Automatic electrochemical liquid medicine adding system

Abstract

The invention relates to the technical field of liquid medicine adding, in particular to an automatic electrochemical liquid medicine adding system which comprises a liquid adding behavior dynamic optimization module, and the liquid adding behavior dynamic optimization module combines a first risk influence value and a second risk influence value to judge the optimization requirement of the liquid adding behavior at the current time; and when an optimization demand exists, generating different batch liquid adding behavior planning schemes, respectively calculating the intervention interference value of each batch liquid adding behavior planning scheme to the production line in the execution process, and screening the batch liquid adding behavior planning scheme corresponding to the minimum intervention interference value as a liquid adding behavior dynamic optimization result. In the automatic electrochemical liquid medicine adding process, liquid medicine in the liquid medicine storage tank is automatically supplemented; in addition, in consideration of the operation state of the current production equipment and the influence of the liquid medicine adding behavior on the produced product, the dynamic optimization of the liquid medicine adding behavior is realized, the interference of the liquid medicine adding behavior on the equipment operation is reduced, and the effective control of the liquid medicine adding behavior is realized.

Description

Technical Field

[0001] The invention relates to the technical field of drug solution addition, in particular to an automated electrochemical drug solution addition system. Background Art

[0002] With the continuous advancement of automation technology, more and more industries have begun to adopt automated equipment for production and management to improve production efficiency and product quality; in the field of electrochemistry, the introduction of automation technology has provided a new solution for the addition of liquid medicines, realizing the transition from manual operation to automated control. Compared with manual addition, which is easily affected by human factors and leads to unstable liquid medicine ratio, the automated electrochemical liquid medicine addition system can achieve accurate quantification of liquid medicine ratio, and reduce the impact of liquid medicine addition process on product quality to a certain extent.

[0003] Existing automated electrochemical liquid addition systems often simply monitor the liquid level in the liquid storage tank through sensors, and automatically prepare the liquid to be added when the monitoring result is abnormal, and realize automatic replenishment of the liquid in the liquid storage tank; however, this method does not take into account the operating status of the current production equipment and the impact of the liquid addition behavior on the production products, fails to achieve dynamic optimization of the liquid addition behavior, and fails to reduce the interference of the liquid addition behavior on the equipment operation; therefore, the existing technology has major defects. Summary of the invention

[0004] The object of the present invention is to provide an automated electrochemical solution adding system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solution: an automated electrochemical liquid addition system, the system comprising: A liquid adding behavior determination module, which obtains the liquid data in each liquid storage tank at the current time in real time through a sensor, and compares the obtained liquid data with the standard parameters of the corresponding liquid storage tank, and calculates the liquid adding demand value of each liquid storage tank; An addition amount prediction module, wherein the addition amount prediction module generates a characteristic parameter of the drug liquid addition corresponding to the current time according to the obtained drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank; A liquid addition behavior impact analysis module, wherein the liquid addition behavior impact analysis module obtains the amount of liquid added corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating status of the production line to which the corresponding liquid storage tank belongs at the current time, and combines the impact of different liquid addition behaviors on the production line operating status in historical data to predict the impact of the corresponding liquid addition amount added to the corresponding liquid storage tank at the current time on the corresponding production line to obtain a first risk impact value; combines the operating data of the current production line to predict the delay of each liquid addition, and evaluates the impact of the corresponding liquid addition delay on the corresponding production line to obtain a second risk impact value; A liquid-adding behavior dynamic optimization module, wherein the liquid-adding behavior dynamic optimization module combines the first risk impact value and the second risk impact value to determine the optimization requirements of the liquid-adding behavior at the current time; and when there is an optimization requirement, generates different batch liquid-adding behavior planning schemes, and respectively calculates the intervention interference value of each batch liquid-adding behavior planning scheme on the production line during the execution process, and selects the batch liquid-adding behavior planning scheme with the smallest corresponding intervention interference value as the liquid-adding behavior dynamic optimization result; The liquid adding behavior warning module generates a liquid adding behavior warning report based on the optimization demand judgment result of the liquid adding behavior at the current time and the liquid adding behavior dynamic optimization result obtained by the liquid adding behavior dynamic optimization module, and feeds it back to the corresponding administrator for confirmation.

[0006] Furthermore, the drug solution data includes the composition of the drug solution, the concentration of each component and the total amount of the drug solution; When calculating the liquid addition requirement value of each liquid storage tank in the liquid addition behavior determination module, the liquid addition requirement value of the i-th liquid storage tank is recorded as Qi, , Among them, β is the demand conversion factor and β is a constant preset in the database; Cik represents the absolute value of the difference between the concentration of the kth component in the liquid data of the i-th liquid storage tank at the current time and the midpoint of the concentration interval corresponding to the corresponding component in the standard parameters of the corresponding liquid storage tank; ki represents the number of component types in the liquid data of the i-th liquid storage tank at the current time; Lik represents the interval length of the concentration interval corresponding to the kth component in the liquid data of the i-th liquid storage tank in the corresponding standard parameter; Zi represents the inverse of the difference between the total amount of liquid medicine in the liquid medicine data of the i-th liquid medicine storage tank at the current time and the minimum value of the total amount of liquid medicine in the corresponding standard parameter; P{,} represents a demand judgment function. When the value of the first parameter in the function is greater than or equal to the value of the second parameter, the corresponding function result is judged to be the value of the first parameter in the function; otherwise, the corresponding function result is judged to be 0.

[0007] The present invention analyzes the drug liquid data to achieve comprehensive quantification of the deviation between the drug liquid storage tank condition and the corresponding standard parameters, thereby achieving accurate judgment of the liquid filling behavior of the drug liquid storage tank.

[0008] Furthermore, the characteristic parameters of the liquid medicine addition corresponding to the current time include the composition of the added liquid medicine corresponding to each liquid medicine storage tank, the concentration of each component and the amount of liquid medicine added; When the addition amount prediction module generates the characteristic parameters of the drug liquid addition corresponding to the current time, the drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank are obtained; Arrange the order of adding medicines corresponding to each medicine storage tank in the medicine addition characteristic parameter corresponding to the current time according to the corresponding medicine addition demand value from large to small, and the medicine addition amount corresponding to the i-th medicine storage tank is the inverse number of the difference between the total amount of medicine in the medicine data of the i-th medicine storage tank at the current time and the minimum value of the total amount of medicine in the corresponding standard parameter; The concentrations corresponding to the various components in the characteristic parameters of the liquid medicine addition corresponding to the current time are obtained by querying the values ​​corresponding to the corresponding data groups in the preset forms in the database. The data groups corresponding to the corresponding components include the concentrations of the corresponding components before adding the medicine, the concentration ranges corresponding to the corresponding components in the corresponding standard parameters, and the amount of liquid medicine added.

[0009] Furthermore, the liquid addition behavior impact analysis module includes an addition amount risk analysis unit and an addition delay risk analysis unit. The addition amount risk analysis unit obtains the amount of medicine added corresponding to each medicine storage tank in the medicine addition characteristic parameter and the operating status of the production line to which the corresponding medicine storage tank belongs at the current time, and combines the impact of different medicine addition behaviors on the production line operating status in the historical data to predict the impact of the corresponding medicine addition amount added to the corresponding medicine storage tank at the current time on the corresponding production line to obtain a first risk impact value; The addition delay risk analysis unit predicts the delay of adding each drug solution in combination with the operation data of the current production line, and evaluates the impact of the corresponding drug solution addition delay on the corresponding production line to obtain a second risk impact value.

[0010] The present invention uses historical data to analyze the interference of the added amount of liquid adding behavior on the production line operation and the interference of the corresponding addition delay when the production line is shut down on the production line operation, and quantifies the corresponding risk impact degrees in the two situations to achieve effective screening of liquid adding methods for the liquid medicine storage tank, and provides data support for determining the optimization needs of the liquid adding behavior at the current time and screening of optimization plans in subsequent steps.

[0011] Further, when the additive amount risk analysis unit obtains the first risk impact value, Obtain the amount of liquid medicine added corresponding to each liquid medicine storage tank in the liquid medicine addition characteristic parameters and the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time, wherein the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time includes the type of production product corresponding to the production line to which the corresponding liquid medicine storage tank belongs at the current time, the waiting time, the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid medicine addition demand value, the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change amount of the liquid medicine addition demand value, and the change function of the liquid medicine addition demand value corresponding to the corresponding product type with the running time; When the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time is equal to the corresponding product type produced by the corresponding production line in the historical data, the quotient of the remaining product quantity to be produced at the current time and the average production speed of the corresponding product type in the historical data; When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, obtain each demand-related data pair corresponding to the i-th liquid storage tank in the historical data, wherein the first value of the demand-related data pair is the liquid addition demand value of the liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; according to the preset function model y=-x -a +b (where a and b are both constants, and the quantitative acquisition of a and b values ​​can be achieved through function fitting) to fit each demand-related data pair obtained, and calculate the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each associated data pair, respectively, to obtain the data fitting deviation corresponding to each fitting result, and use the fitting function corresponding to the minimum value of the obtained data fitting deviation as the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, recorded as WQi (x); When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change in the demand value of the medicine liquid addition of the ith medicine liquid storage tank, obtain each demand mutation associated data pair corresponding to the ith medicine liquid storage tank in the historical data, wherein the first value of the demand mutation associated data pair is the sudden change in the demand for medicine liquid addition of the medicine liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; the sudden change in the demand for medicine liquid addition is equal to the maximum difference between the corresponding values ​​of the demand for medicine liquid addition at different time points per unit time after the medicine adding operation is performed; according to the preset function model y1=-x1 -a+b fits each demand mutation associated data pair obtained, and calculates the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each demand mutation associated data pair, and obtains the data fitting deviation corresponding to each fitting result. The fitting function corresponding to the minimum value of the obtained data fitting deviation is used as the relationship function between the product abnormality rate corresponding to the corresponding product type and the mutation amount of the liquid addition demand value of the i-th liquid storage tank, recorded as WTi (x1); When obtaining the function of the change of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, obtain each operation demand associated data pair corresponding to the i-th liquid medicine storage tank in the historical data, the first value of the operation demand associated data pair is the subsequent operation time based on the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type, and the second value is the liquid addition demand value of the liquid medicine storage tank; fit each obtained operation demand associated data pair according to the preset linear regression model, and use the obtained fitting function as the change function of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, recorded as WYi(t); The first risk impact value corresponding to the addition of the corresponding amount of liquid medicine to the i-th liquid medicine storage tank at the current time is recorded as FOi, The FOi=WTi(B), Among them, B represents the sudden change in the demand for adding liquid medicine corresponding to the amount of liquid medicine added to the i-th liquid medicine storage tank at the current time; WTi (B) represents the function value corresponding to WTi (x1) when x1 is B; The value of B is equal to the average value of the mutation value of the liquid addition requirement corresponding to each element in the reference array corresponding to Qi; The reference array corresponding to Qi is obtained by querying the historical database for all the liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and the corresponding liquid addition amount added in the i-th liquid storage tank at the current time is less than a preset value.

[0012] Further, when the delay risk analysis unit is added to obtain the second risk impact value, The liquid medicine addition delay corresponding to the i-th liquid medicine storage tank is equal to the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time; The second risk impact value corresponding to the delay in adding the liquid medicine corresponding to the i-th liquid medicine storage tank is recorded as FTi, FTi = WQi (WYi (tsi)), Among them, tsi represents the delay of adding liquid medicine corresponding to the i-th liquid medicine storage tank; WYi(tsi) represents the function value corresponding to WYi(t) when t is tsi; WQi(WYi(tsi)) represents the function value corresponding to WQi(x) when x is WYi(tsi).

[0013] Furthermore, when the dynamic optimization module for liquid adding behavior determines the optimization demand for liquid adding behavior at the current time, when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both greater than or equal to the preset product abnormality rate, it is determined that there is an optimization demand for liquid adding behavior at the current time; when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both less than the preset product abnormality rate, it is determined that there is no optimization demand for liquid adding behavior at the current time. If the first risk impact value corresponding to the i-th drug liquid storage tank is less than or equal to the second risk impact value, it is determined that after the waiting time in the operation state of the production line to which the i-th drug liquid storage tank belongs at the current time, the liquid adding behavior operation is performed according to the drug liquid adding characteristic parameters corresponding to the current time; otherwise, the liquid adding behavior operation is immediately performed according to the drug liquid adding characteristic parameters corresponding to the current time; When the dynamic optimization module for liquid adding behavior generates different batch liquid adding behavior planning schemes, the corresponding amount of liquid added to the i-th liquid storage tank at the current time is evenly divided into n parts and two batches, the liquid adding time corresponding to the first batch is the current time, and the liquid adding time corresponding to the second batch is the waiting time in the running state of the production line to which the i-th liquid storage tank belongs at the current time; the number of liquid addition amounts corresponding to each liquid storage tank in the first batch and the second batch is adjusted respectively, and different liquid adding behavior planning schemes corresponding to the corresponding liquid storage tanks are generated, and the liquid adding behavior planning schemes corresponding to each liquid storage tank are combined to generate different batch liquid adding behavior planning schemes, and the sum of the number of liquid addition amounts corresponding to the first batch and the second batch corresponding to the corresponding liquid storage tank in each batch liquid adding behavior planning scheme is n, and n is a constant preset in the database; When the dynamic optimization module for liquid adding behavior respectively calculates the intervention interference value of each batch of liquid adding behavior planning scheme on the production line during the execution process, the intervention interference value of the j-th batch of liquid adding behavior planning scheme on the production line during the execution process is recorded as GRj. , Among them, ig represents the number of liquid medicine storage tanks; HOij represents the prediction result of the first risk impact value corresponding to the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme when the corresponding first batch liquid filling scheme is executed; HTij represents the prediction result of the second risk impact value corresponding to the liquid addition demand value after the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme executes the corresponding first batch liquid filling scheme; The liquid addition demand value corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding first batch liquid addition scheme is equal to the average value of the liquid addition demand values ​​corresponding to each element in the reference set corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding liquid addition behavior; The reference set corresponding to the ith liquid storage tank in the jth batch liquid addition behavior planning scheme is obtained by querying the historical database for all liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and Mij is less than a preset value, wherein Mij represents the corresponding liquid addition amount corresponding to the first batch liquid addition scheme corresponding to the ith liquid storage tank in the jth batch liquid addition behavior planning scheme.

[0014] Furthermore, when the liquid adding behavior warning module generates a liquid adding behavior warning report, if there is no optimization demand for liquid adding behavior in each liquid storage tank at the current time, a set consisting of the current time point, each liquid adding characteristic parameter at the current time and the corresponding execution time is used as the liquid adding behavior warning report corresponding to the current time; If there is a need to optimize the liquid filling behavior of the liquid storage tank at the current time, the set consisting of the current time point and the dynamic optimization results of the liquid filling behavior corresponding to the current time is used as the liquid filling behavior warning report corresponding to the current time; After the generated liquid adding behavior warning report is fed back to the corresponding administrator for confirmation, when the corresponding administrator receives and approves the corresponding liquid adding behavior warning report or the corresponding administrator does not receive the corresponding liquid adding behavior warning report within the preset time, the liquid adding operation on the corresponding medicine liquid storage tank is automatically executed according to the liquid adding behavior planning plan in the corresponding liquid adding behavior warning report; otherwise, the corresponding administrator is reminded to manually perform the liquid adding operation on the corresponding medicine liquid storage tank.

[0015] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in the process of automated electrochemical liquid addition, the present invention not only monitors the liquid level in the liquid storage tank through sensors, and realizes automatic replenishment of the liquid in the liquid storage tank; it also takes into account the operating status of the current production equipment and the impact of the liquid addition behavior on the production products, and realizes dynamic optimization of the liquid addition behavior, reduces the interference of the liquid addition behavior on the equipment operation, and realizes effective control of the liquid addition behavior. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a structural schematic diagram of the automated electrochemical liquid adding system of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 The present invention provides a technical solution: an automated electrochemical liquid addition system, the system comprising: A liquid adding behavior determination module, which obtains the liquid data in each liquid storage tank at the current time in real time through a sensor, and compares the obtained liquid data with the standard parameters of the corresponding liquid storage tank, and calculates the liquid adding demand value of each liquid storage tank; The drug solution data includes the composition of the drug solution, the concentration of each component and the total amount of the drug solution; When calculating the liquid addition requirement value of each liquid storage tank in the liquid addition behavior determination module, the liquid addition requirement value of the i-th liquid storage tank is recorded as Qi, , Among them, β is the demand conversion factor and β is a constant preset in the database; Cik represents the absolute value of the difference between the concentration of the kth component in the liquid data of the i-th liquid storage tank at the current time and the midpoint of the concentration interval corresponding to the corresponding component in the standard parameters of the corresponding liquid storage tank; ki represents the number of component types in the liquid data of the i-th liquid storage tank at the current time; Lik represents the interval length of the concentration interval corresponding to the kth component in the liquid data of the i-th liquid storage tank in the corresponding standard parameter; Zi represents the inverse of the difference between the total amount of liquid medicine in the liquid medicine data of the i-th liquid medicine storage tank at the current time and the minimum value of the total amount of liquid medicine in the corresponding standard parameter; P{,} represents a demand judgment function. When the value of the first parameter in the function is greater than or equal to the value of the second parameter, the corresponding function result is judged to be the value of the first parameter in the function; otherwise, the corresponding function result is judged to be 0.

[0019] An addition amount prediction module, wherein the addition amount prediction module generates a characteristic parameter of the drug liquid addition corresponding to the current time according to the obtained drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank; The characteristic parameters of the liquid medicine addition corresponding to the current time include the composition of the liquid medicine added corresponding to each liquid medicine storage tank, the concentration of each component and the amount of liquid medicine added; When the addition amount prediction module generates the characteristic parameters of the drug liquid addition corresponding to the current time, the drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank are obtained; Arrange the order of adding medicines corresponding to each medicine storage tank in the medicine addition characteristic parameter corresponding to the current time according to the corresponding medicine addition demand value from large to small, and the medicine addition amount corresponding to the i-th medicine storage tank is the inverse number of the difference between the total amount of medicine in the medicine data of the i-th medicine storage tank at the current time and the minimum value of the total amount of medicine in the corresponding standard parameter; The concentrations corresponding to the various components in the characteristic parameters of the liquid medicine addition corresponding to the current time are obtained by querying the values ​​corresponding to the corresponding data groups in the preset forms in the database. The data groups corresponding to the corresponding components include the concentrations of the corresponding components before adding the medicine, the concentration ranges corresponding to the corresponding components in the corresponding standard parameters, and the amount of liquid medicine added.

[0020] A liquid addition behavior impact analysis module, wherein the liquid addition behavior impact analysis module obtains the amount of liquid added corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating status of the production line to which the corresponding liquid storage tank belongs at the current time, and combines the impact of different liquid addition behaviors on the production line operating status in historical data to predict the impact of the corresponding liquid addition amount added to the corresponding liquid storage tank at the current time on the corresponding production line to obtain a first risk impact value; combines the operating data of the current production line to predict the delay of each liquid addition, and evaluates the impact of the corresponding liquid addition delay on the corresponding production line to obtain a second risk impact value; The liquid addition behavior impact analysis module includes an addition amount risk analysis unit and an addition delay risk analysis unit. The addition amount risk analysis unit obtains the amount of medicine added corresponding to each medicine storage tank in the medicine addition characteristic parameter and the operating status of the production line to which the corresponding medicine storage tank belongs at the current time, and combines the impact of different medicine addition behaviors on the production line operating status in the historical data to predict the impact of the corresponding medicine addition amount added to the corresponding medicine storage tank at the current time on the corresponding production line to obtain a first risk impact value; When the additive amount risk analysis unit obtains the first risk impact value, Obtain the amount of liquid medicine added corresponding to each liquid medicine storage tank in the liquid medicine addition characteristic parameters and the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time, wherein the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time includes the type of production product corresponding to the production line to which the corresponding liquid medicine storage tank belongs at the current time, the waiting time, the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid medicine addition demand value, the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change amount of the liquid medicine addition demand value, and the change function of the liquid medicine addition demand value corresponding to the corresponding product type with the running time; When the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time is equal to the corresponding product type produced by the corresponding production line in the historical data, the quotient of the remaining product quantity to be produced at the current time and the average production speed of the corresponding product type in the historical data; When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, obtain each demand-related data pair corresponding to the i-th liquid storage tank in the historical data, wherein the first value of the demand-related data pair is the liquid addition demand value of the liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; according to the preset function model y=-x -a +b (where a and b are both constants, and the quantitative acquisition of a and b values ​​can be achieved through function fitting) to fit each demand-related data pair obtained, and calculate the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each associated data pair, respectively, to obtain the data fitting deviation corresponding to each fitting result, and use the fitting function corresponding to the minimum value of the obtained data fitting deviation as the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, recorded as WQi (x); In this embodiment, when obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, the function model y=-x -a +b is used for function fitting, which is quantified into a specific coordinate system. The parameter corresponding to the x-axis is the required value of adding liquid medicine in the liquid medicine storage tank, and the parameter corresponding to the y-axis is the product abnormality rate corresponding to the corresponding product type. The fitting result is actually a quantitative acquisition of the a and b values.

[0021] When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change in the demand value of the medicine liquid addition of the ith medicine liquid storage tank, obtain each demand mutation associated data pair corresponding to the ith medicine liquid storage tank in the historical data, wherein the first value of the demand mutation associated data pair is the sudden change in the demand for medicine liquid addition of the medicine liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; the sudden change in the demand for medicine liquid addition is equal to the maximum difference between the corresponding values ​​of the demand for medicine liquid addition at different time points per unit time after the medicine adding operation is performed; according to the preset function model y1=-x1 -a +b fits each demand mutation associated data pair obtained, and calculates the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each demand mutation associated data pair, and obtains the data fitting deviation corresponding to each fitting result. The fitting function corresponding to the minimum value of the obtained data fitting deviation is used as the relationship function between the product abnormality rate corresponding to the corresponding product type and the mutation amount of the liquid addition demand value of the i-th liquid storage tank, recorded as WTi (x1); When obtaining the function of the change of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, obtain each operation demand associated data pair corresponding to the i-th liquid medicine storage tank in the historical data, the first value of the operation demand associated data pair is the subsequent operation time based on the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type, and the second value is the liquid addition demand value of the liquid medicine storage tank; fit each obtained operation demand associated data pair according to the preset linear regression model, and use the obtained fitting function as the change function of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, recorded as WYi(t); The first risk impact value corresponding to the addition of the corresponding amount of liquid medicine to the i-th liquid medicine storage tank at the current time is recorded as FOi, The FOi=WTi(B), Among them, B represents the sudden change in the demand for adding liquid medicine corresponding to the amount of liquid medicine added to the i-th liquid medicine storage tank at the current time; WTi (B) represents the function value corresponding to WTi (x1) when x1 is B; The value of B is equal to the average value of the mutation value of the liquid addition requirement corresponding to each element in the reference array corresponding to Qi; The reference array corresponding to Qi is obtained by querying the historical database for all the liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and the corresponding liquid addition amount added in the i-th liquid storage tank at the current time is less than a preset value.

[0022] The addition delay risk analysis unit predicts the delay of adding each liquid medicine in combination with the operation data of the current production line, and evaluates the impact of the corresponding liquid medicine addition delay on the corresponding production line to obtain a second risk impact value; When the delay risk analysis unit is added to obtain the second risk impact value, The liquid medicine addition delay corresponding to the i-th liquid medicine storage tank is equal to the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time; The second risk impact value corresponding to the delay in adding the liquid medicine corresponding to the i-th liquid medicine storage tank is recorded as FTi, FTi = WQi (WYi (tsi)), Among them, tsi represents the delay of adding liquid medicine corresponding to the i-th liquid medicine storage tank; WYi(tsi) represents the function value corresponding to WYi(t) when t is tsi; WQi(WYi(tsi)) represents the function value corresponding to WQi(x) when x is WYi(tsi).

[0023] A liquid-adding behavior dynamic optimization module, wherein the liquid-adding behavior dynamic optimization module combines the first risk impact value and the second risk impact value to determine the optimization requirements of the liquid-adding behavior at the current time; and when there is an optimization requirement, generates different batch liquid-adding behavior planning schemes, and respectively calculates the intervention interference value of each batch liquid-adding behavior planning scheme on the production line during the execution process, and selects the batch liquid-adding behavior planning scheme with the smallest corresponding intervention interference value as the liquid-adding behavior dynamic optimization result; When the dynamic optimization module for liquid adding behavior determines the optimization demand for liquid adding behavior at the current time, when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both greater than or equal to the preset product abnormality rate, it is determined that there is an optimization demand for liquid adding behavior at the current time; when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both less than the preset product abnormality rate, it is determined that there is no optimization demand for liquid adding behavior at the current time. If the first risk impact value corresponding to the i-th drug liquid storage tank is less than or equal to the second risk impact value, it is determined that after the waiting time in the operation state of the production line to which the i-th drug liquid storage tank belongs at the current time, the liquid adding behavior operation is performed according to the drug liquid adding characteristic parameters corresponding to the current time; otherwise, the liquid adding behavior operation is immediately performed according to the drug liquid adding characteristic parameters corresponding to the current time; When the dynamic optimization module for liquid adding behavior generates different batch liquid adding behavior planning schemes, the corresponding amount of liquid added to the i-th liquid storage tank at the current time is evenly divided into n parts and two batches, the liquid adding time corresponding to the first batch is the current time, and the liquid adding time corresponding to the second batch is the waiting time in the running state of the production line to which the i-th liquid storage tank belongs at the current time; the number of liquid addition amounts corresponding to each liquid storage tank in the first batch and the second batch is adjusted respectively, and different liquid adding behavior planning schemes corresponding to the corresponding liquid storage tanks are generated, and the liquid adding behavior planning schemes corresponding to each liquid storage tank are combined to generate different batch liquid adding behavior planning schemes, and the sum of the number of liquid addition amounts corresponding to the first batch and the second batch corresponding to the corresponding liquid storage tank in each batch liquid adding behavior planning scheme is n, and n is a constant preset in the database; When the dynamic optimization module for liquid adding behavior respectively calculates the intervention interference value of each batch of liquid adding behavior planning scheme on the production line during the execution process, the intervention interference value of the j-th batch of liquid adding behavior planning scheme on the production line during the execution process is recorded as GRj. , Among them, ig represents the number of liquid medicine storage tanks; HOij represents the prediction result of the first risk impact value corresponding to the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme when the corresponding first batch liquid filling scheme is executed; HTij represents the prediction result of the second risk impact value corresponding to the liquid addition demand value after the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme executes the corresponding first batch liquid filling scheme; The liquid addition demand value corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding first batch liquid addition scheme is equal to the average value of the liquid addition demand values ​​corresponding to each element in the reference set corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding liquid addition behavior; The reference set corresponding to the ith liquid storage tank in the jth batch liquid addition behavior planning scheme is obtained by querying the historical database for all liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and Mij is less than a preset value, wherein Mij represents the corresponding liquid addition amount corresponding to the first batch liquid addition scheme corresponding to the ith liquid storage tank in the jth batch liquid addition behavior planning scheme.

[0024] A liquid adding behavior early warning module, which generates a liquid adding behavior early warning report based on the optimization demand determination result of the liquid adding behavior at the current time and the liquid adding behavior dynamic optimization result obtained by the liquid adding behavior dynamic optimization module, and feeds it back to the corresponding administrator for confirmation; When the liquid adding behavior warning module generates a liquid adding behavior warning report, if there is no optimization demand for liquid adding behavior in each liquid storage tank at the current time, a set consisting of the current time point, each liquid adding characteristic parameter at the current time and the corresponding execution time is used as the liquid adding behavior warning report corresponding to the current time; If there is a need to optimize the liquid filling behavior of the liquid storage tank at the current time, the set consisting of the current time point and the dynamic optimization results of the liquid filling behavior corresponding to the current time is used as the liquid filling behavior warning report corresponding to the current time; After the generated liquid adding behavior warning report is fed back to the corresponding administrator for confirmation, when the corresponding administrator receives and approves the corresponding liquid adding behavior warning report or the corresponding administrator does not receive the corresponding liquid adding behavior warning report within the preset time, the liquid adding operation on the corresponding medicine liquid storage tank is automatically executed according to the liquid adding behavior planning plan in the corresponding liquid adding behavior warning report; otherwise, the corresponding administrator is reminded to manually perform the liquid adding operation on the corresponding medicine liquid storage tank.

[0025] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0026] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. Automated electrochemical solution adding system, characterized in that: The system comprises: A liquid adding behavior determination module, which obtains the liquid data in each liquid storage tank at the current time in real time through a sensor, and compares the obtained liquid data with the standard parameters of the corresponding liquid storage tank, and calculates the liquid adding demand value of each liquid storage tank; An addition amount prediction module, wherein the addition amount prediction module generates a characteristic parameter of the drug liquid addition corresponding to the current time according to the obtained drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank; A liquid addition behavior impact analysis module, wherein the liquid addition behavior impact analysis module obtains the amount of liquid added corresponding to each liquid storage tank in the liquid addition characteristic parameters and the operating status of the production line to which the corresponding liquid storage tank belongs at the current time, and combines the impact of different liquid addition behaviors on the production line operating status in historical data to predict the impact of the corresponding liquid addition amount added to the corresponding liquid storage tank at the current time on the corresponding production line to obtain a first risk impact value; combines the operating data of the current production line to predict the delay of each liquid addition, and evaluates the impact of the corresponding liquid addition delay on the corresponding production line to obtain a second risk impact value; A liquid-adding behavior dynamic optimization module, wherein the liquid-adding behavior dynamic optimization module combines the first risk impact value and the second risk impact value to determine the optimization requirements of the liquid-adding behavior at the current time; and when there is an optimization requirement, generates different batch liquid-adding behavior planning schemes, and respectively calculates the intervention interference value of each batch liquid-adding behavior planning scheme on the production line during the execution process, and selects the batch liquid-adding behavior planning scheme with the smallest corresponding intervention interference value as the liquid-adding behavior dynamic optimization result; The liquid adding behavior warning module generates a liquid adding behavior warning report based on the optimization demand judgment result of the liquid adding behavior at the current time and the liquid adding behavior dynamic optimization result obtained by the liquid adding behavior dynamic optimization module, and feeds it back to the corresponding administrator for confirmation.

2. The automated electrochemical solution adding system according to claim 1, characterized in that: The drug liquid data includes the composition of the drug liquid, the concentration of each component and the total amount of the drug liquid; When calculating the liquid addition requirement value of each liquid storage tank in the liquid addition behavior determination module, the liquid addition requirement value of the i-th liquid storage tank is recorded as Qi, ， Among them, β is the demand conversion factor and β is a constant preset in the database; Cik represents the absolute value of the difference between the concentration of the kth component in the liquid data of the i-th liquid storage tank at the current time and the midpoint of the concentration interval corresponding to the corresponding component in the standard parameters of the corresponding liquid storage tank; ki represents the number of component types in the liquid data of the i-th liquid storage tank at the current time; Lik represents the interval length of the concentration interval corresponding to the kth component in the liquid data of the i-th liquid storage tank in the corresponding standard parameter; Zi represents the inverse of the difference between the total amount of liquid medicine in the liquid medicine data of the i-th liquid medicine storage tank at the current time and the minimum value of the total amount of liquid medicine in the corresponding standard parameter; P{,} represents a demand judgment function. When the value of the first parameter in the function is greater than or equal to the value of the second parameter, the corresponding function result is judged to be the value of the first parameter in the function; otherwise, the corresponding function result is judged to be 0.

3. The automated electrochemical solution adding system according to claim 1, characterized in that: The characteristic parameters of the liquid medicine addition corresponding to the current time include the composition of the liquid medicine added corresponding to each liquid medicine storage tank, the concentration of each component and the amount of liquid medicine added; When the addition amount prediction module generates the characteristic parameters of the drug liquid addition corresponding to the current time, the drug liquid addition demand value of each drug liquid storage tank and the current state of each drug liquid storage tank are obtained; Arrange the order of adding medicines corresponding to each medicine storage tank in the medicine addition characteristic parameter corresponding to the current time according to the corresponding medicine addition demand value from large to small, and the medicine addition amount corresponding to the i-th medicine storage tank is the inverse number of the difference between the total amount of medicine in the medicine data of the i-th medicine storage tank at the current time and the minimum value of the total amount of medicine in the corresponding standard parameter; The concentrations corresponding to the various components in the characteristic parameters of the liquid medicine addition corresponding to the current time are obtained by querying the values ​​corresponding to the corresponding data groups in the preset forms in the database. The data groups corresponding to the corresponding components include the concentrations of the corresponding components before adding the medicine, the concentration ranges corresponding to the corresponding components in the corresponding standard parameters, and the amount of liquid medicine added.

4. The automated electrochemical solution adding system according to claim 2, characterized in that: The liquid addition behavior impact analysis module includes an addition amount risk analysis unit and an addition delay risk analysis unit. The addition amount risk analysis unit obtains the amount of medicine added corresponding to each medicine storage tank in the medicine addition characteristic parameter and the operating status of the production line to which the corresponding medicine storage tank belongs at the current time, and combines the impact of different medicine addition behaviors on the production line operating status in the historical data to predict the impact of the corresponding medicine addition amount added to the corresponding medicine storage tank at the current time on the corresponding production line to obtain a first risk impact value; The addition delay risk analysis unit predicts the delay of adding each drug solution in combination with the operation data of the current production line, and evaluates the impact of the corresponding drug solution addition delay on the corresponding production line to obtain a second risk impact value.

5. The automated electrochemical solution adding system according to claim 4, characterized in that: When the additive amount risk analysis unit obtains the first risk impact value, Obtain the amount of liquid medicine added corresponding to each liquid medicine storage tank in the liquid medicine addition characteristic parameters and the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time, wherein the operating status of the production line to which the corresponding liquid medicine storage tank belongs at the current time includes the type of production product corresponding to the production line to which the corresponding liquid medicine storage tank belongs at the current time, the waiting time, the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid medicine addition demand value, the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change amount of the liquid medicine addition demand value, and the change function of the liquid medicine addition demand value corresponding to the corresponding product type with the running time; When the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time is equal to the corresponding product type produced by the corresponding production line in the historical data, the quotient of the remaining product quantity to be produced at the current time and the average production speed of the corresponding product type in the historical data; When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, obtain each demand-related data pair corresponding to the i-th liquid storage tank in the historical data, wherein the first value of the demand-related data pair is the liquid addition demand value of the liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; according to the preset function model y=-x -a +b fits each demand-related data pair obtained, and calculates the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each associated data pair, and obtains the data fitting deviation corresponding to each fitting result. The fitting function corresponding to the minimum value of the obtained data fitting deviation is used as the relationship function between the product abnormality rate corresponding to the corresponding product type and the liquid addition demand value of the i-th liquid storage tank, which is recorded as WQi (x); When obtaining the relationship function between the product abnormality rate corresponding to the corresponding product type and the sudden change in the demand value of the medicine liquid addition of the ith medicine liquid storage tank, obtain each demand mutation associated data pair corresponding to the ith medicine liquid storage tank in the historical data, wherein the first value of the demand mutation associated data pair is the sudden change in the demand for medicine liquid addition of the medicine liquid storage tank, and the second value is the product abnormality rate corresponding to the corresponding product type; the sudden change in the demand for medicine liquid addition is equal to the maximum difference between the corresponding values ​​of the demand for medicine liquid addition at different time points per unit time after the medicine adding operation is performed; according to the preset function model y1=-x1 -a +b fits each demand mutation associated data pair obtained, and calculates the sum of the shortest distances between the function curves corresponding to each fitting result and the corresponding coordinates of each demand mutation associated data pair, and obtains the data fitting deviation corresponding to each fitting result. The fitting function corresponding to the minimum value of the obtained data fitting deviation is used as the relationship function between the product abnormality rate corresponding to the corresponding product type and the mutation amount of the liquid addition demand value of the i-th liquid storage tank, recorded as WTi (x1); When obtaining the function of the change of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, obtain each operation demand associated data pair corresponding to the i-th liquid medicine storage tank in the historical data, the first value of the operation demand associated data pair is the subsequent operation time based on the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type, and the second value is the liquid addition demand value of the liquid medicine storage tank; fit each obtained operation demand associated data pair according to the preset linear regression model, and use the obtained fitting function as the change function of the liquid addition demand value of the i-th liquid medicine storage tank corresponding to the corresponding product type with the operation time, recorded as WYi(t); The first risk impact value corresponding to the addition of the corresponding amount of liquid medicine to the i-th liquid medicine storage tank at the current time is recorded as FOi, The FOi=WTi(B), Among them, B represents the sudden change in the demand for adding liquid medicine corresponding to the amount of liquid medicine added to the i-th liquid medicine storage tank at the current time; WTi (B) represents the function value corresponding to WTi (x1) when x1 is B; The value of B is equal to the average value of the mutation value of the liquid addition requirement corresponding to each element in the reference array corresponding to Qi; The reference array corresponding to Qi is obtained by querying the historical database for all the liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and the corresponding liquid addition amount added in the i-th liquid storage tank at the current time is less than a preset value.

6. The automated electrochemical solution adding system according to claim 5, characterized in that: When the delay risk analysis unit is added to obtain the second risk impact value, The liquid medicine addition delay corresponding to the i-th liquid medicine storage tank is equal to the waiting time in the operation state of the production line to which the corresponding liquid medicine storage tank belongs at the current time; The second risk impact value corresponding to the delay in adding the liquid medicine corresponding to the i-th liquid medicine storage tank is recorded as FTi, FTi = WQi (WYi (tsi)), Among them, tsi represents the delay of adding liquid medicine corresponding to the i-th liquid medicine storage tank; WYi(tsi) represents the function value corresponding to WYi(t) when t is tsi; WQi(WYi(tsi)) represents the function value corresponding to WQi(x) when x is WYi(tsi).

7. The automated electrochemical solution adding system according to claim 6, characterized in that: When the dynamic optimization module for liquid adding behavior determines the optimization demand for liquid adding behavior at the current time, when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both greater than or equal to the preset product abnormality rate, it is determined that there is an optimization demand for liquid adding behavior at the current time; when the first risk impact value and the second risk impact value corresponding to the i-th liquid medicine storage tank are both less than the preset product abnormality rate, it is determined that there is no optimization demand for liquid adding behavior at the current time. If the first risk impact value corresponding to the i-th drug liquid storage tank is less than or equal to the second risk impact value, it is determined that after the waiting time in the operation state of the production line to which the i-th drug liquid storage tank belongs at the current time, the liquid adding behavior operation is performed according to the drug liquid adding characteristic parameters corresponding to the current time; otherwise, the liquid adding behavior operation is immediately performed according to the drug liquid adding characteristic parameters corresponding to the current time; When the liquid adding behavior dynamic optimization module generates different batch liquid adding behavior planning schemes, the corresponding liquid addition amount added to the i-th liquid storage tank at the current time is divided into n parts and two batches. The liquid addition time corresponding to the first batch is the current time, and the liquid addition time corresponding to the second batch is the waiting time in the operation state of the production line to which the i-th liquid storage tank belongs at the current time; The number of portions of the added liquid corresponding to each liquid storage tank in the first batch and the second batch is adjusted respectively, and different liquid adding behavior planning schemes corresponding to the corresponding liquid storage tanks are generated, and the liquid adding behavior planning schemes corresponding to the various liquid storage tanks are combined to generate different batch liquid adding behavior planning schemes, and the sum of the number of portions of the added liquid corresponding to the first batch and the second batch respectively corresponding to the corresponding liquid storage tanks in each batch liquid adding behavior planning scheme is n, and n is a constant preset in the database; When the dynamic optimization module for liquid adding behavior respectively calculates the intervention interference value of each batch of liquid adding behavior planning scheme on the production line during the execution process, the intervention interference value of the j-th batch of liquid adding behavior planning scheme on the production line during the execution process is recorded as GRj. ， Among them, ig represents the number of liquid medicine storage tanks; HOij represents the prediction result of the first risk impact value corresponding to the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme when the corresponding first batch liquid filling scheme is executed; HTij represents the prediction result of the second risk impact value corresponding to the liquid addition demand value after the i-th liquid medicine storage tank in the j-th batch liquid filling behavior planning scheme executes the corresponding first batch liquid filling scheme; The liquid addition demand value corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding first batch liquid addition scheme is equal to the average value of the liquid addition demand values ​​corresponding to each element in the reference set corresponding to the i-th liquid storage tank in the j-th batch liquid addition behavior planning scheme after executing the corresponding liquid addition behavior; The reference set corresponding to the ith liquid storage tank in the jth batch liquid addition behavior planning scheme is obtained by querying the historical database for all liquid addition behaviors whose corresponding liquid addition demand value is the same as Qi and whose deviation between the liquid addition amount and Mij is less than a preset value, wherein Mij represents the corresponding liquid addition amount corresponding to the first batch liquid addition scheme corresponding to the ith liquid storage tank in the jth batch liquid addition behavior planning scheme.

8. The automated electrochemical solution adding system according to claim 1, characterized in that: When the liquid adding behavior warning module generates a liquid adding behavior warning report, if there is no optimization demand for liquid adding behavior in each liquid storage tank at the current time, a set consisting of the current time point, each liquid adding characteristic parameter at the current time and the corresponding execution time is used as the liquid adding behavior warning report corresponding to the current time; If there is a need to optimize the liquid filling behavior of the liquid storage tank at the current time, the set consisting of the current time point and the dynamic optimization results of the liquid filling behavior corresponding to the current time is used as the liquid filling behavior warning report corresponding to the current time; After the generated liquid adding behavior warning report is fed back to the corresponding administrator for confirmation, when the corresponding administrator receives and approves the corresponding liquid adding behavior warning report or the corresponding administrator does not receive the corresponding liquid adding behavior warning report within the preset time, the liquid adding operation on the corresponding medicine liquid storage tank is automatically executed according to the liquid adding behavior planning plan in the corresponding liquid adding behavior warning report; otherwise, the corresponding administrator is reminded to manually perform the liquid adding operation on the corresponding medicine liquid storage tank.

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