Search

CN-122013287-A - Electroplating full-flow self-adaptive intelligent control method and system

CN122013287ACN 122013287 ACN122013287 ACN 122013287ACN-122013287-A

Abstract

The application discloses a full-flow self-adaptive intelligent control method and system for electroplating, wherein the method comprises the steps of acquiring current batch workpiece information before electroplating treatment, combining latest equipment state variables to generate initial technological parameters corresponding to each procedure, acquiring actual execution parameters of any procedure after the current batch workpiece completes the procedure in the electroplating treatment process, acquiring second equipment state variables corresponding to incomplete procedures, generating a finished product quality predicted value of the current batch workpiece through a preset finished product quality prediction model based on the actual execution parameters of the completed procedure, the second equipment state variables and the initial technological parameters corresponding to the incomplete procedures, and solving and generating optimal technological parameters of the incomplete procedures by taking the finished product quality predicted value reaching the standard as a constraint condition and taking the predicted cost of the incomplete procedure as an optimization target. The application realizes the cooperative control and global optimization of the whole electroplating process through the inter-batch state transfer and the in-process real-time optimization.

Inventors

  • LUO HAO

Assignees

  • 杭州云会五金电镀有限公司

Dates

Publication Date
20260512
Application Date
20260410

Claims (10)

  1. 1. The full-flow self-adaptive intelligent control method for electroplating is characterized by comprising the following steps of: before electroplating, acquiring current batch workpiece information, and acquiring the latest equipment state variables corresponding to all the procedures through a preset equipment state database; generating initial technological parameters corresponding to each procedure according to the current batch of workpiece information and the latest equipment state variables; In the electroplating treatment process, after any process is completed on the workpieces in the current batch, acquiring actual execution parameters of the process and corresponding first equipment state variables, and updating a preset equipment state database according to the first equipment state variables; Acquiring a second equipment state variable corresponding to the work piece of the current batch in the unfinished working procedure; Generating a finished product quality prediction value of the workpieces in the current batch by presetting a finished product quality prediction model based on actual execution parameters of the completed process, second equipment state variables and initial process parameters corresponding to the incomplete process; Judging whether the product quality predicted value of the workpieces in the current batch reaches a preset product quality qualification threshold value or not; if not, taking the predicted value of the quality of the finished product as a constraint condition and taking the predicted cost of the unfinished working procedure as an optimization target, and solving and generating the optimal technological parameters of the unfinished working procedure.
  2. 2. The method for adaptively controlling the whole electroplating process according to claim 1, wherein generating initial process parameters corresponding to each process according to the current batch of workpiece information and the latest equipment state variables comprises the following steps: acquiring reference process parameters corresponding to each procedure through a preset workpiece-parameter mapping library according to the current batch workpiece information; calculating and acquiring equipment capacity attenuation rate of each procedure by presetting a reference state variable based on the latest equipment state variable; Determining the compensation quantity of the process parameters of each process through a preset parameter compensation rule based on the equipment capacity attenuation rate of each process; based on the reference process parameters and the corresponding compensation amounts of each process, initial process parameters of each process are generated.
  3. 3. The method according to claim 1, wherein the step of solving the optimal process parameters for generating the unfinished process with the predicted cost of the unfinished process minimized as an optimization objective under the constraint that the predicted value of the quality of the finished product meets the preset quality qualification threshold of the finished product comprises: obtaining a feasible value range of each technological parameter of an unfinished procedure, forming a technological parameter feasible domain, and generating a candidate parameter track set in the technological parameter feasible domain; inputting each candidate parameter track, the actual execution parameters of the completed working procedure and the second equipment state variable into a preset product quality prediction model together to obtain a corresponding product quality prediction value; screening candidate parameter tracks of which the product quality predicted value meets a preset product quality qualification threshold value to form a feasible solution set; Calculating the expected cost corresponding to each candidate parameter track in the feasible solution set; and selecting the candidate parameter track with the minimum predicted cost as the optimal technological parameter of the unfinished working procedure.
  4. 4. A full-process adaptive intelligent control method for electroplating according to claim 3, wherein generating a candidate parameter trajectory set in a process parameter feasible domain comprises: acquiring actual execution parameters of the last process of the current completed process, and taking the actual execution parameters as a starting point parameter track; Based on the starting point parameter track, the parameter stability among the working procedures is taken as a constraint condition, and a candidate parameter track set is generated according to a preset sampling strategy, wherein the parameter stability among the working procedures is constrained in such a way that the absolute value of the variation of the same technological parameter between technological parameter set values of two adjacent working procedures does not exceed a preset maximum variation threshold value.
  5. 5. A full-process adaptive intelligent control method according to claim 3, wherein said calculating the estimated cost for each candidate parameter trace in the feasible solution set comprises: Determining the process type and corresponding process parameters of each unfinished process for each candidate parameter track, wherein the process type comprises a pretreatment process, an electroplating process, a post-treatment process and a washing process; determining corresponding cost constitution items according to the process types, wherein the cost constitution items are divided into electric energy cost, liquid medicine cost and equipment occupation time cost; based on the corresponding technological parameters and cost constitution items, according to the corresponding preset calculation method, the expected cost of each unfinished procedure is obtained; and accumulating the predicted cost of each unfinished procedure to obtain the predicted cost corresponding to the candidate parameter track.
  6. 6. The method for intelligent control of electroplating full-process according to claim 5, wherein, during the electroplating process, after any process is completed on the workpieces in the current batch, the method further comprises: if the process type is an electroplating process, process monitoring data of the process in the processing process are obtained, wherein the process monitoring data comprise a tank voltage change curve and a cathode potential change curve; Extracting electroplating process characteristics from the tank voltage change curve and the cathode potential change curve, wherein the electroplating process characteristics comprise average tank voltage, average cathode potential, tank voltage rising rate and cathode potential drift amount; Based on the electroplating process characteristics, estimating the current electrochemical parameters through a preset electrochemical correlation model, and storing the current electrochemical parameters into a preset electroplating process state database.
  7. 7. The method for adaptive intelligent control of a complete process of electroplating according to claim 6, wherein the generating of the final product quality prediction value of the workpieces in the current batch by the preset final product quality prediction model based on the actual execution parameters of the completed process, the state variables of the second equipment and the initial process parameters corresponding to the incomplete process comprises: If the completed process includes an electroplating process, extracting the latest stored electrochemical parameters from a preset electroplating process state database; acquiring a reference deviation by presetting a reference parameter value based on the electrochemical parameter; And if the reference deviation reaches a preset reference deviation threshold, correcting the finished product quality predicted value based on the reference deviation to obtain a corrected finished product quality predicted value.
  8. 8. The method for adaptively controlling the whole electroplating process according to claim 1, further comprising, after the whole electroplating process is finished: Obtaining a final product quality actual measurement value of the current batch of workpieces after the complete flow process treatment; comparing the final product quality actual measurement value with the final product quality predicted value, and calculating a predicted deviation; When the predicted deviation exceeds a preset predicted deviation threshold, online correction is performed on the internal parameters of the preset finished product quality prediction model through a preset optimization method.
  9. 9. An electroplating full-flow self-adaptive intelligent control system, which is characterized by comprising: the data acquisition module (101) is used for acquiring the workpiece information of the current batch before electroplating treatment and acquiring the latest equipment state variables corresponding to all the procedures through a preset equipment state database; the initial parameter determining module (102) is used for generating initial technological parameters corresponding to each process according to the current batch workpiece information and the latest equipment state variables; The electroplating process monitoring module (103) is used for acquiring actual execution parameters of any process and corresponding first equipment state variables of the process after the current batch of workpieces completes the process in the electroplating process, and updating a preset equipment state database according to the first equipment state variables; The finished product quality prediction module (104) is used for acquiring a second equipment state variable corresponding to the unfinished working procedure of the current batch of workpieces, and generating a finished product quality prediction value of the current batch of workpieces through a preset finished product quality prediction model based on actual execution parameters of the finished working procedure, the second equipment state variable and initial technological parameters corresponding to the unfinished working procedure; And the process parameter optimization module (105) is used for judging whether the product quality predicted value of the workpieces in the current batch reaches a preset product quality qualification threshold, if not, taking the product quality predicted value as a constraint condition, taking the predicted cost of the unfinished process as an optimization target, and solving and generating the optimal process parameter of the unfinished process.
  10. 10. A computer readable storage medium storing a computer program capable of being loaded by a processor and executing a plating full-flow adaptive intelligent control method according to any one of claims 1 to 8.

Description

Electroplating full-flow self-adaptive intelligent control method and system Technical Field The application relates to the technical field of automatic electroplating control, in particular to a full-flow self-adaptive intelligent control method and system for electroplating. Background Electroplating is an important process in the field of surface treatment, and is widely applied to the processing of parts in the industries of machinery, electronics, automobiles and the like, and the whole electroplating process generally comprises a pretreatment process (degreasing, pickling), an electroplating process (galvanization, copper plating, nickel plating and the like), a post-treatment process (passivation, sealing) and the like. In the conventional electroplating control, the individual control optimization is usually performed on each process, the hidden influence of the upstream process state on the downstream process is not fully considered, the problem that local optimization and global suboptimal are easily caused is solved, for example, the tiny cleanliness fluctuation of the pretreatment process can cause the electroplating process to need to greatly improve the current density to compensate, the energy consumption is increased, and the quality problems of impurity precipitation, coating scorching and the like can also be caused, so that the final quality of an electroplated finished product is influenced. Disclosure of Invention The application aims to provide a self-adaptive intelligent control method and a self-adaptive intelligent control system for the whole electroplating process, so as to realize cooperative control and global optimization of the whole electroplating process. In a first aspect, the present application provides a full-flow adaptive intelligent control method for electroplating, including: before electroplating, acquiring current batch workpiece information, and acquiring the latest equipment state variables corresponding to all the procedures through a preset equipment state database; generating initial technological parameters corresponding to each procedure according to the current batch of workpiece information and the latest equipment state variables; In the electroplating treatment process, after any process is completed on the workpieces in the current batch, acquiring actual execution parameters of the process and corresponding first equipment state variables, and updating a preset equipment state database according to the first equipment state variables; Acquiring a second equipment state variable corresponding to the work piece of the current batch in the unfinished working procedure; Generating a finished product quality prediction value of the workpieces in the current batch by presetting a finished product quality prediction model based on actual execution parameters of the completed process, second equipment state variables and initial process parameters corresponding to the incomplete process; Judging whether the product quality predicted value of the workpieces in the current batch reaches a preset product quality qualification threshold value or not; if not, taking the predicted value of the quality of the finished product as a constraint condition and taking the predicted cost of the unfinished working procedure as an optimization target, and solving and generating the optimal technological parameters of the unfinished working procedure. According to the technical scheme, the initial technological parameters are generated based on the current workpiece information and the equipment state variables at the end of the previous batch before electroplating treatment, so that the effective transfer of the state between batches is realized, the quality of a finished product is predicted according to the actual execution parameters when one process is finished in the electroplating process, the cost is minimized and optimized only when the prediction does not reach the standard, unnecessary frequent adjustment is avoided, and therefore, the overall optimization of the whole process energy consumption and the materials is realized on the premise of ensuring the quality of the finished product to be qualified, and the stability and the economy of electroplating production are obviously improved. Optionally, generating initial process parameters corresponding to each process according to the current batch of workpiece information and the latest equipment state variables includes: acquiring reference process parameters corresponding to each procedure through a preset workpiece-parameter mapping library according to the current batch workpiece information; calculating and acquiring equipment capacity attenuation rate of each procedure by presetting a reference state variable based on the latest equipment state variable; Determining the compensation quantity of the process parameters of each process through a preset parameter compensation rule based on the equipment capacity a