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CN-115204474-B - Production process parameter recommendation method, related equipment, program product and storage medium

CN115204474BCN 115204474 BCN115204474 BCN 115204474BCN-115204474-B

Abstract

The embodiment of the application provides a production process parameter recommending method based on abnormal working conditions, and related equipment, a program product and a storage medium, wherein the method comprises the steps of determining a first adjusting range of a first process parameter, wherein the first process parameter is an adjustable process parameter affecting the performance index of a product in production; selecting N+1 technological parameter values from a first adjusting range, respectively inputting the N+1 technological parameter values into a first mathematical model to obtain predicted values of N+1 groups of product performance indexes, inputting the predicted values of the N+1 groups of product performance indexes into an index evaluation model to obtain N+1 index evaluation values, determining a first adjusting value in the N+1 technological parameter values according to the N+1 index evaluation values, and determining recommended values of first technological parameters of the product according to the first adjusting value. By adopting the embodiment of the application, the recommended value of the adjustable technological parameter can be obtained through a prediction algorithm, and the performance index and the efficiency of production are improved.

Inventors

  • GUO CHUANLIANG
  • TONG XIAOHUI

Assignees

  • 希望知舟技术(深圳)有限公司

Dates

Publication Date
20260505
Application Date
20220418

Claims (9)

  1. 1. The production process parameter recommendation method based on the abnormal working condition is characterized by comprising the following steps of: Selecting n+1 process parameter values from a first adjustment range of a first process parameter, wherein N is an integer greater than 1, the first process parameter is an adjustable process parameter affecting a product performance index in production, and the first adjustment range is an adjustment range determined according to a first upper limit value and a first lower limit value of the first process parameter in a design score card; Inputting the N+1 process parameter values into a first mathematical model to obtain predicted values of N+1 groups of product performance indexes, and inputting the predicted values of the N+1 groups of product performance indexes into an index evaluation model to obtain N+1 index evaluation values, wherein the index evaluation values are used for evaluating the comprehensive approaching degree of the predicted values of each group of product performance indexes in the predicted values of a plurality of groups of product performance indexes corresponding to the N+1 process parameter values and a corresponding group of product performance target values; Determining a first adjustment value in N+1 process parameter values according to the N+1 index evaluation values, wherein the first adjustment value is a process parameter value corresponding to the largest index evaluation value in the N+1 index evaluation values; determining a recommended value of the first process parameter of the product according to the first adjustment value; The step of inputting the n+1 process parameter values into a first mathematical model to obtain predicted values of n+1 groups of product performance indexes, includes: determining a first reference value of a second process parameter, wherein the first reference value is a target value of the second process parameter in a marker post working condition score card; Determining a second reference value of a third process parameter and an abnormal predicted value of a fourth process parameter, wherein the third process parameter is of the adjustable process parameter type, the fourth process parameter is of the non-adjustable process parameter type, and the second process parameter, the third process parameter, the fourth process parameter and the first process parameter belong to an independent variable set of the first mathematical model; If the recommended value exists in the third process parameter, the second reference value is the recommended value of the third process parameter value, and if the recommended value does not exist in the third process parameter value, the second reference value is the target value of the third process parameter value, wherein the target value of the third process parameter is the target value of the third process parameter in the marker post working condition score card; Respectively inputting the N+1 process parameter values, the first reference value, the second reference value and the abnormal predicted value of the fourth process parameter into the first mathematical model to obtain predicted values of N+1 groups of product performance indexes, wherein the data blocks corresponding to the first process parameter, the second process parameter and the fourth process parameter are respectively combined into a chain type data structure according to time sequence and in a sequential connection mode; The method comprises the steps of calculating a first technological parameter, wherein the first technological parameter is a technological parameter for carrying out predicted value calculation of a product performance index, the second technological parameter is a corresponding technological parameter which does not need to be adjusted under a normal working condition, and the third technological parameter is a recommended value of the first technological parameter of a recommended value algorithm or a default value of the first technological parameter of an unfinished recommended value algorithm when an abnormal working condition occurs.
  2. 2. The method of claim 1, wherein the step of determining the position of the substrate comprises, And executing parameter calculation operation of the predicted value of the product performance index aiming at a first process parameter in the independent variable set in the first mathematical model, and if the second reference value of the third process parameter does not have a recommended value, executing parameter calculation operation flow of the predicted value of the product performance index by the third process parameter without the recommended value, wherein the parameter calculation operation flow of the third process parameter is the same as the parameter calculation flow of the first process parameter.
  3. 3. The method according to any one of claims 1 to 2, wherein selecting n+1 process parameter values from the first adjustment range of the first process parameter comprises: determining N-1 equally dividing points from the first adjustment range; And determining the first upper limit value and the first lower limit value of the N-1 equally divided points and the first adjustment range as N+1 process parameter values.
  4. 4. A method according to claim 3, wherein said determining a recommended value of said first process parameter of said product from said first adjustment value comprises: if the first adjustment value is the first upper limit value or the first lower limit value, the first adjustment value is used as a recommended value of the first process parameter; If the first adjustment value is not the first upper limit value or the first lower limit value, optimizing the first adjustment value to obtain a second adjustment value, and determining a recommended value of the first process parameter according to the second adjustment value.
  5. 5. The method of claim 4, wherein optimizing the first adjustment value to obtain a second adjustment value, determining a recommended value for the first process parameter based on the second adjustment value, comprises: Forming a second adjustment range according to process parameter values corresponding to two adjacent equal division points before and after the first adjustment value; And performing M times of the following operations on the second adjustment range: Dividing the second adjustment range into two sub-ranges; Respectively inputting the intermediate values of the two sub-ranges into the index evaluation model to obtain two index evaluation values; Selecting a sub-range with the highest index evaluation value from the two sub-ranges as the new second adjustment range according to the two index evaluation values; The intermediate value of the sub-range with the highest index evaluation value after the M times of iteration is used as the second adjustment value; And taking the second adjustment value as a recommended value of the first process parameter.
  6. 6. An apparatus for recommending production process parameters based on abnormal conditions, comprising: The device comprises a selection unit, a first processing unit and a second processing unit, wherein the selection unit is used for selecting N+1 process parameter values from a first adjustment range of first process parameters, N is an integer greater than 1, the first process parameters are adjustable process parameters which influence the performance index of a product in production, and the first adjustment range is an adjustment range determined according to a first upper limit value and a first lower limit value of the first process parameters in a design score card; The evaluation unit is used for inputting the N+1 process parameter values into a first mathematical model respectively to obtain predicted values of N+1 groups of product performance indexes, and inputting the predicted values of the N+1 groups of product performance indexes into an index evaluation model to obtain N+1 index evaluation values, wherein the index evaluation values are used for evaluating the comprehensive approaching degree of the predicted values of each group of product performance indexes in the predicted values of the plurality of groups of product performance indexes corresponding to the N+1 process parameter values and a corresponding group of product performance target values; The determining unit is used for determining a first adjustment value in the N+1 process parameter values according to the N+1 index evaluation values, wherein the first adjustment value is the process parameter value corresponding to the largest index evaluation value in the N+1 index evaluation values; A first determining unit, configured to determine a recommended value of the first process parameter of the product according to the first adjustment value; The step of inputting the n+1 process parameter values into a first mathematical model to obtain predicted values of n+1 groups of product performance indexes, includes: determining a first reference value of a second process parameter, wherein the first reference value is a target value of the second process parameter in a marker post working condition score card; Determining a second reference value of a third process parameter and an abnormal predicted value of a fourth process parameter, wherein the third process parameter is of the adjustable process parameter type, the fourth process parameter is of the non-adjustable process parameter type, and the second process parameter, the third process parameter, the fourth process parameter and the first process parameter belong to an independent variable set of the first mathematical model; If the recommended value exists in the third process parameter, the second reference value is the recommended value of the third process parameter value, and if the recommended value does not exist in the third process parameter value, the second reference value is the target value of the third process parameter value, wherein the target value of the third process parameter is the target value of the third process parameter in the marker post working condition score card; Respectively inputting the N+1 process parameter values, the first reference value, the second reference value and the abnormal predicted value of the fourth process parameter into the first mathematical model to obtain predicted values of N+1 groups of product performance indexes, wherein the data blocks corresponding to the first process parameter, the second process parameter and the fourth process parameter are respectively combined into a chain type data structure according to time sequence and in a sequential connection mode; The method comprises the steps of calculating a first technological parameter, wherein the first technological parameter is a technological parameter for carrying out predicted value calculation of a product performance index, the second technological parameter is a corresponding technological parameter which does not need to be adjusted under a normal working condition, and the third technological parameter is a recommended value of the first technological parameter of a recommended value algorithm or a default value of the first technological parameter of an unfinished recommended value algorithm when an abnormal working condition occurs.
  7. 7. An electronic device comprising a transceiver, a processor and a memory, the memory for storing a computer program, the processor invoking the computer program for performing the method of any of claims 1-5.
  8. 8. A computer readable storage medium, characterized in that the computer readable storage medium comprises a computer program which, when executed by a processor, performs the method of any of claims 1-5.
  9. 9. A computer program product, characterized in that the computer program in the computer program product, when executed by a processor, performs the method of any of claims 1-5.

Description

Production process parameter recommendation method, related equipment, program product and storage medium Technical Field The present application relates to the field of production technologies, and in particular, to a method for recommending production process parameters based on abnormal conditions, and related apparatus, program product, and storage medium. Background Along with the development of scientific technology, the production requirements and demands on the production process are higher and higher, the working condition conditions during production are complex due to excessive factors influencing production, the number of production process parameters during production is excessive, and when any production process parameter (such as pressure and hydrogen content) is abnormally changed due to uncontrollable factors such as equipment load, the indexes of production can be influenced due to continuous production. In order to solve the problem of process parameter variation, production personnel generally adjust the process parameters in the equipment according to experience accumulated by the production personnel under complex working conditions, so that the problems of inaccurate adjustment, low adjustment efficiency, insufficient adjustment time and the like can be caused, and the production quality and the production efficiency of the production process are affected. Disclosure of Invention The embodiment of the application discloses a production process parameter recommending method based on abnormal working conditions, related equipment, a program product and a storage medium, which can obtain a recommended value of the process parameter of production equipment through a prediction algorithm when the process parameter is abnormally changed, and improve the performance index of the product and the production efficiency. In a first aspect, an embodiment of the present application provides a method for recommending production process parameters based on abnormal working conditions, which is characterized by comprising: determining a first adjusting range of a first technological parameter, wherein the first technological parameter is an adjustable technological parameter affecting the performance index of a product in production, and the first adjusting range is an adjusting range determined according to a first upper limit value and a first lower limit value of the first technological parameter in a design score card; selecting n+1 process parameter values from the first adjustment range, N being an integer greater than 1; Inputting the N+1 process parameter values into a first mathematical model to obtain predicted values of N+1 groups of product performance indexes, and inputting the predicted values of the N+1 groups of product performance indexes into an index evaluation model to obtain N+1 index evaluation values, wherein the index evaluation values are used for evaluating the comprehensive approaching degree of the predicted values of each group of product performance indexes in the predicted values of a plurality of groups of product performance indexes corresponding to the N+1 process parameter values and a corresponding group of product performance target values; Determining a first adjustment value in N+1 process parameter values according to the N+1 index evaluation values, wherein the first adjustment value is a process parameter value corresponding to the largest index evaluation value in the N+1 index evaluation values; and determining a recommended value of the first process parameter of the product according to the first adjustment value. In the above method, when the process parameter is abnormally changed, the recommended value of the first process parameter (i.e., the adjustable process parameter to be adjusted) is predicted, i.e., the process parameter with the largest index evaluation value is selected as the recommended value of the first process parameter within the first adjustment range, instead of manually adjusting the process parameter by the experience accumulated by the producer according to experience, and taking the manually adjusted process parameter as the recommended value of the first process parameter. The method can timely and accurately obtain the recommended value of the adjustable process parameters to be adjusted under the condition that the production working condition is changed in a complex manner and a plurality of adjustable process parameters are required to be adjusted, and production personnel adjust the process parameters according to the recommended value, so that the performance index and the adjustment efficiency of the product are improved. It should be noted that under the complex working condition, the recommended value of the first technological parameter is obtained through a prediction method for the adjustable technological parameter (the first technological parameter) to be adjusted, the non-adjustable technological parameter to be ad