CN-121995885-A - Intelligent cooperative control system and method for cleaning warping products

CN121995885ACN 121995885 ACN121995885 ACN 121995885ACN-121995885-A

Abstract

The invention discloses an intelligent cooperative control system and method for cleaning a warped product, which relate to the technical field of cleaning intelligent control and are used for acquiring data of the warped product to obtain characteristics of the warped product, acquiring actual cleaning parameters when the warped product is cleaned, dividing a warped product cleaning sub-process, calculating deviation degree of the warped product of the sub-process, analyzing influence coefficients of the cleaning parameters on the cleaning sub-process based on the deviation degree of the warped product of the sub-process, analyzing influence coefficients of the cleaning sub-process on cleaning defective rate, analyzing participation degree of the actual cleaning parameters of the warped product of a new batch on the defective rate of the product when the warped product of the new batch is cleaned, recording the participation degree into a defective rate abnormal emergency processing database, and updating the database in real time according to a preset period.

Inventors

CAO HAIYANG
XU BIN
DING QIN
CHEN YUANHUA

Assignees

江苏富乐华半导体科技股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260209

Claims (9)

1. The intelligent cooperative control method for cleaning the warping product is characterized by comprising the following steps of: s1, acquiring data of a warped product to obtain characteristics of the warped product, and acquiring actual cleaning parameters when the warped product is cleaned; S2, dividing a warp product cleaning sub-process based on the warp product cleaning process, calculating deviation degree of the warp product of the sub-process, comparing actual states of each batch of products after corresponding sub-links with standard states based on the deviation degree of the warp product of the sub-process, determining deviation degree of each batch of products in the sub-links, considering actual cleaning parameters of cleaning, and analyzing influence degree of the cleaning parameters on the sub-links; s3, analyzing the influence coefficient of the cleaning sub-process on the cleaning reject ratio based on the cleaning reject ratio in the historical data; s4, analyzing the participation degree of actual cleaning parameters of the new batch of warped products on the defective rate of the products when the new batch of warped products are subjected to cleaning tasks, and recording the participation degree into a defective rate abnormal emergency processing database; s5, monitoring the reject ratio of the product in real time, and sending an alarm for correcting the actual cleaning parameters and an alarm for equipment abnormality to management personnel according to the reject ratio; and S6, updating the database in real time according to a preset period.
2. The intelligent cooperative control method for cleaning a warped product according to claim 1, wherein when the influence coefficient of cleaning parameters on the cleaning sub-process is analyzed based on the deviation degree of the warped product in the sub-process, the cleaning process of the warped product is divided into a plurality of sub-links, a constructed product characteristic database is called, the actual state and the standard state of each batch of products after the products pass through the corresponding sub-links are compared, the deviation degree of the single batch of products in the sub-links is determined, and the preset standard cleaning parameters and the actual cleaning parameters of each batch are combined, so that the action intensity of each parameter on the cleaning effect of the sub-links is measured, and the relative influence coefficient of the cleaning parameters on the sub-links is obtained.
3. The intelligent cooperative control method for cleaning a warped product according to claim 2, wherein in step S1, after authorization, data acquisition is performed on the warped product to obtain warped product data of the warped product, preprocessing and normalizing are performed on the warped product data of any type of warped product to obtain warped product characteristics of any type of warped product, and further, a warped product characteristic database is established, preset cleaning parameters are used as standard cleaning parameters, and actual cleaning parameters during cleaning of any batch of warped products are acquired in real time.
4. The intelligent cooperative control method for cleaning a warped product according to claim 3, wherein in step S2, the warped product cleaning process is divided into M warped product cleaning sub-processes based on the warped product cleaning process, m=1, 2,..m, for the mth cleaning sub-process, the warped product standard feature of the mth cleaning sub-process is { a 1_m ,A 2_m ,…,A n_m ,…,A N_m }, where N represents the number of warped product standard features, a n_m represents the nth warped product standard feature, the warped product standard feature of the mth cleaning sub-process represents the standard feature specified after the warped product passes through the mth cleaning sub-process, the warped product feature database is invoked, the number of batches of the warped product that is cleaned is P, wherein the warped product feature of the P-th warp product passes through the mth cleaning sub-process is { B 1_m_p ,B 2_m_p ,…,B n_m_p ,…,B N_m_p }, wherein B n_m_p represents the N-th warp product feature of the mth cleaning sub-process, p=1, 2,..p, and thus obtaining the warp product bias of the mth cleaning sub-process C p_m : ; substituting p=1, 2 one by one, P, obtaining a sub-process warp product deviation degree of an mth cleaning sub-process of P batches of warp products, wherein the sub-process warp product deviation degree of the mth cleaning sub-process of the P batches of warp products is { C 1_m ,C 2_m ,…,C p_m ,…,C P_m }, calling a standard cleaning parameter of the cleaning process, wherein the standard cleaning parameter of the cleaning process is { R 1 ,R 2 ,…,R y ,…,R Y }, R y represents a y standard cleaning parameter, calling an actual cleaning parameter of the P batches of warp products, and the actual cleaning parameter of the P batches of warp products is { R 1_p ,R 2_p ,…,R y_p ,…,R Y_p }, wherein R y_p represents a y actual cleaning parameter of the P batches of warp products, and further calculating the influence degree D y_m of the y cleaning parameter on the mth cleaning sub-process: ; Where C m represents the average value of all values in C 1_m ,C 2_m ,…,C p_m ,…,C P_m , substituting y=1, 2, Y, resulting in the degree of influence of Y cleaning parameters on the mth cleaning sub-process D 1_m ,D 2_m ,…,D y_m ,…,D Y_m , and further obtains the influence coefficient D y_m of the Y cleaning parameter on the m cleaning sub-process, the influence coefficient of the Y-th cleaning parameter on the m-th cleaning sub-process is the ratio of the influence degree of the Y-th cleaning parameter on the m-th cleaning sub-process to the sum of the influence degree of the Y-th cleaning parameter on the m-th cleaning sub-process, and y=1, 2 is substituted into the ratio of Y to obtain the influence coefficient of the Y-th cleaning parameter on the m-th cleaning sub-process, and the influence coefficient of the Y-th cleaning parameter on the m-th cleaning sub-process is { D 1_m ,d 2_m ,…,d y_m ,…,d Y_m }.
5. The intelligent cooperative control method for cleaning a warpage product of claim 4, wherein in step S3, based on the history data, a cleaning failure rate of P batches of warpage products after M cleaning sub-processes is obtained, the cleaning failure rate of P batches of warpage products after M cleaning sub-processes is { E 1 ,E 2 ,…,E p ,…,E P }, wherein E p represents the cleaning failure rate of P batches of warpage products after M cleaning sub-processes, and further the influence degree F m of the M cleaning sub-processes on the cleaning failure rate is calculated: ; Where E represents the average of all values in { E 1 ,E 2 ,…,E p ,…,E P }, substituting m=1, 2, M, obtaining the degree of influence of M cleaning sub-flows on the cleaning failure rate { F 1 ,F 2 ,…,F m ,…,F M }, and obtaining the influence coefficient { F 1 ,f 2 ,…,f m ,…,f M } of the M cleaning sub-processes on the cleaning failure rate, wherein F m is the influence coefficient of the mth cleaning sub-process on the cleaning failure rate, and F m is the ratio of the sum of all values in F m and { F 1 ,F 2 ,…,F m ,…,F M }.
6. The intelligent cooperative control method for cleaning a warped product according to claim 5, wherein in step S4, when a new batch of warped product is subjected to a cleaning task, an actual cleaning parameter of the new batch of warped product is obtained, the actual cleaning parameter of the new batch of warped product is { S 1 ,S 2 ,…,S y ,…,S Y }, S y represents a Y-th actual cleaning parameter of the new batch of warped product, a Y-th actual cleaning parameter deviation degree T y ,T y =|(S y -R y )/R y is calculated, a product of a Y-th actual cleaning parameter deviation degree and an influence coefficient d y_m of the Y-th actual cleaning parameter on the M-th cleaning sub-process is obtained, a defective rate participation coefficient V y ,V y of the Y-th actual cleaning parameter on the defective rate is obtained, a sum of a participation coefficient of the Y-th actual cleaning parameter on the M-th cleaning sub-process and an influence coefficient of the corresponding M-th cleaning sub-process is obtained, a participation coefficient U y_m corresponds to the influence coefficient f m , and a defective rate obtained by substituting Y = 1,2, and a defective rate participation coefficient V y ,V y of the Y actual cleaning parameter on the defective rate is obtained as a sum of products of the influence coefficients of the Y actual cleaning sub-process on the M-th actual cleaning sub-process.
7. The intelligent cooperative control method for cleaning the warping products according to claim 6, wherein in step S5, in the process of cleaning the warping products in a new batch, the cleaning reject ratio of the warping products is monitored in real time, if the cleaning reject ratio is lower than a preset cleaning reject ratio threshold, the actual reject ratio is judged to be normal, the cleaning of the warping products in the new batch is continued, otherwise, the reject ratio is judged to be abnormal, the cleaning task is suspended, the actual cleaning parameter recommendation manager is checked from high to low according to the reject ratio participation coefficients of the Y actual cleaning parameters, the cleaning task is re-entered after the check, the re-entry number of the cleaning tasks is calculated in the single cleaning task, if the re-entry number is lower than the preset re-entry number threshold, the cleaning task is judged to be normal, otherwise, the cleaning equipment is judged to be faulty, and a cleaning equipment fault alarm is sent to a manager.
8. The intelligent cooperative control method for cleaning a warped product according to claim 6, wherein in step S6, the database is updated after one warped product cleaning task management cycle is performed.
9. The intelligent cooperative control system for cleaning the warping product is applied to the intelligent cooperative control method for cleaning the warping product according to any one of claims 1 to 8, and is characterized by comprising a warping product data acquisition module, a cleaning parameter influence analysis module, a sub-process defective rate analysis module, a new batch parameter participation analysis module, a cleaning defective rate monitoring and early warning module and a cleaning data period updating module; the warpage product data acquisition module is used for acquiring data of a warpage product to acquire the characteristics of the warpage product; The cleaning parameter influence analysis module is used for dividing a cleaning sub-process of the warped product based on the cleaning process of the warped product, calculating deviation degree of the warped product of the sub-process, comparing actual states of each batch of products after the products pass through corresponding sub-links with standard states based on the deviation degree of the warped product of the sub-process, determining deviation degree of each batch of products in the sub-links, considering actual cleaning parameters of cleaning, and analyzing influence degree of the cleaning parameters on the sub-links; The sub-flow reject ratio analysis module is used for analyzing the influence coefficient of the cleaning sub-flow on the cleaning reject ratio based on the cleaning reject ratio in the historical data; The new batch parameter participation analysis module is used for analyzing participation degree of actual cleaning parameters of the new batch of warped products on the defective rate of the products when the new batch of warped products are subjected to cleaning tasks, and recording the participation degree into the defective rate abnormal emergency processing database; the cleaning defective rate monitoring and early warning module is used for monitoring the defective rate of products in real time and sending out an alarm for correcting actual cleaning parameters and an alarm for equipment abnormality to management personnel according to the defective rate; the cleaning data period updating module is used for updating the database in real time according to a preset period.

Description

Intelligent cooperative control system and method for cleaning warping products Technical Field The invention relates to the technical field of intelligent cleaning control, in particular to an intelligent cooperative control system and method for cleaning a warping product. Background In the technical field of cleaning of warping products, a core technical problem of lack of a full-process accurate cooperative control mechanism exists for a long time, and the problem directly causes the technical dilemma that a cleaning link generally faces poor quality stability, low production efficiency and high comprehensive cost. Specifically, due to the lack of support for precise collaborative control of the whole process, the dynamic adaptation relation between product features and cleaning parameters cannot be constructed in the prior art, only a uniform solidified cleaning parameter scheme can be adopted, the precise disassembly and collaborative linkage of the whole process cannot be realized by the uniform solidified cleaning parameter scheme, the associated influence mechanism of each subdivision cleaning link on the quality of the final product cannot be clarified, and when the cleaning failure rate is abnormal, blind investigation can only be carried out on all cleaning parameters and links, so that the root of the problem is difficult to quickly locate, a targeted regulation and control scheme cannot be formulated, the occupation ratio of the poor product is high, and the reworking and repairing cost is greatly increased. In addition, the lack of a full-flow accurate collaborative management and control mechanism also causes the existing cleaning management system to lack the normalized data iteration and equipment early warning linkage capability, so that on one hand, dynamic optimization of a cleaning scheme cannot be realized by integrally utilizing various data in the actual cleaning process, on the other hand, equipment fault hidden danger is difficult to be prejudged through flow data monitoring, and the equipment fault hidden danger is often required to be treated after equipment shutdown fault occurs, thereby causing production flow interruption and further exacerbating the dual dilemma of quality and efficiency. Disclosure of Invention The invention aims to provide an intelligent cooperative control system and method for cleaning a warping product, so as to solve the problems in the background art. In order to solve the technical problems, the invention provides the following technical scheme that the intelligent cooperative control method for cleaning the warping product comprises the following steps: s1, acquiring data of a warped product to obtain characteristics of the warped product, and acquiring actual cleaning parameters when the warped product is cleaned; S2, dividing a warp product cleaning sub-process based on the warp product cleaning process, calculating deviation degree of the warp product of the sub-process, comparing actual states of each batch of products after corresponding sub-links with standard states based on the deviation degree of the warp product of the sub-process, determining deviation degree of each batch of products in the sub-links, considering actual cleaning parameters of cleaning, and analyzing influence degree of the cleaning parameters on the sub-links; s3, analyzing the influence coefficient of the cleaning sub-process on the cleaning reject ratio based on the cleaning reject ratio in the historical data; s4, analyzing the participation degree of actual cleaning parameters of the new batch of warped products on the defective rate of the products when the new batch of warped products are subjected to cleaning tasks, and recording the participation degree into a defective rate abnormal emergency processing database; s5, monitoring the reject ratio of the product in real time, and sending an alarm for correcting the actual cleaning parameters and an alarm for equipment abnormality to management personnel according to the reject ratio; and S6, updating the database in real time according to a preset period. When the influence coefficient of the cleaning parameter on the cleaning sub-process is analyzed based on the deviation degree of the warp product in the sub-process, the cleaning process of the warp product is divided into a plurality of sub-links, a constructed product characteristic database is called, the actual state of each batch of products after the products pass through the corresponding sub-link is compared with the standard state, so that the deviation degree of the single batch of products in the sub-link is determined, the action intensity of each parameter on the cleaning effect of the sub-link is measured by combining the preset standard cleaning parameter and the actual cleaning parameter of each batch, and the relative influence coefficient of the cleaning parameter on the sub-link is further obtained. Further, in step S1, after authorization, dat