An intelligent processing and detection system for capsule preparation production

Abstract

The present invention belongs to the technical field of capsule preparation production supervision, and specifically is an intelligent processing and detection system for capsule preparation production, comprising a server, a raw material preparation and mixing supervision module, a capsule filling supervision module, a capsule weighing feedback module, a capsule visual detection module and a production early warning module; the present invention uses the raw material preparation and mixing supervision module to monitor and analyze the operation process of a mixing device in real time, and performs material distribution evaluation on the mixed materials after mixing, effectively ensuring the uniformity of material distribution in the production of capsule preparations, and uses the capsule filling supervision module to monitor the filling process in real time, which is conducive to the efficient and stable operation of the filling equipment, realizes the full process supervision of capsule preparation production, effectively ensures the quality of the produced capsule preparations, and can comprehensively evaluate the production performance of the production line, thereby ensuring the stable and efficient operation of the corresponding capsule preparation production line, with a high level of intelligence.

Description

Technical Field

[0001] The invention relates to the technical field of capsule preparation production supervision, and in particular to an intelligent processing detection system for capsule preparation production. Background Art

[0002] Capsule preparations refer to solid preparations made by filling raw materials and appropriate excipients into hollow capsules or sealing them in soft capsule materials. These raw materials can be pure drug powders, or in the form of liquids or suspensions. Excipients are used to increase the stability and fluidity of the drugs or to cover up bad odors. The main advantages of capsule preparations include taste masking, improved drug stability, rapid onset of action, solidification of liquid drugs, and delayed or localized release of drugs.

[0003] At present, in the production process of capsule preparations, it is difficult to achieve effective supervision of the entire process from raw material preparation and mixing, capsule filling to capsule finished product testing. It is impossible to timely and accurately feedback abnormal mixing and filling conditions, and it is impossible to accurately evaluate the quality of each capsule and the operating performance of the corresponding capsule preparation production line, which increases the management difficulty of managers and has a low level of intelligence and automation.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent processing and detection system for capsule preparation production, which solves the problems that the prior art is difficult to achieve effective supervision of the entire process from raw material preparation and mixing, capsule filling to capsule finished product testing, cannot timely and accurately feedback abnormal mixing conditions and abnormal filling conditions, and cannot accurately evaluate the quality of each capsule and the operating performance of the corresponding capsule preparation production line, is difficult to manage, and has low intelligence and automation levels.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent processing and detection system for capsule preparation production, comprising a server, a raw material preparation and mixing supervision module, a capsule filling supervision module, a capsule weighing feedback module, a capsule visual detection module and a production early warning module; when the capsule preparation is produced, the raw materials for preparing the capsule preparation are conveyed to a mixing device in a preset proportion and sequence, the mixing device is operated to make the raw materials evenly distributed, the raw material preparation and mixing supervision module monitors the operation process of the mixing device in real time and generates a mixing detection abnormality signal or a mixing detection normal signal through analysis, and after the mixing is completed, the material distribution of the mixed material is evaluated and a material distribution qualified signal or a material distribution unqualified signal is generated, and the mixing detection abnormality signal and the material distribution unqualified signal are sent to the production early warning module via the server;

[0008] When a qualified material distribution signal is generated, the evenly mixed material is filled into the capsule through the filling equipment, and the capsule filling supervision module monitors the filling process in real time, generates a qualified filling detection signal or an unqualified filling detection signal through analysis, and sends the unqualified filling detection signal to the production early warning module via the server; the capsule weighing feedback module weighs the produced capsules, marks the corresponding capsules as inferior capsules or superior capsules based on the weighing information, and sends the weighing detection mark information of the capsules to the server for storage; the capsule visual inspection module visually scans the produced capsules, identifies the appearance defects of the capsules based on the visual scanning information, and marks the corresponding capsules as abnormal capsules or normal capsules accordingly, and sends the visual inspection mark information of the corresponding capsules to the server for storage.

[0009] Furthermore, the specific operation process of the raw material preparation and mixing supervision module includes:

[0010] During the operation of the mixing device, the rotation speed of the stirring component in the mixing device and the internal temperature of the mixing device are collected, the rotation speed is calculated to be different from the preset target speed and the absolute value is taken to obtain the mixed rotation speed value, and the internal temperature of the mixing device is calculated to be different from the preset target temperature and the absolute value is taken to obtain the mixed temperature value; the mixed rotation speed value and the mixed temperature value are numerically compared with the preset mixed rotation speed threshold value and the preset mixed temperature threshold value respectively, if the mixed rotation speed value or the mixed temperature value exceeds the corresponding preset threshold value, it is judged that the mixing device is in a high deviation state of operation;

[0011] The total time that the mixing device is in a high deviation state in a unit time is collected and marked as the total deviation time value, and the maximum value of a single continuous time that the mixing device is in a high deviation state in a unit time is collected and marked as the single deviation time value, and the ratio of the power consumed by the mixing device in a unit time to its average operating power is marked as a mixing consumption ratio value, and the difference between the mixing consumption ratio value and the median of a preset mixing consumption ratio value range is calculated and the absolute value is taken to obtain a mixing consumption detection value; the mixing consumption detection value, the total deviation time value and the single deviation time value are numerically calculated to obtain a raw material mixing difference value, and the raw material mixing difference value is numerically compared with a preset raw material mixing difference threshold value; if the raw material mixing difference value exceeds the preset raw material mixing difference threshold value, a mixing detection abnormal signal is generated; if the raw material mixing difference value does not exceed the preset raw material mixing difference threshold value, a mixing detection normal signal is generated.

[0012] Furthermore, the specific operation process of the raw material preparation and mixing supervision module also includes:

[0013] After the mixing is completed, the materials at several positions in the mixing device are obtained and the components are tested. The percentages of various raw materials in the corresponding positions are obtained through the component testing and marked as the raw material percentage values. The corresponding positions in the mixing device are marked as positions with no material bias, positions with high material bias or positions with low material bias through position material bias assessment and analysis.

[0014] If there is no material deviation area or a high material deviation area in the mixing device, an unqualified material distribution signal is generated; if there is a material deviation area but no high material deviation area in the mixing device, the ratio of the number of low material deviation areas to the number of material deviation areas is marked as the mixing distribution coefficient, and the mixing distribution coefficient is numerically compared with the preset mixing distribution coefficient threshold. If the mixing distribution coefficient exceeds the preset mixing distribution coefficient threshold, an unqualified material distribution signal is generated; if the mixing distribution coefficient does not exceed the preset mixing distribution coefficient threshold, a qualified material distribution signal is generated.

[0015] Furthermore, the specific analysis process of the position material deviation assessment analysis is as follows:

[0016] Compare the raw material percentage values ​​of various raw materials in the corresponding parts with the corresponding preset raw material percentage value ranges one by one. If the raw material percentage values ​​of various raw materials in the corresponding parts are all within the corresponding preset raw material percentage value ranges, the corresponding parts are marked as parts without material deviation;

[0017] If the raw material segregation value of the corresponding raw material in the corresponding part is not within the corresponding preset raw material segregation value range, the corresponding raw material is marked as a distribution abnormal material, and the deviation value of the raw material segregation value of the corresponding distribution abnormal material compared with the corresponding preset raw material segregation value range is marked as a raw material segregation deviation value; each group of raw materials is set in advance to correspond to a group of deviation influence values, and the raw material segregation value of the corresponding distribution abnormal material in the corresponding part is multiplied by the matched deviation influence value to obtain the raw material segregation value, and the raw material segregation values ​​of all distribution abnormal materials in the corresponding part are summed up to obtain the part material deviation value;

[0018] The material deviation value of the corresponding part in the mixing device is numerically compared with the preset material deviation threshold. If the material deviation value exceeds the preset material deviation threshold, the corresponding part is marked as a high material deviation part; if the material deviation value exceeds the preset material deviation threshold, the corresponding part is marked as a low material deviation part.

[0019] Furthermore, the specific operation process of the capsule weighing feedback module is as follows:

[0020] The corresponding capsule is weighed by a weighing device, the weighed mass of the corresponding capsule is obtained and marked as the capsule re-inspection value, and the capsule re-inspection value is numerically compared with the preset capsule re-inspection value range. If the capsule re-inspection value is not within the preset capsule re-inspection value range, the corresponding capsule is marked as a heavy and inferior capsule; if the corresponding capsule re-inspection value is within the preset capsule re-inspection value range, the corresponding capsule is marked as a heavy and superior capsule.

[0021] Furthermore, the specific operation process of the capsule visual detection module is as follows:

[0022] The corresponding capsule is scanned by a visual scanning device to obtain an image of the capsule appearance. The capsule appearance image is used to determine whether the shape of the capsule is regular, the surface is smooth, and whether there are cracks or bubble defects. If the shape of the corresponding capsule is regular, the surface is smooth, and there are no cracks or bubble defects, the corresponding capsule is marked as a normal capsule; if the shape of the corresponding capsule is irregular or the surface is not smooth or there are cracks or bubble defects, the corresponding capsule is marked as an abnormal capsule.

[0023] Furthermore, the specific operation process of the capsule filling supervision module includes:

[0024] Collect environmental information of the operation area of ​​the filling equipment when performing the filling operation, including real-time environmental temperature, real-time environmental humidity, environmental dust data and microbial data, and mark the deviation between the real-time environmental temperature and the preset suitable environmental temperature standard value for capsule preparation production as the temperature deviation value, and similarly obtain the humidity deviation value; calculate the temperature deviation value, humidity deviation value, environmental dust data and microbial data to obtain the filling ring value, and compare the filling ring value with the preset filling ring threshold. If the filling ring value exceeds the preset filling ring threshold, a filling detection unqualified signal is generated;

[0025] If the filling ring value does not exceed the preset filling ring threshold, the capsule filling efficiency data of the filling equipment within unit time and the material delivery speed fluctuation value during each capsule filling are collected, and the mean of all material delivery speed fluctuation values ​​within unit time is calculated to obtain the filling and conveying evaluation value. The capsule filling efficiency data and the median of the preset capsule filling efficiency data range are differenced and the absolute value is taken to obtain the capsule filling efficiency deviation value; the capsule filling efficiency deviation value and the filling and conveying evaluation value are numerically calculated to obtain the capsule filling detection value, and the capsule filling detection value is numerically compared with the preset capsule filling detection threshold. If the capsule filling detection value exceeds the preset capsule filling detection threshold, a filling detection unqualified signal is generated; if the capsule filling detection value does not exceed the preset capsule filling detection threshold, a filling detection qualified signal is generated.

[0026] Furthermore, the server is communicatively connected with the production line comprehensive evaluation module, and the production line comprehensive evaluation module is used to set the detection period, obtain the number of heavy and inferior capsules and the number of heavy and high-quality capsules produced by the corresponding production line during the detection period, and calculate the ratio of the number of heavy and inferior capsules to the number of heavy and high-quality capsules to obtain the capsule heavy and inferior detection value; and obtain the number of abnormal capsules and the number of normal capsules produced by the corresponding production line during the detection period, and calculate the ratio of the number of abnormal capsules to the number of normal capsules to obtain the capsule abnormal detection value; numerically compare the capsule heavy and inferior detection value and the capsule abnormal detection value with the preset capsule heavy and inferior detection threshold and the preset capsule abnormal detection threshold, respectively; if the capsule heavy and inferior detection value or the capsule abnormal detection value exceeds the corresponding preset threshold, a production line comprehensive evaluation unqualified signal is generated; if both the capsule heavy and inferior detection value and the capsule abnormal detection value do not exceed the corresponding preset threshold, a full production line evaluation and analysis is performed.

[0027] Furthermore, the specific analysis process of the full production line evaluation and analysis is as follows:

[0028] The ratio of the number of times the corresponding production line generates abnormal mixing detection signals during the production process within the detection period to the number of times the raw material preparation and mixing is marked as the raw material mixing frequency value, and the ratio of the number of times the material distribution unqualified signals are generated to the number of times the raw material preparation and mixing is marked as the material distribution frequency value; and the ratio of the number of times the filling detection unqualified signals are generated during the production process of the corresponding production line within the detection period to the total operation time of the filling equipment is marked as the capsule filling frequency value, and the raw material mixing frequency value, the material distribution frequency value, the capsule filling frequency value, the capsule weight and inferior detection value and the capsule storage abnormality detection value are normalized and calculated to obtain the production line traceability evaluation value; the production line traceability evaluation value is numerically compared with the preset production line traceability evaluation threshold value, and if the production line traceability evaluation value exceeds the preset production line traceability evaluation threshold value, a production line comprehensive evaluation unqualified signal is generated; if the production line traceability evaluation value does not exceed the preset production line traceability evaluation threshold value, a production line comprehensive evaluation qualified signal is generated.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. In the present invention, the operation process of the mixing device is monitored in real time by the raw material preparation and mixing supervision module, and a mixing detection abnormal signal or a mixing detection normal signal is generated by analysis. After the mixing is completed, the material distribution of the mixed material is evaluated and a material distribution qualified signal or a material distribution unqualified signal is generated. When the mixing detection abnormal signal or the material distribution unqualified signal is generated, the production early warning module issues a corresponding early warning, which effectively ensures the uniformity of material distribution of the produced capsule preparations and significantly improves the quality of the produced capsule preparations; and the filling process is monitored in real time by the capsule filling supervision module, and a filling detection qualified signal or a filling detection unqualified signal is generated by analysis. When the filling detection unqualified signal is generated, the production early warning module issues a corresponding early warning, which is conducive to the efficient and stable operation of the filling equipment, further ensures the quality of the produced capsule preparations, and significantly reduces the management difficulty of the management personnel;

[0031] 2. In the present invention, the produced capsules are weighed by the capsule weighing feedback module, and the corresponding capsules are marked as inferior capsules or superior capsules based on the weighing information. The capsule visual inspection module visually scans the produced capsules by visual scanning inspection equipment, and identifies the appearance defects of the capsules based on the visual scanning information, so as to accurately feedback the quality status of each capsule preparation. The production performance status of the corresponding production line during the inspection period is comprehensively evaluated by the production line comprehensive evaluation module, and a production line comprehensive evaluation qualified signal or a production line comprehensive evaluation unqualified signal is generated. When the production line comprehensive evaluation unqualified signal is generated, personnel training and equipment inspection and other measures are promptly carried out on the corresponding production line, so as to ensure the stable and efficient operation of the corresponding capsule preparation production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0033] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0034] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0035] 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.

[0036] Embodiment 1: Figure 1As shown, the present invention proposes an intelligent processing and detection system for capsule preparation production, comprising a server, a raw material preparation and mixing supervision module, a capsule filling supervision module, a capsule weighing feedback module, a capsule visual detection module and a production early warning module, and the server is communicatively connected with the raw material preparation and mixing supervision module, the capsule filling supervision module, the capsule weighing feedback module, the capsule visual detection module and the production early warning module;

[0037] The production of capsule preparations is carried out through the corresponding production line. The production equipment involved in the production line of capsule production includes mixing devices, filling equipment, etc. When producing capsule preparations, the raw materials for preparing capsule preparations are transported to the mixing device according to the preset proportion and sequence. The mixing device is operated to make the raw materials evenly distributed. The raw material preparation and mixing supervision module monitors the operation process of the mixing device in real time and generates a mixing detection abnormal signal or a mixing detection normal signal through analysis, specifically:

[0038] During the operation of the mixing device, the rotation speed of the stirring component in the mixing device and the internal temperature of the mixing device are collected, the rotation speed is calculated with the preset target speed and the absolute value is taken to obtain the mixing speed value, and the internal temperature of the mixing device is calculated with the preset target temperature and the absolute value is taken to obtain the mixing temperature value; the mixing speed value and the mixing temperature value are numerically compared with the preset mixing speed threshold value and the preset mixing temperature threshold value respectively, if the mixing speed value or the mixing temperature value exceeds the corresponding preset threshold value, it indicates that the mixing performance of the mixing device at the corresponding moment is poor, and it is judged that the mixing device is in a high deviation state of operation;

[0039] The total time that the mixing device is in a high deviation state in a unit time is collected and marked as the total deviation time value, and the maximum single duration of the mixing device in a high deviation state in a unit time is collected and marked as the single deviation time value, and the ratio of the power consumed by the mixing device in a unit time to its average operating power is marked as a mixed consumption ratio value, and the difference between the mixed consumption ratio value and the median of the preset mixed consumption ratio value range is calculated and the absolute value is taken to obtain the mixed consumption detection value; wherein, the larger the value of the mixed consumption detection value is, the more abnormal the power consumption performance of the mixing device is;

[0040] The raw material mixing value YF is obtained by numerically calculating the mixing consumption detection value YR, the total time value of operation difference YS and the single time value of operation difference YD through the formula YF=hy1*YR+(hy2*YS+hy3*YD) / hy1, wherein hy1, hy2 and hy3 are preset proportional coefficients, hy1>hy3>hy2>0.26; and the larger the numerical value of the raw material mixing value YF is, the worse the mixing performance of the mixing device per unit time is; the raw material mixing value YF is numerically compared with the preset raw material mixing threshold value, if the raw material mixing value YF exceeds the preset raw material mixing threshold value, indicating that the mixing performance of the mixing device per unit time is poor, then a mixing detection abnormal signal is generated; if the raw material mixing value YF does not exceed the preset raw material mixing threshold value, indicating that the mixing performance of the mixing device per unit time is good, then a mixing detection normal signal is generated.

[0041] After the mixing is completed, the raw material preparation and mixing supervision module evaluates the material distribution of the mixed materials and generates a qualified material distribution signal or an unqualified material distribution signal, and sends the abnormal mixing detection signal and the unqualified material distribution signal to the production early warning module via the server. When the production early warning module receives the abnormal mixing detection signal or the unqualified material distribution signal, it issues a corresponding early warning, which is convenient for the management personnel to grasp the material mixing status in detail. When the management personnel receive the corresponding early warning, they can make targeted corresponding control measures in time, thereby effectively ensuring the uniformity of material distribution of the produced capsule preparations, significantly improving the quality of the produced capsule preparations, and reducing the management difficulty of the management personnel; specifically:

[0042] After the mixing is completed, the materials at several positions in the mixing device are obtained and the components are detected. Preferably, the components are detected mainly by using an infrared spectrometer and a gas chromatograph. The percentages of various raw materials in the materials at the corresponding positions are obtained through the component detection and marked as raw material percentage values. The raw material percentage values ​​of various raw materials at the corresponding positions are compared with the corresponding preset raw material percentage value ranges one by one. If the raw material percentage values ​​of various raw materials at the corresponding positions are all within the corresponding preset raw material percentage value ranges, indicating that the contents of various raw materials in the materials at the corresponding positions meet the requirements and the distribution of the raw materials in the materials is relatively uniform, the corresponding positions are marked as positions without material bias.

[0043] If the raw material proportion value of the corresponding raw material in the corresponding part is not within the corresponding preset raw material proportion value range, the corresponding raw material is marked as a distribution abnormal material, and the deviation value of the raw material proportion value of the corresponding distribution abnormal material compared with the corresponding preset raw material proportion value range is marked as a raw material proportion deviation value; each group of raw materials is set in advance to correspond to a group of deviation influence values, wherein the values ​​of the deviation influence values ​​are all greater than zero, and are pre-set by the management personnel and stored in the server; and, the greater the degree of influence of the deviation of the corresponding raw material on the quality of the capsule preparation, the greater the value of the deviation influence value matched thereto; the raw material proportion deviation value of the corresponding distribution abnormal material in the corresponding part is multiplied by the matched deviation influence value to obtain the raw material segregation value, and the raw material segregation values ​​of all distribution abnormal materials in the corresponding part are summed up to obtain the part material deviation value;

[0044] It should be noted that the larger the value of the position material deviation value of the corresponding position, the worse the material distribution condition of the corresponding position; the position material deviation value of the corresponding position in the mixing device is compared with the preset position material deviation threshold value. If the position material deviation value exceeds the preset position material deviation threshold value, it indicates that the material distribution condition of the corresponding position is extremely poor, and the corresponding position is marked as a high material deviation position; if the position material deviation value exceeds the preset position material deviation threshold value, it indicates that the material distribution condition of the corresponding position is poor, and the corresponding position is marked as a low material deviation position;

[0045] If there is no material deviation area or a high material deviation area in the mixing device, an unqualified material distribution signal is generated; if there is a material deviation area but no high material deviation area in the mixing device, the ratio of the number of low material deviation areas to the number of material deviation areas is marked as the mixing distribution coefficient, and the mixing distribution coefficient is numerically compared with the preset mixing distribution coefficient threshold. If the mixing distribution coefficient exceeds the preset mixing distribution coefficient threshold, it indicates that the mixing condition of the mixing operation is poor as a whole, and the distribution of the raw materials in the mixed material is uneven, then an unqualified material distribution signal is generated; if the mixing distribution coefficient does not exceed the preset mixing distribution coefficient threshold, it indicates that the mixing condition of the mixing operation is good as a whole, and the distribution of the raw materials in the mixed material is uniform, then a qualified material distribution signal is generated.

[0046] When the qualified material distribution signal is generated, the uniformly mixed material is filled into the capsule through the filling equipment. The capsule filling supervision module monitors the filling process in real time, generates a qualified filling detection signal or a failed filling detection signal through analysis, and sends the failed filling detection signal to the production early warning module through the server. The production early warning module issues a corresponding early warning when receiving the failed filling detection signal. When the management personnel receive the corresponding early warning, they timely perform corresponding control operations on the filling equipment to ensure the efficient and stable operation of the filling equipment, thereby further ensuring the quality of the produced capsule preparations; the specific operation process of the capsule filling supervision module is as follows:

[0047] Collect environmental information of the operation area of ​​the filling equipment when performing the filling operation, the environmental information including real-time environmental temperature, real-time environmental humidity, environmental dust data and microbial data, wherein the environmental dust data is a data value indicating the dust concentration in the operation area, and the microbial data is a data value indicating the number of microorganisms per unit volume; mark the deviation value between the real-time environmental temperature and the preset suitable environmental temperature standard value for the production of capsule preparations as the production temperature deviation value, and mark the deviation value between the real-time environmental humidity and the preset suitable environmental humidity standard value for the production of capsule preparations as the production humidity deviation value;

[0048] By formula The temperature deviation value TW, the humidity deviation value TS, the environmental dust data TF and the microbial data TP are calculated to obtain the filling ring value TY, wherein fy1, fy2, fy3 and fy4 are preset proportional coefficients, and the values ​​of fy1, fy2, fy3 and fy4 are all greater than zero; and the larger the value of the filling ring value TY, the worse the operating environment of the filling equipment, and the less conducive it is to ensure the quality of the produced capsule preparations. The filling ring value TY is numerically compared with the preset filling ring threshold. If the filling ring value TY exceeds the preset filling ring threshold, it indicates that the operating environment of the filling equipment is poor and needs to be adjusted in time, and a filling detection unqualified signal is generated;

[0049] If the filling ring value TY does not exceed the preset filling ring threshold, the capsule filling efficiency data of the filling equipment within a unit time and the material delivery speed fluctuation value during each capsule filling are collected, wherein the capsule filling efficiency data is a data value indicating the number of capsules produced within a certain period of time; the material delivery speed fluctuation value is a data value indicating the degree of fluctuation of the material output speed when the filling equipment performs capsule filling. The larger the value of the material delivery speed fluctuation value, the more unstable the material output speed of the corresponding filling process is; the mean of all material delivery speed fluctuation values ​​within a unit time is calculated to obtain a filling and conveying evaluation value, the difference between the capsule filling efficiency data and the median of the preset capsule filling efficiency data range is calculated and the absolute value is taken to obtain the capsule filling efficiency difference value;

[0050] By formula The capsule filling efficiency difference value WY and the filling conveying evaluation value WQ are numerically calculated to obtain the capsule filling detection value WF, wherein ew1 and ew2 are preset weight coefficients, ew2>ew1>0; and the larger the value of the capsule filling detection value WF, the worse the operating performance of the filling equipment per unit time; the capsule filling detection value WF is numerically compared with the preset capsule filling detection threshold value, if the capsule filling detection value WF exceeds the preset capsule filling detection threshold value, indicating that the operating performance of the filling equipment per unit time is poor, then a filling detection unqualified signal is generated; if the capsule filling detection value WF does not exceed the preset capsule filling detection threshold value, indicating that the operating performance of the filling equipment per unit time is good, then a filling detection qualified signal is generated.

[0051] Furthermore, the capsule weighing feedback module weighs the produced capsules, marks the corresponding capsules as heavy and inferior capsules or heavy and high-quality capsules based on the weighing information, and sends the capsule weighing detection mark information to the server for storage; specifically: the corresponding capsules are weighed by a weighing device, the weighing mass of the corresponding capsules is obtained and marked as the capsule re-inspection value, the capsule re-inspection value is numerically compared with the preset capsule re-inspection value range, if the capsule re-inspection value is not within the preset capsule re-inspection value range, indicating that the weight of the corresponding capsule does not meet the standard, the corresponding capsule is marked as a heavy and inferior capsule; if the corresponding capsule re-inspection value is within the preset capsule re-inspection value range, indicating that the weight of the corresponding capsule meets the standard, the corresponding capsule is marked as a heavy and high-quality capsule.

[0052] The capsule visual inspection module performs a visual scan on the produced capsules through a visual scanning inspection device, identifies the appearance defects of the capsules based on the visual scanning information, and marks the corresponding capsules as defective capsules or normal capsules accordingly, and sends the visual inspection marking information of the corresponding capsules to the server for storage, specifically: the corresponding capsules are scanned by a visual scanning device to obtain an image of the capsule appearance, and the capsule appearance image is used to determine whether the shape of the capsule is regular, whether the surface is smooth, and whether there are defects such as cracks or bubbles. If the shape of the corresponding capsule is regular, the surface is smooth, and there are no defects such as cracks or bubbles, it indicates that the quality of the corresponding capsule meets the standards, and the corresponding capsule is marked as a normal capsule; if the shape of the corresponding capsule is irregular or the surface is not smooth or there are defects such as cracks or bubbles, it indicates that the quality of the corresponding capsule does not meet the standards, and the corresponding capsule is marked as a defective capsule.

[0053] Embodiment 2: Figure 2As shown, the difference between this embodiment and embodiment 1 is that the server is connected to the production line comprehensive evaluation module in communication, and the production line comprehensive evaluation module is used to set the detection period, preferably, the detection period is ten hours; the number of heavy and inferior capsules and the number of heavy and superior capsules produced by the corresponding production line during the detection period are obtained, and the number of heavy and inferior capsules is calculated by ratio to the number of heavy and superior capsules to obtain the capsule heavy and inferior detection value; and the number of abnormal capsules and the number of normal capsules produced by the corresponding production line during the detection period are obtained, and the number of abnormal capsules is calculated by ratio to the number of normal capsules to obtain the capsule abnormal detection value; the capsule heavy and inferior detection value and the capsule abnormal detection value are numerically compared with the preset capsule heavy and inferior detection threshold and the preset capsule abnormal detection threshold, respectively, if the capsule heavy and inferior detection value or the capsule abnormal detection value exceeds the corresponding preset threshold, it indicates that the quality of the capsules produced by the corresponding production line during the detection period is poor as a whole, and then a production line comprehensive evaluation unqualified signal is generated;

[0054] If both the capsule weight and inferior detection values ​​and the capsule abnormality detection values ​​do not exceed the corresponding preset thresholds, a full-process evaluation and analysis of the production line is conducted, specifically: the ratio of the number of times the corresponding production line generates abnormal mixing detection signals during the production process to the number of times the raw material is mixed is marked as the raw material mixing frequency value, and the ratio of the number of times the material distribution unqualified signals are generated to the number of times the raw material is mixed is marked as the material distribution frequency value; and the ratio of the number of times the filling detection unqualified signals are generated during the production process of the corresponding production line during the detection period to the total operation time of the filling equipment is marked as the capsule filling frequency value;

[0055] The raw material mixing frequency difference value XF, the material distribution frequency difference value XG, the capsule filling frequency difference value XY, the capsule weight and inferiority detection value XW and the capsule storage difference detection value XK are normalized and calculated by the formula XP=a1*XF+a2*XG+a3*XY+(a4*XW+a5*XK) / 2 to obtain the production line traceability evaluation value XP; wherein a1, a2, a3, a4, a5 are preset proportional coefficients, and the values ​​of a1, a2, a3, a4, a5 are all positive numbers; and the larger the value of the production line traceability evaluation value XP is, the worse the production performance of the corresponding production line is;

[0056] The production line traceability evaluation value XP is numerically compared with the preset production line traceability evaluation threshold. If the production line traceability evaluation value XP exceeds the preset production line traceability evaluation threshold, it indicates that the production performance of the corresponding production line is poor, and a production line comprehensive evaluation unqualified signal is generated; if the production line traceability evaluation value XP does not exceed the preset production line traceability evaluation threshold, it indicates that the production performance of the corresponding production line is good, and a production line comprehensive evaluation qualified signal is generated; and the production line comprehensive evaluation unqualified signal is sent to the production early warning module via the server. When the production early warning module receives the production line comprehensive evaluation unqualified signal, it issues a corresponding early warning, so that the management personnel can promptly carry out personnel training and equipment inspection and other measures for the corresponding production line, thereby ensuring the stable and efficient operation of the corresponding production line.

[0057] The working principle of the present invention is as follows: when in use, the operation process of the mixing device is monitored in real time through the raw material preparation and mixing supervision module, and a mixing detection abnormal signal or a mixing detection normal signal is generated through analysis. After the mixing is completed, the material distribution of the mixed material is evaluated and a material distribution qualified signal or a material distribution unqualified signal is generated. When the mixing detection abnormal signal or the material distribution unqualified signal is generated, the production early warning module issues a corresponding early warning, which is convenient for management personnel to grasp the material mixing status in detail and make targeted control measures in time, thereby effectively ensuring the uniformity of material distribution of the produced capsule preparations and significantly improving the quality of the produced capsule preparations; the filling process is monitored in real time through the capsule filling supervision module, and a filling detection qualified signal or a filling detection unqualified signal is generated through analysis. When the filling detection unqualified signal is generated, the production early warning module issues a corresponding early warning. When the management personnel receive the corresponding early warning, they promptly perform corresponding control operations on the filling equipment to ensure the efficient and stable operation of the filling equipment, thereby further ensuring the quality of the produced capsule preparations and effectively reducing the management difficulty of the management personnel.

[0058] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent processing and detection system for capsule preparation production, characterized in that: It includes a server, a raw material preparation and mixing supervision module, a capsule filling supervision module, a capsule weighing feedback module, a capsule visual detection module and a production early warning module; when producing capsule preparations, the raw materials for preparing the capsule preparations are transported to the mixing device in a preset proportion and sequence, the mixing device is operated to make the raw materials evenly distributed, the raw material preparation and mixing supervision module monitors the operation process of the mixing device in real time and generates a mixing detection abnormality signal or a mixing detection normal signal through analysis, and after the mixing is completed, the material distribution of the mixed material is evaluated and a material distribution qualified signal or a material distribution unqualified signal is generated, and the mixing detection abnormality signal and the material distribution unqualified signal are sent to the production early warning module via the server; When a qualified material distribution signal is generated, the uniformly mixed material is filled into the capsule through the filling equipment, the capsule filling supervision module monitors the filling process in real time, generates a qualified filling detection signal or a unqualified filling detection signal through analysis, and sends the unqualified filling detection signal to the production early warning module via the server; the capsule weighing feedback module weighs the produced capsules, marks the corresponding capsules as heavy inferior capsules or heavy superior capsules based on the weighing information, and sends the weighing detection mark information of the capsules to the server for storage; the capsule visual inspection module visually scans the produced capsules, identifies the appearance defects of the capsules based on the visual scanning information, and accordingly marks the corresponding capsules as abnormal capsules or normal capsules, and sends the visual inspection mark information of the corresponding capsules to the server for storage; The specific operation process of the raw material preparation and mixing supervision module includes: During the operation of the mixing device, the rotation speed of the stirring component in the mixing device and the internal temperature of the mixing device are collected, the rotation speed is calculated to be different from the preset target speed and the absolute value is taken to obtain the mixing rotation speed value, and the internal temperature of the mixing device is calculated to be different from the preset target temperature and the absolute value is taken to obtain the mixing temperature value; if the mixing rotation speed value or the mixing temperature value exceeds the corresponding preset threshold value, it is judged that the mixing device is in a high deviation state of operation; The total time that the mixing device is in a high deviation state in a unit time is collected and marked as the total operation error time value, and the maximum single duration of the mixing device in a high deviation state in a unit time is collected and marked as the single operation error time value, and the ratio of the power consumed by the mixing device in a unit time to its average operating power is marked as a mixed consumption ratio value, and the difference between the mixed consumption ratio value and the median of the preset mixed consumption ratio value range is calculated and the absolute value is taken to obtain the mixed consumption detection value; The raw material mixing value YF is obtained by numerically calculating the mixing detection value YR, the total time value of transportation difference YS and the single time value of transportation difference YD through the formula YF=hy1*YR+(hy2*YS+hy3*YD) / hy1, wherein hy1, hy2 and hy3 are preset proportional coefficients, hy1>hy3>hy2>0.26; if the raw material mixing value exceeds the preset raw material mixing threshold, a mixing detection abnormal signal is generated; if the raw material mixing value does not exceed the preset raw material mixing threshold, a mixing detection normal signal is generated.

2. The intelligent processing and detection system for capsule preparation production according to claim 1, characterized in that: The specific operation process of the raw material preparation and mixing supervision module also includes: After the mixing is completed, the materials at several positions in the mixing device are obtained and the components are tested. The percentages of various raw materials in the corresponding positions are obtained through the component testing and marked as the raw material percentage values. The corresponding positions in the mixing device are marked as positions with no material bias, positions with high material bias or positions with low material bias through position material bias assessment and analysis. If there is no material deviation area or a high material deviation area in the mixing device, an unqualified material distribution signal is generated; if there is a material deviation area but no high material deviation area in the mixing device, the ratio of the number of low material deviation areas to the number of material deviation areas is marked as the mixing distribution coefficient, and if the mixing distribution coefficient exceeds the preset mixing distribution coefficient threshold, an unqualified material distribution signal is generated; if the mixing distribution coefficient does not exceed the preset mixing distribution coefficient threshold, a qualified material distribution signal is generated.

3. The intelligent processing and detection system for capsule preparation production according to claim 2, characterized in that: The specific analysis process of the position material deviation assessment analysis is as follows: Compare the raw material percentage values ​​of various raw materials in the corresponding parts with the corresponding preset raw material percentage value ranges one by one. If the raw material percentage values ​​of various raw materials in the corresponding parts are all within the corresponding preset raw material percentage value ranges, the corresponding parts are marked as parts without material deviation; if the raw material percentage value of the corresponding raw material in the corresponding parts is not within the corresponding preset raw material percentage value range, the corresponding raw material is marked as abnormal distribution material, and the deviation value of the raw material percentage value of the corresponding abnormal distribution material compared with the corresponding preset raw material percentage value range is marked as the raw material percentage deviation value; A set of deviation influence values ​​is set in advance for each group of raw materials. The raw material deviation value of the corresponding abnormally distributed material in the corresponding part is multiplied by the matched deviation influence value to obtain the raw material segregation value. The raw material segregation values ​​of all abnormally distributed materials in the corresponding part are summed up to obtain the part material deviation value. If the part material deviation value exceeds the preset part material deviation threshold, the corresponding part is marked as a high material deviation part; if the part material deviation value exceeds the preset part material deviation threshold, the corresponding part is marked as a low material deviation part.

4. The intelligent processing and detection system for capsule preparation production according to claim 1, characterized in that: The specific operation process of the capsule weighing feedback module is as follows: The corresponding capsule is weighed by a weighing device, and the weighed mass of the corresponding capsule is obtained and marked as the capsule re-inspection value. If the capsule re-inspection value is not within the preset capsule re-inspection value range, the corresponding capsule is marked as a heavy and inferior capsule; if the corresponding capsule re-inspection value is within the preset capsule re-inspection value range, the corresponding capsule is marked as a heavy and superior capsule.

5. The intelligent processing and detection system for capsule preparation production according to claim 1, characterized in that: The specific operation process of the capsule visual detection module is as follows: The corresponding capsule is scanned by a visual scanning device to obtain an image of the capsule appearance. The capsule appearance image is used to determine whether the shape of the capsule is regular, the surface is smooth, and whether there are cracks or bubble defects. If the shape of the corresponding capsule is regular, the surface is smooth, and there are no cracks or bubble defects, the corresponding capsule is marked as a normal capsule; if the shape of the corresponding capsule is irregular or the surface is not smooth or there are cracks or bubble defects, the corresponding capsule is marked as an abnormal capsule.

6. The intelligent processing and detection system for capsule preparation production according to claim 1, characterized in that: The specific operation process of the capsule filling supervision module includes: Collect environmental information of the operation area of ​​the filling equipment during the filling operation, including real-time environmental temperature, real-time environmental humidity, environmental dust data and microbial data. Mark the deviation between the real-time environmental temperature and the preset suitable environmental temperature standard value for capsule preparation production as the temperature deviation value. Similarly, obtain the humidity deviation value. Calculate the temperature deviation value, humidity deviation value, environmental dust data and microbial data to obtain the filling ring value. If the filling ring value exceeds the preset filling ring threshold, generate a filling detection unqualified signal. If the filling ring value does not exceed the preset filling ring threshold, the capsule filling efficiency data of the filling equipment within unit time and the material delivery speed fluctuation value during each capsule filling are collected, and the mean of all material delivery speed fluctuation values ​​within unit time is calculated to obtain the filling and conveying evaluation value. The capsule filling efficiency data and the median of the preset capsule filling efficiency data range are differenced and the absolute value is taken to obtain the capsule filling efficiency deviation value; the capsule filling efficiency deviation value and the filling and conveying evaluation value are numerically calculated to obtain the capsule filling detection value. If the capsule filling detection value exceeds the preset capsule filling detection threshold, a filling detection unqualified signal is generated; if the capsule filling detection value does not exceed the preset capsule filling detection threshold, a filling detection qualified signal is generated.

7. The intelligent processing and detection system for capsule preparation production according to claim 1, characterized in that: The server is communicatively connected with the production line comprehensive evaluation module, which is used to set the inspection period, obtain the number of heavy and inferior capsules and the number of heavy and high-quality capsules produced by the corresponding production line during the inspection period, and calculate the ratio of the number of heavy and inferior capsules to the number of heavy and high-quality capsules to obtain the capsule heavy and inferior detection value; and obtain the number of abnormal capsules and the number of normal capsules produced by the corresponding production line during the inspection period, and calculate the ratio of the number of abnormal capsules to the number of normal capsules to obtain the capsule abnormal detection value; if the capsule heavy and inferior detection value or the capsule abnormal detection value exceeds the corresponding preset threshold, a production line comprehensive evaluation unqualified signal is generated; if both the capsule heavy and inferior detection value and the capsule abnormal detection value do not exceed the corresponding preset threshold, a full production line evaluation and analysis is performed.

8. The intelligent processing and detection system for capsule preparation production according to claim 7, characterized in that: The specific analysis process of the full production line evaluation and analysis is as follows: The ratio of the number of times the abnormal mixing detection signal is generated during the production process of the corresponding production line during the detection period to the number of times the raw material is mixed is marked as the raw material mixing frequency difference value, and the ratio of the number of times the material distribution unqualified signal is generated to the number of times the raw material is mixed is marked as the material distribution frequency difference value; And the ratio of the number of times the filling detection unqualified signal is generated in the production process of the corresponding production line during the detection period to the total operation time of the filling equipment is marked as the capsule filling frequency difference value, and the raw material mixing frequency difference value, material distribution frequency difference value, capsule filling frequency difference value, capsule weight and inferior detection value and capsule storage difference detection value are normalized and calculated to obtain the production line traceability evaluation value; if the production line traceability evaluation value exceeds the preset production line traceability evaluation threshold, a production line comprehensive evaluation unqualified signal is generated; If the production line traceability assessment value does not exceed the preset production line traceability assessment threshold, a production line comprehensive assessment qualified signal is generated.

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