Production device of blood-activating and swelling-reducing external ointment and control system thereof

Abstract

The present application relates to the technical field of health product production, and particularly relates to a production device and control system of blood-activating and swelling-eliminating external application ointment, the device comprises a medicinal material cleaning machine, a conveying pipe, a vacuum dryer, a universal pulverizer, a first sealing element, a second sealing element, a mixing and stirring tank, a cooling tank, a blood-activating and swelling-eliminating external application ointment production control system and a filling machine, the system comprises a production data acquisition module, a production quality evaluation module, a data source monitoring module, a production process monitoring module, a production parameter control module and a decision execution module, a production adjustment decision is generated, and the device is controlled according to the production adjustment decision, so that the process parameters are adjusted in real time to reach the best state, and the production quality is improved.

Description

Technical Field

[0001] This invention relates to the field of health product manufacturing technology, and in particular to a production apparatus and control system for a topical ointment for promoting blood circulation and reducing swelling. Background Technology

[0002] In the production of traditional topical ointments for promoting blood circulation and reducing swelling, each process typically relies on independent equipment and is carried out in segments, such as the separate processes of cleaning, drying, pulverizing, mixing, and filling of medicinal materials. This model has obvious defects and shortcomings: First, the reliance on manual transfer between processes is prone to introducing contamination and is inefficient; second, as a critical process, the determination of the endpoint of mixing often depends on fixed time or operator experience, making it impossible to assess the uniformity of the ointment's composition and physical texture in real time and quantitatively, resulting in large quality fluctuations between batches and difficulty in ensuring uniformity; third, the production process lacks closed-loop monitoring of equipment health and process stability, making it difficult to quickly diagnose and adaptively adjust when sensors malfunction or the process deviates, affecting production stability and product qualification rate.

[0003] Chinese patent CN112316079B discloses a production equipment for spleen-nourishing traditional Chinese medicine. This equipment includes, sequentially arranged along a production line, a raw material weighing device, a raw material washing device, a raw material chopping device, a raw material drying device, a raw material processing device, a raw material sterilization device, a raw material pulverizing and sieving device, a raw material mixing device, and a mixed material packaging device. Therefore, this solution still suffers from problems such as unstable production quality and low product consistency due to the lack of real-time monitoring of equipment status and process stability. Summary of the Invention

[0004] Therefore, the present invention provides a production device and control system for a topical ointment for promoting blood circulation and reducing swelling, in order to overcome the problems of unstable production quality and low product consistency caused by the lack of real-time monitoring of equipment status and process stability in the production process in the prior art.

[0005] To achieve the above objectives, in one aspect, the present invention provides a production apparatus for a topical ointment that promotes blood circulation and reduces swelling, the apparatus comprising:

[0006] The herbal medicine washing machine is connected to a vacuum dryer through a first conveying pipe and is used to wash the raw materials for ointments to obtain cleaned herbal medicines.

[0007] The conveying pipe includes a first conveying pipe, a second conveying pipe, a third conveying pipe, a fourth conveying pipe, and a fifth conveying pipe. The first conveying pipe connects the herbal medicine washing machine and the vacuum dryer, and conveys the washed herbal medicine from the herbal medicine washing machine to the vacuum dryer. The second conveying pipe connects the vacuum dryer and the universal pulverizer, and conveys the dried herbal medicine from the vacuum dryer to the universal pulverizer. The third conveying pipe connects the universal pulverizer and the mixing tank, and conveys the pulverized herbal medicine from the universal pulverizer to the mixing tank. The fourth conveying pipe connects the mixing tank and the cooling tank, and conveys the mixed herbal medicine from the mixing tank to the cooling tank. The fifth conveying pipe connects the cooling tank and the filling machine, and conveys the blood-activating and swelling-reducing external ointment from the cooling tank to the filling machine.

[0008] A vacuum dryer is connected to a first and a second sealing element, and is connected to a medicinal material washing machine through a first conveying pipe and to a universal pulverizer through a second conveying pipe. It is used to perform vacuum drying on the washed medicinal materials to obtain dried medicinal materials.

[0009] A sealing element, comprising a first sealing element and a second sealing element, for sealing a vacuum dryer;

[0010] The universal pulverizer is connected to the vacuum dryer through the second conveying pipe and to the mixing tank through the third conveying pipe. It is used to pulverize the dried medicinal materials according to production adjustment decisions to obtain pulverized medicinal materials.

[0011] The mixing tank is connected to the universal pulverizer via a third conveying pipe and to the cooling tank via a fourth conveying pipe. It is also connected to the production control system of the blood-activating and swelling-reducing external ointment via an internal connection line. It is used to mix the pulverized medicinal materials according to production adjustment decisions to obtain the mixed medicinal materials.

[0012] The cooling tank, which is connected to the mixing tank via the fourth conveying pipe and to the filling machine via the fifth conveying pipe, is used to cool the mixed medicinal materials to obtain a blood-activating and swelling-reducing external ointment.

[0013] The production control system for the blood-activating and swelling-reducing external ointment is connected to the mixing tank via an internal connection line. It acquires production quality data, acquires production quality index, performs cause analysis, outputs production adjustment decisions, monitors data sources and performs data compensation processing, adjusts production adjustment decisions, updates the production quality index during the acquisition process, updates the data compensation processing process, updates the decision adjustment process, and optimizes the production adjustment decisions.

[0014] The filling machine, which is connected to the cooling tank via the fifth conveying pipe, is used to fill the external ointment for promoting blood circulation and reducing swelling.

[0015] Further, the mixing tank includes:

[0016] A stirring paddle, placed inside a mixing tank, is used to stir the pulverized medicinal materials according to production adjustment decisions;

[0017] A heating jacket, located outside the mixing tank, is used to heat the mixing tank according to production adjustment decisions;

[0018] A sensor cluster, placed on the inner wall of the mixing tank, is used to collect production quality data. The sensor cluster includes an online near-infrared spectrometer, an online viscometer, an online laser particle size analyzer, a power transmitter, a temperature sensor, and a vibration acceleration sensor. The production quality data includes multi-point component concentration values, paste viscosity, key particle size values, stirring power, real-time temperature, and mechanical vibration intensity. The online viscometer is used to collect paste viscosity, the online laser particle size analyzer is used to collect key particle size values, the online near-infrared spectrometer is used to collect multi-point component concentration values, the power transmitter is used to collect stirring power, the temperature sensor is used to collect real-time temperature, and the vibration acceleration sensor is used to collect mechanical vibration intensity.

[0019] On the other hand, the present invention also provides a production control system for a topical ointment for promoting blood circulation and reducing swelling, the system comprising:

[0020] The production data acquisition module is used to acquire production quality data;

[0021] The production quality assessment module is used to obtain the production quality index based on production quality data, perform cause analysis based on the production quality index, obtain the cause analysis results, and output production adjustment decisions based on the cause analysis results.

[0022] The data source monitoring module is used to monitor the data source based on production quality data, obtain the first backtracking data difference and the second backtracking data difference, and perform data compensation processing on the acquisition process of the production quality index based on the first backtracking data difference and the second backtracking data difference to obtain the secondary production quality index. The module then makes production adjustment decisions based on the secondary production quality index.

[0023] The production process monitoring module is used to acquire process stability, update the production quality index based on process stability, update the data compensation process based on process stability, perform contradiction inference on the process stability acquisition, obtain contradiction inference results, and update production adjustment decisions based on contradiction inference results.

[0024] The production parameter control module is used to perform parameter boundary control on production quality data, obtain boundary control results, and optimize production adjustment decisions based on the boundary control results.

[0025] The decision execution module is used to control the equipment based on production adjustment decisions.

[0026] Furthermore, the production quality assessment module obtains the production quality index based on the production quality data. Specifically, it obtains the uniformity R based on the multi-point component concentration values ​​in the production quality data, and obtains the physical texture B based on the paste viscosity and key particle size values ​​in the production quality data. The production quality index S is calculated based on the uniformity R, physical texture B, uniformity weight w1, and physical texture weight w2. The formula is set as S = R × w1 + B × w2 to obtain the production quality index S, where w1 + w2 = 1.

[0027] The production quality assessment module compares the production quality index S with the preset production quality index S0, judges the degree of compliance of the production quality index based on the comparison results, and performs cause analysis based on the judgment results, wherein:

[0028] When S≥S0, the production quality assessment module determines that the production quality index meets the standard and does not perform cause analysis.

[0029] When S < S0, the production quality assessment module determines that the production quality index does not meet the standard, performs cause analysis, and obtains the cause analysis results.

[0030] The production quality assessment module outputs production adjustment decisions based on the root cause analysis results. Specifically, it compares the root cause analysis results with preset root cause analysis results in the process adjustment strategy library, and outputs production adjustment decisions based on the comparison results.

[0031] When the root cause analysis results are consistent with the preset root cause analysis results, the production adjustment decision corresponding to the preset root cause analysis results will be output.

[0032] When the root cause analysis results are inconsistent with the preset root cause analysis results, the root cause analysis results are pushed out, and production adjustment decisions are obtained through manual settings and stored in the process adjustment strategy library.

[0033] Furthermore, the data source monitoring module monitors the data source based on the production quality data, specifically by: acquiring the backtracking uniformity Rh, calculating the first backtracking data difference Hv1 based on the backtracking uniformity Rh and the uniformity R, and setting Hv1=Rh-R;

[0034] The retrospective physical texture Bh is obtained, and the second retrospective data difference Hv2 is calculated based on the retrospective physical texture Bh and the physical texture B, and Hv2 is set as Bh-B;

[0035] The first backtracking data difference Hv1 and the second backtracking data difference Hv2 are compared with preset first backtracking data difference Hv10 and preset second backtracking data difference Hv20, respectively. Based on the comparison results, the status of the first and second backtracking data differences is determined, and data compensation processing is performed on the production quality index acquisition process according to the determination results. Specifically:

[0036] When Hv1≤Hv10 and Hv2≤Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is normal, and does not perform data compensation processing in the process of obtaining the production quality index.

[0037] When Hv1 > Hv10 and Hv2 ≤ Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the acquisition process of the production quality index: input the multi-point component concentration values ​​into the virtual uniformity sensor to obtain the virtual uniformity R' output by the virtual sensor, and calculate the production quality index S according to the virtual uniformity R', physical texture B, uniformity weight w1 and physical texture weight w2, and set S = R' × w1 + B × w2 to obtain the secondary production quality index S2;

[0038] When Hv1≤Hv10 and Hv2>Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the process of obtaining the production quality index: the paste viscosity and key particle size value are input into the virtual texture sensor to obtain the virtual physical texture B' output by the virtual sensor, and the production quality index S is calculated according to the uniformity R, the virtual physical texture B', the uniformity weight w1 and the physical texture weight w2. S=R×w1+B'×w2 is set to obtain the secondary production quality index S2.

[0039] When Hv1 > Hv10 and Hv2 > Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the acquisition process of the production quality index: the multi-point component concentration value, paste viscosity and key particle size value are input into the virtual uniformity sensor and the virtual texture sensor respectively, to obtain the virtual uniformity R' output by the virtual uniformity sensor and the virtual physical texture B' output by the virtual texture sensor, and calculate the production quality index S according to the virtual uniformity R', virtual physical texture B', uniformity weight w1 and physical texture weight w2, and set S = R' × w1 + B' × w2 to obtain the secondary production quality index S2.

[0040] Furthermore, the data source monitoring module compares the secondary production quality index S2 with the preset production quality index S0, judges the status of the data source based on the comparison result, and makes production adjustment decisions based on the judgment result, wherein:

[0041] When S2≥S0, the data source monitoring module determines that the data source situation is acceptable and does not make any decision adjustments to the production adjustment decision.

[0042] When S2 < S0, the data source monitoring module determines that the data source situation is unacceptable and makes a production adjustment decision: it will activate physical isolation protection and issue an alarm as the output of the production adjustment decision.

[0043] Furthermore, the production process monitoring module acquires the process stability pm, compares the process stability pm with a preset process stability pm0, judges the degree of compliance of the process stability based on the comparison result, and updates the production quality index acquisition process and the data compensation process based on the judgment result, wherein:

[0044] When pm≥pm0, the production process monitoring module determines that the process stability meets the standard, and does not update the production quality index during the acquisition process or compensate for the data compensation process.

[0045] When pm < pm0, the production process monitoring module determines that the compliance level of the process stability is not up to standard, and performs index update on the process of obtaining the production quality index: the physical texture weight w2 is updated according to the update coefficient gf to obtain the updated physical texture weight w2', w2' = w2 × gf is set, and w1 = 1 - w2' is used as the physical texture weight w2, and the production quality index S is recalculated according to the uniformity R, physical texture B, uniformity weight w1 and physical texture weight w2;

[0046] The data compensation process involves updating the data: adding high-confidence baseline batch data packets to the training sets of the virtual uniformity sensor and the virtual texture sensor, and reconstructing the virtual uniformity sensor and the virtual texture sensor to obtain the updated virtual uniformity sensor and the updated virtual texture sensor. Then, the data compensation process is performed again based on the updated virtual uniformity sensor and the updated virtual texture sensor.

[0047] Furthermore, the production process monitoring module performs contradiction inference on the process stability acquisition process to obtain contradiction inference results, which include whether a contradiction exists or not. Based on these contradiction inference results, the decision adjustment process is updated, wherein:

[0048] When the contradiction inference result is that there is no contradiction, the decision adjustment process is not updated.

[0049] When the contradiction inference result indicates the existence of a contradiction, the decision adjustment process is updated: the physical isolation protection and alarm activation in the decision adjustment are replaced with sensing and detection by temperature sensors and vibration acceleration sensors.

[0050] Furthermore, the production parameter control module performs parameter boundary control on the production quality number through a multi-objective optimization algorithm to obtain boundary control results, and optimizes the production adjustment decision based on the boundary control results: the boundary control results are added to the production adjustment decision.

[0051] Furthermore, the decision execution module controls the equipment based on production adjustment decisions.

[0052] Compared with existing technologies, the beneficial effects of this invention are as follows: the device, through the series connection of a medicinal herb washing machine, a vacuum dryer, and a universal pulverizer, achieves a fully enclosed continuous pretreatment process from raw material washing and low-temperature high-efficiency drying to fine pulverization, effectively preserving the active ingredients in the blood-activating and swelling-reducing external ointment and ensuring product quality from the source. The device also integrates a mixing tank with a stirring paddle, a heating jacket, and a sensor cluster, forming the core of intelligent mixing and real-time quality perception. The synergy between the stirring paddle and the heating jacket enables precise and proactive control of the mixing intensity and temperature environment to meet the process requirements of producing the blood-activating and swelling-reducing external ointment. The device also collects production quality indices through the sensor cluster and outputs production adjustment decisions based on the production quality data through the production control system of the blood-activating and swelling-reducing external ointment, thereby ensuring that the produced blood-activating and swelling-reducing external ointment has excellent uniformity and stability in both chemical composition and physical texture.

[0053] In particular, the system acquires production quality data through a production data acquisition module to facilitate multi-dimensional monitoring of production quality. The system also acquires a production quality index through a production quality assessment module, measuring the quality status of the blood-activating and swelling-reducing external ointment in a specific numerical form. When the production quality index fails to meet standards, the system promptly analyzes the causes to adaptively improve production quality. Furthermore, the system monitors the status of the sensor cluster through a data source monitoring module to avoid the impact of data source fluctuations on production quality, thereby improving the accuracy of production quality monitoring and the consistency of the final product. It also further determines the reliability of the data source to prevent continued operation from significantly reducing production quality. The system also... The system uses a production process monitoring module to assess the degree of process stability, thereby monitoring the stability of the equipment process and reducing production quality instability caused by process instability. It also updates production adjustment decisions based on contradiction inference results to address potential sensor malfunctions, thus improving production quality and efficiency. Furthermore, the system uses a production parameter control module to acquire boundary control results, enabling equipment control based on production adjustment decisions to improve production efficiency without exceeding the actual physical limits of the equipment. Finally, the system uses a decision execution module to control the equipment based on production adjustment decisions, adjusting process parameters in real time to achieve optimal performance, thereby improving production quality. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of the production apparatus for the blood-activating and swelling-reducing external ointment in this embodiment;

[0055] Figure 2 This is a schematic diagram of the mixing tank in this embodiment;

[0056] Figure 3 This is a schematic diagram of the production control system for the blood-activating and swelling-reducing external ointment in this embodiment;

[0057] In the diagram: 1. Herb washing machine; 2. Conveying pipe; 3. First conveying pipe 201; 4. Second conveying pipe 202; 5. Third conveying pipe 203; 6. Fourth conveying pipe 204; 7. Fifth conveying pipe 205; 8. Vacuum dryer; 9. Sealing component; 10. First sealing component 401; 11. Second sealing component 402; 12. Universal pulverizer; 13. Mixing tank; 14. Cooling tank; 15. Production control system for blood-activating and swelling-reducing external ointment; 16. Filling machine. Detailed Implementation

[0058] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0059] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0060] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0061] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0062] Please see Figure 1 The diagram shown is a structural schematic of the production apparatus for the blood-activating and swelling-reducing external ointment of this embodiment. The apparatus includes:

[0063] The herbal medicine washing machine 1 is connected to the vacuum dryer 3 through the first conveying pipe 201 and is used to wash the raw materials of the ointment to obtain the washed herbal medicine.

[0064] The conveying pipe 2 includes a first conveying pipe 201, a second conveying pipe 202, a third conveying pipe 203, a fourth conveying pipe 204, and a fifth conveying pipe 205. The first conveying pipe 201 connects the herbal medicine washing machine 1 and the vacuum dryer 3, and conveys the washed herbal medicine from the herbal medicine washing machine 1 to the vacuum dryer 3. The second conveying pipe 202 connects the vacuum dryer 3 and the universal pulverizer 5, and conveys the dried herbal medicine from the vacuum dryer 3 to the universal pulverizer 5. The third conveying pipe 203 connects the universal pulverizer 5 and the mixing tank 6, and conveys the pulverized herbal medicine from the universal pulverizer 5 to the mixing tank 6. The fourth conveying pipe 204 connects the mixing tank 6 and the cooling tank 7, and conveys the mixed herbal medicine from the mixing tank 6 to the cooling tank 7. The fifth conveying pipe 205 connects the cooling tank 7 and the filling machine 9, and conveys the blood-activating and swelling-reducing external ointment from the cooling tank 7 to the filling machine 9.

[0065] Vacuum dryer 3 is connected to the first seal 401 and the second seal 402, and is connected to the herbal washing machine 1 through the first conveying pipe 201 and to the universal pulverizer 5 through the second conveying pipe 202. It is used to perform vacuum drying on the washed herbal materials to obtain dried herbal materials.

[0066] The sealing element 4, which includes a first sealing element 401 and a second sealing element 402, is used to seal the vacuum dryer 3;

[0067] The universal pulverizer 5 is connected to the vacuum dryer 3 through the second conveying pipe 202 and to the mixing tank 6 through the third conveying pipe 203. It is used to pulverize the dried medicinal materials according to production adjustment decisions to obtain pulverized medicinal materials.

[0068] The mixing tank 6 is connected to the universal pulverizer 5 through the third conveying pipe 203 and to the cooling tank 7 through the fourth conveying pipe 204. It is also connected to the production control system 8 of the blood-activating and swelling-reducing external ointment through an internal connection line (not shown in the figure). It is used to stir the pulverized medicinal materials according to the production adjustment decision to obtain the stirred medicinal materials.

[0069] Cooling tank 7 is connected to mixing tank 6 via fourth conveying pipe 204 and to filling machine 9 via fifth conveying pipe 205. It is used to cool the stirred medicinal materials to obtain a blood-activating and swelling-reducing external ointment.

[0070] The production control system 8 for the blood-activating and swelling-reducing external ointment is connected to the mixing tank 6 via an internal connection line (not shown in the figure) and is used to output production adjustment decisions.

[0071] The filling machine 9 is connected to the cooling tank 7 via the fifth conveying pipe 205 and is used to fill the external ointment for promoting blood circulation and reducing swelling.

[0072] Specifically, the production process of the blood-activating and swelling-reducing external ointment is as follows: Raw materials for the ointment are placed in a medicinal herb cleaning machine for cleaning, resulting in cleaned medicinal materials. These cleaned medicinal materials are then pumped into a vacuum dryer via a conveying pipe. The first and second seals are closed, and the cleaned medicinal materials are vacuum-dried to obtain dried medicinal materials. The dried medicinal materials are then pumped into a universal pulverizer via a conveying pipe for pulverizing, resulting in pulverized medicinal materials. The pulverized medicinal materials are then pumped into a mixing tank via a conveying pipe for mixing, resulting in stirred medicinal materials. The stirred medicinal materials are then pumped into a cooling tank via a conveying pipe for cooling, resulting in the blood-activating and swelling-reducing external ointment. The blood-activating and swelling-reducing external ointment is then pumped into a filling machine via a conveying pipe for filling. The internal connection line refers to the power line that transmits signals and data, such as a motor control signal line.

[0073] Please see Figure 2 As shown, this is a schematic diagram of the structure of the mixing tank in this embodiment. The mixing tank includes:

[0074] A stirring paddle 601 is placed inside a mixing tank 6 and is used to stir the pulverized medicinal materials according to production adjustment decisions.

[0075] Heating jacket 602, which is located outside the mixing tank 6, is used to heat the mixing tank 6 according to production adjustment decisions;

[0076] A sensor cluster 603, placed on the inner wall of the mixing tank 6, is used to collect production quality data. The sensor cluster includes an online near-infrared spectrometer 631, an online viscometer 632, an online laser particle size analyzer 633, a power transmitter 634, a temperature sensor 635, and a vibration acceleration sensor 636. The production quality data includes multi-point component concentration values, paste viscosity, key particle size values, stirring power, real-time temperature, and mechanical vibration intensity. The online viscometer 632 is used to collect paste viscosity; the online laser particle size analyzer 633 is used to collect key particle size values; the online near-infrared spectrometer 631 is used to collect multi-point component concentration values; the power transmitter 634 is used to collect stirring power; the temperature sensor 635 is used to collect real-time temperature; and the vibration acceleration sensor 636 is used to collect mechanical vibration intensity.

[0077] Specifically, the multi-point component concentration values ​​dp={dp1,dp2,..., } refers to the content of the same target component in m samples of medicinal materials after stirring, collected synchronously and continuously from different spatial locations within the mixing tank, such as ferulic acid in Ligusticum chuanxiong. Here, m is the number of samples. This embodiment does not limit the different spatial locations within the mixing tank; those skilled in the art can freely choose according to actual needs. For example, the upper, middle, and lower layers, and the areas near the tank wall and stirring shaft of each layer can be used as different spatial locations for sampling. Here, dp1 refers to the target component content at the first spatial location among the multi-point component concentration values, dp2 refers to the target component content at the second spatial location among the multi-point component concentration values, and so on. This refers to the first of the multi-point component concentration values. The target component content at each spatial location The order is based on the content of the target components, and The values ​​are positive integers. The viscosity of the paste refers to the value that measures the flow resistance of the medicinal materials after stirring. The critical particle size value refers to the particle size value that 90% of the particles in the medicinal materials are smaller than after stirring. The stirring power refers to the active power consumed by the motor that drives the stirring paddle of the mixing tank at the current instant. The real-time temperature refers to the instantaneous temperature value of the medicinal materials after stirring in the mixing tank. The mechanical vibration intensity refers to the vibration amplitude generated by the mixing tank during operation.

[0078] Specifically, the production device for the blood-activating and swelling-reducing external ointment is applied in the production process of the ointment. The device, through the series connection of a herbal washing machine, a vacuum dryer, and a universal pulverizer, achieves a fully enclosed continuous pretreatment process from raw material washing and low-temperature, high-efficiency drying to fine pulverization. This effectively preserves the active ingredients in the ointment, ensuring product quality from the source. The device also integrates a mixing tank with a stirring paddle, a heating jacket, and a sensor cluster, forming the core of intelligent mixing and real-time quality sensing. The synergy between the stirring paddle and the heating jacket enables precise and proactive control of the mixing intensity and temperature environment to meet the process requirements of the ointment production. Furthermore, the device collects production quality indices through the sensor cluster and outputs production adjustment decisions based on the production quality data through the ointment's production control system, thereby ensuring that the produced ointment exhibits excellent uniformity and stability in both chemical composition and physical texture.

[0079] Please see Figure 3 The diagram shown is a structural schematic of the production control system for the blood-activating and swelling-reducing external ointment of this embodiment. The system includes:

[0080] The production data acquisition module is used to acquire production quality data;

[0081] The production quality assessment module is used to acquire the production quality index based on the production quality data, perform cause analysis based on the production quality index, obtain the cause analysis results, and output production adjustment decisions based on the cause analysis results. The production quality assessment module is connected to the production data acquisition module.

[0082] The data source monitoring module is used to monitor the data source based on production quality data, obtain the first backtracking data difference and the second backtracking data difference, and perform data compensation processing on the acquisition process of the production quality index based on the first backtracking data difference and the second backtracking data difference to obtain a secondary production quality index. The secondary production quality index is used to make production adjustment decisions. The data source monitoring module is connected to the production quality assessment module.

[0083] The production process monitoring module is used to acquire process stability, update the production quality index based on process stability, update the data compensation process based on process stability, perform contradiction inference on the process stability acquisition, obtain contradiction inference results, and update production adjustment decisions based on contradiction inference results. The production process monitoring module is connected to the data source monitoring module.

[0084] The production parameter control module is used to perform parameter boundary control on production quality data, obtain boundary control results, and optimize production adjustment decisions based on the boundary control results. The production parameter control module is connected to the production process monitoring module.

[0085] The decision execution module is used to control the equipment based on production adjustment decisions, and the decision execution module is connected to the production parameter control module.

[0086] Specifically, the production control system for the blood-activating and swelling-reducing external ointment is applied in the production equipment of the ointment. The system monitors data sources and production processes, and performs parameter boundary control to minimize the impact of equipment status and process parameters on production quality, thereby improving production quality and the consistency of the final product. Specifically, the system acquires production quality data through a production data acquisition module for multi-dimensional monitoring of production quality. It also acquires a production quality index through a production quality assessment module, measuring the quality status of the medicinal materials after mixing in a numerical form. When the production quality index fails to meet the standards, the system promptly analyzes the causes to adaptively improve production quality. Furthermore, the system monitors the status of the sensor cluster through a data source monitoring module to avoid the impact of data source fluctuations on production quality, thereby improving production efficiency. The system ensures the accuracy of quality monitoring and the consistency of the final product, further determining the reliability of the data source to prevent continued operation from significantly reducing production quality. It also uses a production process monitoring module to assess the degree of process stability, monitoring the stability of the equipment process and reducing production quality instability caused by process instability. Furthermore, it updates production adjustment decisions based on contradiction inference results to address potential sensor faults, thereby improving production quality and efficiency. The system also uses a production parameter control module to acquire boundary control results, enabling equipment control based on production adjustment decisions to improve production efficiency without exceeding the actual physical limits of the equipment. Finally, the system uses a decision execution module to control the equipment based on production adjustment decisions, adjusting process parameters in real time to achieve optimal performance, thus improving production quality.

[0087] Specifically, the production data acquisition module acquires production quality data, which includes multi-point component concentration values, paste viscosity, key particle size values, stirring power, real-time temperature, and mechanical vibration intensity.

[0088] Specifically, the production data acquisition module acquires production quality data to facilitate multi-dimensional monitoring of production quality, thereby improving the accuracy of process monitoring.

[0089] Specifically, the production quality assessment module obtains the production quality index based on the production quality data. Specifically, it obtains the uniformity R based on the multi-point component concentration values ​​in the production quality data, and obtains the physical texture B based on the paste viscosity and key particle size values ​​in the production quality data. The production quality index S is calculated based on the uniformity R, physical texture B, uniformity weight w1, and physical texture weight w2. The formula is set as S = R × w1 + B × w2, and the production quality index S is obtained, where w1 + w2 = 1.

[0090] Specifically, the uniformity refers to a numerical value that measures the degree of uniformity of the medicinal materials after stirring. The process of obtaining the uniformity R includes: based on the multi-point component concentration values ​​dp={dp1,dp2,..., } and sample quantity For the average concentration Perform calculations and set =(dp1+dp2+,...,+ ) / According to the average concentration The standard deviation sd is calculated, and sd = Based on standard deviation (sd) and mean concentration The relative standard deviation pd is calculated, and pd = sd / The relative standard deviation pd is mapped to the [0,1] interval using a maximum-minimum normalization algorithm to obtain the normalized relative standard deviation pd1. The uniformity R is then calculated based on the normalized relative standard deviation pd1, with R = 1 - pd1. The physical texture refers to a comprehensive index reflecting the fluidity and fineness of the blood-activating and swelling-reducing external ointment. The process of obtaining the physical texture B includes: comparing the ointment viscosity in the production quality data with a viscosity score curve to obtain the ointment viscosity score gd; and comparing the key particle size value with a preset particle size score table to obtain the key particle size score fd. The viscosity score curve refers to a pre-set standardized independent score that maps the ointment viscosity to an ointment viscosity score. A viscosity score curve is created by using historical paste viscosity as the x-axis and the corresponding paste viscosity score as the y-axis. The paste viscosity score is output by comparing the position of the paste viscosity on the x-axis. The preset particle size score table refers to a standardized independent score table for acquiring key particle size values. For example, a key particle size value less than 50 micrometers is scored as 1 point; for a key particle size value greater than 50 micrometers but less than 100 micrometers, the score decreases by 0.02 points for every 1 micrometer increase; and a value exceeding 100 micrometers is scored as 0 points, indicating that the physical texture is unqualified and requiring re-grinding. Here, 50 micrometers and 100 micrometers are the optimal thresholds for key particle size values ​​based on historical experience. Values ​​below 50 micrometers are considered acceptable. Micrometers can easily lead to wasted power, and particles larger than 80 micrometers can result in insufficient fineness of the final paste. The physical texture B is calculated based on the paste viscosity score gd, the key particle size score fd, the viscosity score weight n1, and the particle size score weight n2. The formula is B = gd × n1 + fd × n2, where n1 + n2 = 1. The viscosity score weight n1 measures the importance of the paste viscosity score in the physical texture, and the particle size score weight n2 measures the importance of the key particle size score in the physical texture. This embodiment does not limit the specific values ​​of the viscosity score weight n1 and the particle size score weight n2; those skilled in the art can freely choose according to actual needs. Since the topical ointment for promoting blood circulation and reducing swelling is a smear-type ointment, the viscosity of the ointment, which has a direct impact on the user experience, is more important. Therefore, n1=0.6 and n2=0.4 are set to maintain the balance between viscosity and fineness and increase the viscosity score weight. The uniformity weight w1 refers to the value that measures the importance of uniformity in the production quality index, and the physical texture weight w2 refers to the value that measures the importance of physical texture in the production quality index. This embodiment does not limit the specific value setting of the uniformity weight w1 and the physical texture weight w2. Those skilled in the art can freely choose according to actual needs. For example, w1=0.7 and w2=0.3 can be set according to the content uniformity of the topical ointment, which is of most concern to regulatory agencies.

[0091] Specifically, the production quality assessment module acquires the production quality index and measures the quality status of the blood-activating and swelling-reducing external ointment in a specific numerical form, which facilitates timely adjustment of the production process and control of the final quality, thereby improving the efficiency of quality monitoring.

[0092] Specifically, the production quality assessment module compares the production quality index S with the preset production quality index S0, judges the degree of compliance of the production quality index based on the comparison results, and performs cause analysis based on the judgment results, wherein:

[0093] When S≥S0, the production quality assessment module determines that the production quality index meets the standard and does not perform cause analysis.

[0094] When S < S0, the production quality assessment module determines that the production quality index does not meet the standard, performs cause analysis, and obtains the cause analysis results.

[0095] The production quality assessment module outputs production adjustment decisions based on the root cause analysis results. Specifically, it compares the root cause analysis results with preset root cause analysis results in the process adjustment strategy library, and outputs production adjustment decisions based on the comparison results.

[0096] When the root cause analysis results are consistent with the preset root cause analysis results, the production adjustment decision corresponding to the preset root cause analysis results will be output.

[0097] When the root cause analysis results are inconsistent with the preset root cause analysis results, the root cause analysis results are pushed out, and production adjustment decisions are obtained through manual settings and stored in the process adjustment strategy library.

[0098] Specifically, the preset production quality index refers to a preset value used to judge the degree of compliance of the production quality index. This embodiment does not limit the specific value of the preset production quality index S0. Those skilled in the art can freely choose according to actual needs. For example, if the lowest production quality index of qualified blood-activating and swelling-reducing external ointment produced in the past 24 hours is 0.86, then S0 = 0.86 is set. The degree of compliance of the production quality index includes compliance and non-compliance. The cause analysis refers to the process of judging the possible causes of failure in the production process through a Bayesian network model. In this embodiment, the data in the production quality data is used as nodes, and arrows represent the causal relationship between nodes. The probability table of each node is updated based on historical data. The historical data refers to the cause analysis results of historical occurrences and their corresponding probabilities. For example, the probability of increased mechanical vibration intensity due to loose stirring blades is 75%. A Bayesian network model is constructed. The cause analysis results refer to the possible causes of failure in the production process. For example, the current low production quality index S is mainly due to a significant decrease in uniformity R. While uniformity R decreases, the stirring power is stable but the real-time temperature is low. The process adjustment strategy library refers to the library of... The preset cause analysis results serve as an index, and the production adjustment decisions corresponding to the preset cause analysis results serve as a data retrieval library for related content. The preset cause analysis results refer to the preset index for retrieving related content. Historical cause analysis results can be stored in the process adjustment strategy library as preset cause analysis results, and the production adjustment decisions corresponding to the historical cause analysis results serve as related content corresponding to the preset cause analysis results. The cause analysis results being consistent with the preset cause analysis results means that the cause analysis results are completely identical to the preset cause analysis results. The cause analysis results being inconsistent with the preset cause analysis results means that the cause analysis results and the preset cause analysis results have at least one different cause. This embodiment does not limit the specific method of pushing the cause analysis results. Those skilled in the art can freely choose according to actual needs, such as generating to-do items based on the cause analysis results and pinning them to the top of the task list on the control interface. The manual setting refers to the process of manually setting production adjustment decisions based on the cause analysis results. The production adjustment decisions refer to a set of modification instructions generated after the cause analysis to drive the production device of the blood-activating and swelling-reducing external ointment.

[0099] Specifically, the production quality assessment module judges the degree of compliance of the production quality index. When the production quality index fails to meet the standard, it promptly analyzes the reasons, identifies the parameters affecting production quality in the production process, and outputs corresponding production adjustment decisions to make adjustments, thereby adaptively improving production quality.

[0100] Specifically, the data source monitoring module monitors the data source based on production quality data, specifically by: acquiring the backtracking uniformity Rh, calculating the first backtracking data difference Hv1 based on the backtracking uniformity Rh and the uniformity R, and setting Hv1=Rh-R;

[0101] The backtracking physical texture Bh is obtained, and the second backtracking data difference Hv2 is calculated based on the backtracking physical texture Bh and the physical texture B, and Hv2 is set as Bh-B;

[0102] The first backtracking data difference Hv1 and the second backtracking data difference Hv2 are compared with preset first backtracking data difference Hv10 and preset second backtracking data difference Hv20, respectively. Based on the comparison results, the status of the first and second backtracking data differences is determined, and data compensation processing is performed on the production quality index acquisition process according to the determination results. Specifically:

[0103] When Hv1≤Hv10 and Hv2≤Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is normal, and does not perform data compensation processing in the process of obtaining the production quality index.

[0104] When Hv1 > Hv10 and Hv2 ≤ Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the acquisition process of the production quality index: input the multi-point component concentration values ​​into the virtual uniformity sensor to obtain the virtual uniformity R' output by the virtual sensor, and calculate the production quality index S according to the virtual uniformity R', physical texture B, uniformity weight w1 and physical texture weight w2, and set S = R' × w1 + B × w2 to obtain the secondary production quality index S2;

[0105] When Hv1≤Hv10 and Hv2>Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the process of obtaining the production quality index: the paste viscosity and key particle size value are input into the virtual texture sensor to obtain the virtual physical texture B' output by the virtual sensor, and the production quality index S is calculated according to the uniformity R, the virtual physical texture B', the uniformity weight w1 and the physical texture weight w2. S=R×w1+B'×w2 is set to obtain the secondary production quality index S2.

[0106] When Hv1 > Hv10 and Hv2 > Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the acquisition process of the production quality index: the multi-point component concentration value, paste viscosity and key particle size value are input into the virtual uniformity sensor and the virtual texture sensor respectively, to obtain the virtual uniformity R' output by the virtual uniformity sensor and the virtual physical texture B' output by the virtual texture sensor, and calculate the production quality index S according to the virtual uniformity R', virtual physical texture B', uniformity weight w1 and physical texture weight w2, and set S = R' × w1 + B' × w2 to obtain the secondary production quality index S2.

[0107] Specifically, the backtracking uniformity refers to the uniformity occurring at the previous historical time step, where the previous time step refers to the backtracking time span during data source monitoring by the system. For example, backtracking two seconds from the current moment can be considered as the previous time step. The backtracking physical texture refers to the physical texture occurring at the previous historical time step. This embodiment does not limit the specific methods for obtaining the backtracking uniformity and backtracking physical texture; those skilled in the art can freely choose according to actual needs, such as obtaining the backtracking uniformity and backtracking physical texture through system operation logs. The preset first backtracking data... The difference and the preset second backtracking data difference refer to preset values ​​used to judge the state of the first backtracking data difference and the second backtracking data difference. This embodiment does not limit the specific values ​​of the preset first backtracking data difference Hv10 and the preset second backtracking data difference Hv20. Those skilled in the art can freely choose according to actual needs. For example, the lowest value of the first backtracking data difference and the second backtracking data difference occurring within the historical time window can be used as the preset first backtracking data difference and the preset second backtracking data difference. For example, the lowest value of the first backtracking data difference in the past 24 hours is 0.86, and the lowest value of the second backtracking data difference is... If the value is 0.81, then Hv10 = 0.86 and Hv20 = 0.81. The state of the first backtracking data difference and the second backtracking data difference refers to the normality of the sensor cluster reflected by the first backtracking data difference and the second backtracking data difference, including normal and abnormal. The virtual uniformity sensor refers to a mathematical model that replaces the online near-infrared spectrometer. This embodiment does not limit the specific construction form of the virtual uniformity sensor. Those skilled in the art can freely choose according to actual needs. For example, the first historical production quality database can be divided into a first virtual training set of 70%, a first virtual validation set of 20%, and a first virtual test set of 10%. The gradient boosting decision tree is trained through the first virtual training set. The parameters in the gradient boosting decision tree are optimized through cross-validation grid search to obtain the first trained gradient boosting decision tree. After each iteration, the performance index is calculated using the first virtual validation set. When the performance index on the first virtual validation set no longer improves in continuous iterations, early stopping is triggered to obtain the validated first trained gradient boosting decision tree. Then, the determination coefficient of the validated first trained gradient boosting decision tree on the first test set is calculated, and the determination coefficient is greater than 0.The gradient boosting decision tree with a training efficiency of 95% is used as the output of a virtual uniformity sensor. The first historical production quality database refers to a database that stores historical production quality data and their corresponding virtual uniformities. The virtual texture sensor refers to a mathematical model that replaces online viscometers and online laser particle size analyzers. This embodiment does not limit the specific construction method of the virtual texture sensor. Those skilled in the art can freely choose according to actual needs. For example, the second historical production quality database can be divided into a second virtual training set (70%), a second virtual validation set (20%), and a second virtual test set (10%). The gradient boosting decision tree is then used to evaluate the gradient quality of the second virtual training set. The gradient boosting decision tree is trained using the following settings: the input feature dimension is a two-dimensional feature vector composed of paste viscosity and key particle size values; the hyperparameters are optimized using cross-validation grid search; the number of trees is determined to be 200; the maximum depth of a single tree is 4; the learning rate is 0.15; the minimum number of samples for node re-split is 7; the minimum number of samples for leaf nodes is 3; and the sample sampling ratio is 0.8. Mean squared error is used as the loss function during training to obtain the second trained gradient boosting decision tree. After each iteration, the mean squared error index is calculated using the second virtual validation set. The tree is considered successful when the mean squared error index decreases by less than 1 × 10⁻⁶ over 10 consecutive iterations. −4 When the time is right, early stopping is triggered, and the second trained gradient boosting decision tree after verification is obtained. Then the determination coefficient of the second trained gradient boosting decision tree after verification on the second test set is calculated. The second trained gradient boosting decision tree after verification with a determination coefficient greater than 0.95 is used as the output of the virtual texture sensor. The second historical production quality database refers to the database that stores historical production quality data and its corresponding physical texture.

[0108] Specifically, the data source monitoring module monitors the status of the sensor cluster by comparing the previous backtracking uniformity and backtracking physical texture, so as to avoid the impact of data source fluctuations on production quality, thereby improving the accuracy of production quality monitoring and the consistency of the final product.

[0109] Specifically, the data source monitoring module compares the secondary production quality index S2 with the preset production quality index S0, judges the status of the data source based on the comparison result, and makes production adjustment decisions based on the judgment result, wherein:

[0110] When S2≥S0, the data source monitoring module determines that the data source situation is acceptable and does not make any decision adjustments to the production adjustment decision.

[0111] When S2 < S0, the data source monitoring module determines that the data source situation is unacceptable and makes a production adjustment decision: it will activate physical isolation protection and issue an alarm as the output of the production adjustment decision.

[0112] Specifically, the data source refers to the acceptable level of fluctuation in data measured by the online near-infrared spectrometer, online viscometer, and online laser particle size analyzer in the sensor cluster, which is judged based on the secondary production quality index and the preset production quality index. This includes acceptable and unacceptable fluctuations. The physical isolation protection refers to the process of closing the discharge valve in the filling machine, stopping stirring, and maintaining a constant temperature through the heating jacket. This embodiment does not limit the alarm method. Those skilled in the art can freely choose according to actual needs, such as providing maintenance reminders through pop-up windows on the system control interface.

[0113] Specifically, the data source monitoring module uses a secondary production quality index to assess the condition of the data source, thereby further determining the reliability of the data source. When the condition of the data source is unacceptable, it promptly implements physical isolation protection to prevent continued operation from significantly reducing production quality.

[0114] Specifically, the production process monitoring module acquires the process stability pm, compares the process stability pm with a preset process stability pm0, judges the degree of compliance of the process stability based on the comparison result, and updates the production quality index acquisition process and the data compensation process based on the judgment result, wherein:

[0115] When pm≥pm0, the production process monitoring module determines that the process stability meets the standard, and does not update the production quality index during the acquisition process or compensate for the data compensation process.

[0116] When pm < pm0, the production process monitoring module determines that the compliance level of the process stability is not up to standard, and performs index update on the process of obtaining the production quality index: the physical texture weight w2 is updated according to the update coefficient gf to obtain the updated physical texture weight w2', w2' = w2 × gf is set, and w1 = 1 - w2' is used as the physical texture weight w2, and the production quality index S is recalculated according to the uniformity R, physical texture B, uniformity weight w1 and physical texture weight w2;

[0117] The data compensation process involves updating the data: adding high-confidence baseline batch data packets to the training sets of the virtual uniformity sensor and the virtual texture sensor, and reconstructing the virtual uniformity sensor and the virtual texture sensor to obtain the updated virtual uniformity sensor and the updated virtual texture sensor. Then, the data compensation process is performed again based on the updated virtual uniformity sensor and the updated virtual texture sensor.

[0118] Specifically, the process stability refers to a numerical value that measures the stability of the process of the device. The process of obtaining process stability includes: acquiring vibration stability and temperature stability based on real-time temperature and mechanical vibration intensity. Vibration stability refers to the standard deviation of mechanical vibration intensity within the ointment processing time period, and temperature stability refers to the standard deviation of temperature within the ointment processing time period. The ointment processing time period refers to the length of time from when the pulverized medicinal materials enter the mixing tank for stirring to when they enter the cooling tank. In this embodiment, the ointment processing time is monitored through system operation logs. The vibration stability q1 and temperature stability q2 are recorded and acquired over a specific time period. The vibration stability q1 and temperature stability q2 are normalized using a maximum-minimum normalization algorithm to obtain normalized vibration stability q1 and normalized temperature stability q2. Based on the normalized vibration stability q1, normalized temperature stability q2, vibration stability weight z1, and temperature stability weight z2, the process stability pm is set as pm = (1-q1)×z1 + (1-q2)×z2. The vibration stability weight refers to a coefficient that measures the importance of the normalized vibration stability in the process stability, and the temperature stability weight refers to a coefficient that measures the importance of the normalized vibration stability in the process stability. The coefficient representing the importance of temperature stability in process stability after normalization is given, and z1 + z2 = 1. This embodiment does not limit the specific values ​​of the vibration stability weight z1 and the temperature stability weight z2. Those skilled in the art can freely choose according to actual needs. For example, if real-time temperature directly participates in the chemical reactions and physical changes of the production process and has a more direct impact on quality, then a higher weight is assigned to real-time temperature, setting z1 = 0.4 and z2 = 0.6. The preset process stability refers to a preset value used to judge the degree of achievement of process stability standards. This embodiment does not specify a preset value. The specific value of the process stability pm0 is limited, and those skilled in the art can freely choose according to actual needs. For example, based on historical production experience, pm0 can be set to 0.82. When the stability is lower than this value, the system determines that the process is in an unstable state, which may lead to unqualified production quality. When the stability is higher than this value, it is easy to trigger updates frequently, which may lead to system instability. The high confidence benchmark batch data package refers to the data package that stores the production quality data of the blood-activating and swelling-reducing external ointment with qualified production quality in a single production in history, as well as its corresponding uniformity and physical texture.

[0119] Specifically, the production process monitoring module judges the degree of process stability to monitor the stability of the equipment process, reduce the production quality instability caused by process instability, and thus improve production quality and product consistency.

[0120] Specifically, the production process monitoring module performs contradiction inference on the process stability acquisition process to obtain contradiction inference results. These results include whether a contradiction exists or not. Based on these results, the module updates the decision-making process for adjustment.

[0121] When the contradiction inference result is that there is no contradiction, the decision adjustment process is not updated.

[0122] When the contradiction inference result indicates the existence of a contradiction, the decision adjustment process is updated: the physical isolation protection and alarm activation in the decision adjustment are replaced with sensing and detection by temperature sensors and vibration acceleration sensors.

[0123] Specifically, the contradiction inference refers to the process of verifying whether uniformity, physical texture, and production quality index are normal and up to standard when process stability is substandard. The contradiction inference result of "existing contradiction" means that when process stability is substandard, uniformity, physical texture, and production quality index are all normal and up to standard. The contradiction inference result of "no contradiction" means that when process stability is substandard, at least one of uniformity, physical texture, and production quality index is abnormal or substandard. The sensing detection refers to the operation of verifying whether there is a fault in the temperature sensor and vibration acceleration sensor. This embodiment does not limit the specific method of sensing detection. Those skilled in the art can freely choose according to actual needs, such as signal amplitude range check.

[0124] Specifically, the production process monitoring module updates production adjustment decisions based on contradiction inference results, so as to further monitor temperature sensors and vibration acceleration sensors in the data source and deal with potential sensor failures in a timely manner, thereby improving production quality and efficiency.

[0125] Specifically, the production parameter control module uses a multi-objective optimization algorithm to perform parameter boundary control on the production quality number, obtains the boundary control result, and optimizes the production adjustment decision based on the boundary control result: the boundary control result is added to the production adjustment decision.

[0126] Specifically, the parameter boundary control process is as follows: using key process parameters as decision variables, with the objectives of maximizing the production quality index and minimizing production time, and setting dynamic boundaries, the core constraint is to construct a constrained optimization problem for quality compliance. A multi-objective evolutionary algorithm is used to search within the feasible region of the key process parameters to obtain the Pareto optimal solution set. The optimal parameter combination is selected from the Pareto optimal solution set as the boundary control result. The key process parameters refer to the parameter values ​​that need to be adjusted in production adjustment decisions, such as increasing the stirring speed to 105 rpm. The feasible region of the key process parameters refers to the set of all process parameters that satisfy various constraints, such as quality compliance and equipment limits. The dynamic boundary refers to the temporary value boundary of the key process parameters, such as temporarily lowering the upper limit of the speed when the bearing temperature is high. The dynamic boundary is obtained by consulting the equipment technical specifications and the factory nameplate. The optimal parameter combination refers to the process parameters corresponding to the optimal point selected from the Pareto optimal solution set according to preset preferences, such as prioritizing quality or rushing the production schedule for this batch, such as a temperature of 68.5℃ and a speed of 108 rpm.

[0127] Specifically, the production parameter control module acquires the boundary control results so that when controlling the device based on production adjustment decisions, it can ensure production quality and improve production efficiency without exceeding the actual physical limits of the device.

[0128] Specifically, the decision execution module controls the equipment based on production adjustment decisions.

[0129] Specifically, the device control refers to the process of driving the production device of the blood-activating and swelling-reducing external ointment to make production adjustments based on production adjustment decisions. This embodiment does not limit the specific method of device control. Those skilled in the art can freely choose according to actual needs, such as using a programmable logic controller for device control.

[0130] Specifically, the decision execution module controls the equipment based on production adjustment decisions to adjust process parameters in real time to achieve the optimal state, thereby improving production quality.

[0131] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A production apparatus for a topical ointment for promoting blood circulation and reducing swelling, characterized in that, The device includes: The herbal medicine washing machine (1) is connected to the vacuum dryer (3) through the first conveying pipe (201) and is used to clean the raw materials of the ointment to obtain the cleaned herbal medicine. The conveying pipe (2) includes a first conveying pipe (201), a second conveying pipe (202), a third conveying pipe (203), a fourth conveying pipe (204), and a fifth conveying pipe (205). The first conveying pipe (201) is used to connect the herbal medicine washing machine (1) and the vacuum dryer (3) and to convey the washed herbal medicine from the herbal medicine washing machine (1) to the vacuum dryer (3). The second conveying pipe (202) is used to connect the vacuum dryer (3) and the universal pulverizer (5) and to convey the dried herbal medicine from the vacuum dryer (3) to the universal pulverizer. The machine (5), the third conveying pipe (203) is used to connect the universal pulverizer (5) and the mixing tank (6), and to convey the pulverized medicinal materials from the universal pulverizer (5) to the mixing tank (6). The fourth conveying pipe (204) is used to connect the mixing tank (6) and the cooling tank (7), and to convey the mixed medicinal materials from the mixing tank (6) to the cooling tank (7). The fifth conveying pipe (205) is used to connect the cooling tank (7) and the filling machine (9), and to convey the blood-activating and swelling-reducing external ointment from the cooling tank (7) to the filling machine (9). Vacuum dryer (3), which is connected to the first seal (401) and the second seal (402), and is connected to the herbal medicine washing machine (1) through the first conveying pipe (201), and to the universal pulverizer (5) through the second conveying pipe (202), is used to vacuum dry the cleaned herbal medicine to obtain dried herbal medicine; A sealing element (4), comprising a first sealing element (401) and a second sealing element (402), is used to seal the vacuum dryer (3); The universal pulverizer (5) is connected to the vacuum dryer (3) through the second conveying pipe (20) and to the mixing tank (6) through the third conveying pipe (203). It is used to pulverize the dried medicinal materials according to the production adjustment decision to obtain pulverized medicinal materials. The mixing tank (6) is connected to the universal pulverizer (5) through the third conveying pipe (203) and to the cooling tank (7) through the fourth conveying pipe (204). It is also connected to the production control system (8) of the blood-activating and swelling-reducing external ointment through an internal connection line (not shown in the figure). It is used to stir the pulverized medicinal materials according to the production adjustment decision to obtain the stirred medicinal materials. Cooling tank (7), which is connected to mixing tank (6) through fourth conveying pipe (204) and to filling machine (9) through fifth conveying pipe (205), is used to cool the stirred medicinal materials to obtain blood-activating and swelling-reducing external ointment; The production control system (8) for the blood-activating and swelling-reducing external ointment is connected to the mixing tank (6) via an internal connection line (not shown in the figure). It is used to acquire production quality data, acquire production quality index, perform cause analysis, output production adjustment decisions, monitor data sources and perform data compensation processing, adjust production adjustment decisions, update the index during the acquisition process of production quality index, update the data compensation processing process, update the decision adjustment process, and optimize the production adjustment decision. The filling machine (9) is connected to the cooling tank (7) via the fifth conveying pipe (205) and is used to fill the blood-activating and swelling-reducing external ointment.

2. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 1, characterized in that, The mixing tank includes: A stirring paddle (601) is placed inside a mixing tank (6) and is used to stir the pulverized medicinal materials according to production adjustment decisions; A heating jacket (602) is placed outside the mixing tank (6) for heating the mixing tank (6) according to production adjustment decisions; A sensor cluster (603), placed on the inner wall of the mixing tank (6), is used to collect production quality data. The sensor cluster includes an online near-infrared spectrometer (631), an online viscometer (632), an online laser particle size analyzer (633), a power transmitter (634), a temperature sensor (635), and a vibration acceleration sensor (636). The production quality data includes multi-point component concentration values, paste viscosity, key particle size values, stirring power, real-time temperature, and mechanical vibration intensity. The online viscometer (632) is used to collect paste viscosity, the online laser particle size analyzer (633) is used to collect key particle size values, the online near-infrared spectrometer (631) is used to collect multi-point component concentration values, the power transmitter (634) is used to collect stirring power, the temperature sensor (635) is used to collect real-time temperature, and the vibration acceleration sensor (636) is used to collect mechanical vibration intensity.

3. A production control system for a topical ointment for promoting blood circulation and reducing swelling as described in any one of claims 1-2, the system comprising: The production data acquisition module is used to acquire production quality data; The production quality assessment module is used to obtain the production quality index based on production quality data, perform cause analysis based on the production quality index, obtain the cause analysis results, and output production adjustment decisions based on the cause analysis results. The data source monitoring module is used to monitor the data source based on production quality data, obtain the first backtracking data difference and the second backtracking data difference, and perform data compensation processing on the acquisition process of the production quality index based on the first backtracking data difference and the second backtracking data difference to obtain the secondary production quality index. The module then makes production adjustment decisions based on the secondary production quality index. The production process monitoring module is used to acquire process stability, update the production quality index based on process stability, update the data compensation process based on process stability, perform contradiction inference on the process of acquiring process stability, obtain contradiction inference results, and update the decision-making process based on contradiction inference results. The production parameter control module is used to perform parameter boundary control on production quality data, obtain boundary control results, and optimize production adjustment decisions based on the boundary control results. The decision execution module is used to control the equipment based on production adjustment decisions.

4. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 3, characterized in that, The production quality assessment module obtains the production quality index based on the production quality data. Specifically, it obtains the uniformity R based on the multi-point component concentration values ​​in the production quality data, and obtains the physical texture B based on the paste viscosity and key particle size values ​​in the production quality data. The production quality index S is calculated based on the uniformity R, physical texture B, uniformity weight w1, and physical texture weight w2. The formula is set as S = R × w1 + B × w2, and the production quality index S is obtained, where w1 + w2 = 1. The production quality assessment module compares the production quality index S with the preset production quality index S0, judges the degree of compliance of the production quality index based on the comparison results, and performs cause analysis based on the judgment results, wherein: When S≥S0, the production quality assessment module determines that the production quality index meets the standard and does not perform cause analysis. When S < S0, the production quality assessment module determines that the production quality index does not meet the standard, performs cause analysis, and obtains the cause analysis results. The production quality assessment module outputs production adjustment decisions based on the root cause analysis results. Specifically, it compares the root cause analysis results with preset root cause analysis results in the process adjustment strategy library, and outputs production adjustment decisions based on the comparison results. When the root cause analysis results are consistent with the preset root cause analysis results, the production adjustment decision corresponding to the preset root cause analysis results will be output. When the root cause analysis results are inconsistent with the preset root cause analysis results, the root cause analysis results are pushed out, and production adjustment decisions are obtained through manual settings and stored in the process adjustment strategy library.

5. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 4, characterized in that, The data source monitoring module monitors the data source based on production quality data, specifically by: acquiring the backtracking uniformity Rh, calculating the first backtracking data difference Hv1 based on the backtracking uniformity Rh and the uniformity R, and setting Hv1=Rh-R; The retrospective physical texture Bh is obtained, and the second retrospective data difference Hv2 is calculated based on the retrospective physical texture Bh and the physical texture B, and Hv2 is set as Bh-B; The first backtracking data difference Hv1 and the second backtracking data difference Hv2 are compared with preset first backtracking data difference Hv10 and preset second backtracking data difference Hv20, respectively. Based on the comparison results, the status of the first and second backtracking data differences is determined, and data compensation processing is performed on the production quality index acquisition process according to the determination results. Specifically: When Hv1≤Hv10 and Hv2≤Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is normal, and does not perform data compensation processing in the process of obtaining the production quality index. When Hv1 > Hv10 and Hv2 ≤ Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the acquisition process of the production quality index: input the multi-point component concentration values ​​into the virtual uniformity sensor to obtain the virtual uniformity R' output by the virtual sensor, and calculate the production quality index S according to the virtual uniformity R', physical texture B, uniformity weight w1 and physical texture weight w2, and set S = R' × w1 + B × w2 to obtain the secondary production quality index S2; When Hv1≤Hv10 and Hv2>Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the process of obtaining the production quality index: the paste viscosity and key particle size value are input into the virtual texture sensor to obtain the virtual physical texture B' output by the virtual sensor, and the production quality index S is calculated according to the uniformity R, the virtual physical texture B', the uniformity weight w1 and the physical texture weight w2. S=R×w1+B'×w2 is set to obtain the secondary production quality index S2. When Hv1 > Hv10 and Hv2 > Hv20, the data source monitoring module determines that the state of the first backtracking data difference and the second backtracking data difference is abnormal, and performs data compensation processing on the acquisition process of the production quality index: the multi-point component concentration value, paste viscosity and key particle size value are input into the virtual uniformity sensor and the virtual texture sensor respectively, to obtain the virtual uniformity R' output by the virtual uniformity sensor and the virtual physical texture B' output by the virtual texture sensor, and calculate the production quality index S according to the virtual uniformity R', virtual physical texture B', uniformity weight w1 and physical texture weight w2, and set S = R' × w1 + B' × w2 to obtain the secondary production quality index S2.

6. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 5, characterized in that, The data source monitoring module compares the secondary production quality index S2 with the preset production quality index S0, judges the status of the data source based on the comparison result, and makes production adjustment decisions based on the judgment result, wherein: When S2≥S0, the data source monitoring module determines that the data source situation is acceptable and does not make any decision adjustments to the production adjustment decision. When S2 < S0, the data source monitoring module determines that the data source situation is unacceptable and makes a production adjustment decision: it will activate physical isolation protection and issue an alarm as the output of the production adjustment decision.

7. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 6, characterized in that, The production process monitoring module acquires the process stability pm, compares the process stability pm with the preset process stability pm0, judges the degree of compliance of the process stability based on the comparison result, and updates the production quality index acquisition process and the data compensation process based on the judgment result. When pm≥pm0, the production process monitoring module determines that the process stability meets the standard, and does not update the production quality index during the acquisition process or compensate for the data compensation process. When pm < pm0, the production process monitoring module determines that the compliance level of the process stability is not up to standard, and performs index update on the process of obtaining the production quality index: the physical texture weight w2 is updated according to the update coefficient gf to obtain the updated physical texture weight w2', w2' = w2 × gf is set, and w1 = 1 - w2' is used as the physical texture weight w2, and the production quality index S is recalculated according to the uniformity R, physical texture B, uniformity weight w1 and physical texture weight w2; The data compensation process involves updating the data: adding high-confidence baseline batch data packets to the training sets of the virtual uniformity sensor and the virtual texture sensor, and reconstructing the virtual uniformity sensor and the virtual texture sensor to obtain the updated virtual uniformity sensor and the updated virtual texture sensor. Then, the data compensation process is performed again based on the updated virtual uniformity sensor and the updated virtual texture sensor.

8. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 7, characterized in that, The production process monitoring module performs contradiction inference on the process stability acquisition process, obtains contradiction inference results, including whether a contradiction exists or not, and updates the decision-making process based on the contradiction inference results, wherein: When the contradiction inference result is that there is no contradiction, the decision adjustment process is not updated. When the contradiction inference result indicates the existence of a contradiction, the decision adjustment process is updated: the physical isolation protection and alarm activation in the decision adjustment are replaced with sensing and detection by temperature sensors and vibration acceleration sensors.

9. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 8, characterized in that, The production parameter control module uses a multi-objective optimization algorithm to perform parameter boundary control on the production quality number, obtains the boundary control results, and optimizes the production adjustment decision based on the boundary control results: the boundary control results are added to the production adjustment decision.

10. The production apparatus for the blood-activating and swelling-reducing external ointment according to claim 9, characterized in that, The decision execution module controls the equipment based on production adjustment decisions.

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