical coefficient of the degree of change.

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