CN116224949B - Traditional Chinese medicine formula granule production process data processing system based on artificial intelligence - Google Patents
Traditional Chinese medicine formula granule production process data processing system based on artificial intelligence Download PDFInfo
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- CN116224949B CN116224949B CN202310518704.7A CN202310518704A CN116224949B CN 116224949 B CN116224949 B CN 116224949B CN 202310518704 A CN202310518704 A CN 202310518704A CN 116224949 B CN116224949 B CN 116224949B
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 73
- 238000012545 processing Methods 0.000 title claims abstract description 66
- 239000003814 drug Substances 0.000 title claims abstract description 43
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 18
- 239000008187 granular material Substances 0.000 title claims abstract description 9
- 239000002994 raw material Substances 0.000 claims abstract description 92
- 238000001514 detection method Methods 0.000 claims abstract description 54
- 238000000034 method Methods 0.000 claims abstract description 46
- 239000002245 particle Substances 0.000 claims abstract description 22
- 238000011157 data evaluation Methods 0.000 claims abstract description 14
- 238000012360 testing method Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000013523 data management Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000638 solvent extraction Methods 0.000 description 2
- 239000011800 void material Substances 0.000 description 2
- 235000013361 beverage Nutrition 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000005469 granulation Methods 0.000 description 1
- 230000003179 granulation Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by quality surveillance of production
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention discloses a traditional Chinese medicine formula granule production process data processing system based on artificial intelligence, which relates to the field of pharmaceutical process data processing, and comprises a central control processing unit and a data acquisition unit, wherein the data acquisition unit is used for receiving an instruction sent by the central control processing unit to acquire raw material data, process parameters and finished product quality detection data in the traditional Chinese medicine formula granule production process; a data classification unit; the data evaluation unit is used for evaluating the degree of influence of each technological parameter of the raw materials in the same batch on the processing quality of the product; the automatic generation unit is used for generating a plurality of groups of matched process parameter data during processing of different raw materials; the artificial intelligence-based traditional Chinese medicine formula particle production process data processing system can formulate production process parameters corresponding to the raw material according to the grade of the raw material, is used for guaranteeing the quality of production finished products of raw materials of different grades, and can gradually improve the matched process parameter data during processing of the raw materials of the corresponding grade.
Description
Technical Field
The invention relates to a pharmaceutical process data processing technology, in particular to a traditional Chinese medicine formula particle production process data processing system based on artificial intelligence.
Background
The traditional Chinese medicine formula granule is prepared by extracting and concentrating single traditional Chinese medicine decoction pieces according to the traditional standard, and is used for clinical prescription of traditional Chinese medicine, the single traditional Chinese medicine concentrated granule is called as the single traditional Chinese medicine concentrated granule in China before, and the traditional Chinese medicine decoction pieces, the new decoction pieces, the refined decoction pieces, the beverage type decoction pieces, the scientific traditional Chinese medicine and the like are also called as decoction-free traditional Chinese medicine decoction pieces in China after the traditional Chinese medicine decoction pieces are taken as raw materials, and the traditional Chinese medicine decoction pieces are processed by the production processes of extraction, separation, concentration, drying, granulation, packaging and the like.
The invention discloses a medicine production data management system based on intelligent management in China patent publication No. CN112712262A, which relates to the technical field of medicine production, and comprises an RFID tag, a radio frequency reader, a central controller, a database server, a system setting module, a warehouse unit, a dealer unit and a hospital mechanism unit, wherein the warehouse unit, the dealer unit and the hospital mechanism unit are electrically connected with the central controller;
with respect to the related art in the above, the inventors consider that there are the following drawbacks: more is the data management after the medicine production, is difficult to improve the medicine production technology level and gradually improve the quality of finished products after different grades of raw materials are produced and processed through the data processing of the medicine in the production process, and therefore, the scheme provides a traditional Chinese medicine formula particle production process data processing system based on artificial intelligence.
Disclosure of Invention
The invention aims to provide a traditional Chinese medicine formula particle production process data processing system based on artificial intelligence so as to solve the defects in the prior art.
In order to achieve the above object, the present invention provides the following technical solutions: the data processing system based on artificial intelligence for the production process of the traditional Chinese medicine formula particles comprises a central control processing unit and a data acquisition unit, wherein the data acquisition unit is used for receiving an instruction sent by the central control processing unit to acquire raw material data, process parameters and finished product quality detection data in the production process of the traditional Chinese medicine formula particles;
the data classification unit is connected with the data acquisition unit and is used for classifying each item of data acquired by the data acquisition unit according to batches;
the data evaluation unit is connected with the data classification unit and is used for evaluating the degree of influence of each technological parameter of the raw materials in the same batch on the processing quality of the product;
the automatic generation unit is connected with the data processing unit and is used for generating a plurality of groups of matched process parameter data when different raw materials are processed and transmitting the data to the central control processing unit, the central control processing unit sends an instruction to the production system according to the plurality of groups of process parameter data, and the production system respectively produces according to the plurality of groups of process parameter data;
the test data deriving unit is respectively connected with the data acquisition unit and the central control processing unit, and is used for obtaining a plurality of groups of quality detection data of products produced by the production system according to the data of the automatic generating unit and returning the quality detection data to the central control processing unit;
the feedback unit is used for receiving the instruction of the central control processing unit, comparing the multiple groups of quality detection data in the test data deriving unit and sending the comparison result to the automatic generating unit, and the automatic generating unit synthesizes the comparison result to improve the matched technological parameter data when the corresponding grade raw materials are processed.
Further, the data acquisition unit comprises a raw material data acquisition module, a process parameter acquisition module and a quality detection data acquisition module, wherein the raw material data acquisition module is used for acquiring raw material data grades required by producing traditional Chinese medicine formula particles, and the raw material data grades are divided according to raw material quality.
Further, the process parameter acquisition module is used for acquiring various production process parameters under the corresponding raw materials.
Further, the quality detection data acquisition module is used for acquiring quality detection data of products produced by corresponding production process parameters under corresponding raw materials.
Further, the data classification unit classifies the same batch of data according to the same grade of raw material data, the production process parameters used by the grade of raw material and the quality detection data of the products obtained by the grade of raw material data according to the corresponding production process parameters.
Further, the data evaluation unit sequentially evaluates each process parameter according to different quality detection data obtained by the raw material data under the same grade according to different process parameters, and the influence degree of a specific single process parameter under the same grade on the quality detection single data is obtained.
Further, the automatic generation unit performs comprehensive analysis according to each result obtained in the data evaluation unit, and formulates corresponding production process parameters according to the raw material grade so as to ensure the quality of the finished products produced by the raw materials of different grades.
Further, the quality detection data acquisition module receives instructions of the central control processing unit to acquire a plurality of groups of finished product quality detection data produced by the production system according to a plurality of groups of process parameter data, and sends the plurality of groups of finished product quality detection data to the test data deriving unit.
Further, the feedback unit comprises a comparison module and a comparison algorithm model, the comparison module compares a plurality of groups of finished product quality detection data produced by a plurality of groups of process parameter data according to the comparison algorithm model to obtain single item data dominant items in the quality detection data of each group, and further obtains parameter settings corresponding to the single item data dominant items, and the comparison algorithm model comprises the following operation steps: (1) Solving the minimum value Min of the key codes in the list array and the subscript suf thereof, and counting the number MinNum of the minimum values; (2) placing the minimum value at the split position, i.e., low; (3) determining a segmentation limit of low, high=low+MinNum; (4) Performing one-pass segmentation, and arranging the minimum values with the same numerical value at proper positions; (5) The rest of the values are processed as above until all the values are ordered; the specific algorithm program is as follows:
void DataI ist::QuickSort ()
{ inte, low=0, high=length-1;// determine the range of the quick ordering
Element temp ,Min=list[ow];
while (low<length- 1)
{high=length- 1 ;
The minimum value is initialized and its subscript is recorded
int MinNum=1 ,sufHlow;
Min=list[low];
for (i=low+ 1;i < =high; i++)// find minimum value
{ number of statistical minimums
if(Min.key=: =list[i].key) MinNum++;
if(Min.key>listi].key)
{Min=list[i]; suf=i;MinNum=1;}
}
The minimum value is put to low position
if(suf!=low) {temp=list[suf];
list[suf]=list[ow];list[low]=temp;}
Low++// determine the extent of the division
high=low+MinNum;// one division
while (low < low+MinNum && high <=length- 1)
{while (high<= -length- 1&& listhigh].key >Min.key)
In the sequence of ++high; +/from back to front
if (high > length-1) break;// out of range
while (low<low+MinNum &&
list[ow]key=-Min.key)
++ Low;// sequential front-to-back comparison
Exchange when the condition is met
if( low < low+MinNum && high<=length- 1)
{temp=list[low];list[low]=list[high];
list[high]=temp;low++;high++;}
One-time partitioning by }// while
The value of/(Low is Low+MinNum, and the front subinterval and the rear subinterval are obtained
In which list [ low ] -list [ ow+MinNum ] is ordered
The// list [ low+MinNum+1] -list [ length-1 ] is to be ranked.
Further, the automatic generation unit combines the parameter settings corresponding to the single item data advantage items obtained by the feedback unit, and improves the matched technological parameter data in the processing of the corresponding grade raw materials.
Compared with the prior art, the data processing system for the production process of the traditional Chinese medicine formula particles based on artificial intelligence can process raw material data, process parameters and quality detection data in the production of the traditional Chinese medicine formula particles, and the production process parameters corresponding to the raw material data can be formulated according to the grade of the raw material so as to ensure the quality of the finished products produced by the raw materials of different grades, and the matched process parameter data in the processing of the raw materials of the corresponding grades can be gradually improved, so that the quality of the finished products produced and processed by the raw materials of different grades is further gradually improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a schematic block diagram of a data processing system for an artificial intelligence based production process of traditional Chinese medicine formula particles according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a data acquisition unit according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a feedback unit according to an embodiment of the present invention.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the present invention will be further described in detail with reference to the accompanying drawings.
Referring to fig. 1-3, an artificial intelligence-based traditional Chinese medicine formula particle production process data processing system comprises a central control processing unit, a data acquisition unit, a processing parameter and a quality detection data, wherein the data acquisition unit is used for receiving an instruction sent by the central control processing unit to acquire raw material data, processing parameters and quality detection data of a traditional Chinese medicine formula particle production process, the data acquisition unit comprises a raw material data acquisition module, a processing parameter acquisition module and a quality detection data acquisition module, the raw material data acquisition module is used for acquiring raw material data grades required by producing traditional Chinese medicine formula particles, the raw material data grades are divided according to raw material quality, the processing parameter acquisition module is used for acquiring production process parameters under corresponding raw materials, the quality detection data acquisition module is used for acquiring product quality detection data produced by using corresponding production process parameters under corresponding raw materials, the raw material data are detected by a related instrument, raw material grades are divided according to quality, corresponding process parameters are set for producing traditional Chinese medicine formula particles according to corresponding raw material grades, in order to improve product production quality in an actual production process, the data acquisition unit can acquire raw material data of various grades, a plurality of process parameters corresponding to the raw material data of each grade and corresponding product quality detection data under the corresponding to the raw material grade;
the data classification unit is connected with the data acquisition unit and is used for classifying all data acquired by the data acquisition unit according to batches, and the data classification unit classifies the same batch of data by using the same grade of raw material data, the production process parameters used by the grade of raw material and the product quality detection data obtained by the grade of raw material data according to the corresponding production process parameters;
the data evaluation unit is connected with the data classification unit and is used for evaluating the degree of influence of each technological parameter of the raw materials in the same batch on the processing quality of the product, and sequentially evaluates each technological parameter according to different quality detection data obtained by the raw material data in the same grade according to different technological parameters to obtain the influence degree of a specific single technological parameter on the quality detection single data in the same grade, wherein the influence degree is particularly represented by the influence degree of the adjustment of a certain technological parameter of the raw materials in a certain grade on a certain numerical value of the product quality during production;
the automatic generation unit is connected with the data processing unit and is used for generating a plurality of groups of matched process parameter data when different raw materials are processed, the automatic generation unit carries out comprehensive analysis according to each result obtained in the data evaluation unit, and formulates corresponding production process parameters according to the raw material grades so as to ensure the quality of finished products produced by different grades of raw materials, the automatic generation unit analyzes the result obtained by the data evaluation unit based on the deep neural network, the specific performance is that the production quality of the grade of raw materials is higher when the process parameter set value of a certain grade of raw materials is produced, a plurality of groups of process parameter data corresponding to the grade of raw materials are matched, the data are transmitted to the central control processing unit, and the central control processing unit sends instructions to the production system according to the plurality of groups of process parameter data, and the production system respectively carries out production according to the plurality of groups of process parameter data;
the test data acquisition module is used for receiving an instruction of the central control processing unit to acquire a plurality of groups of finished product quality detection data produced by the production system according to the plurality of groups of process parameter data and sending the acquired plurality of groups of finished product quality detection data to the test data output unit, and the feedback unit is used for receiving the instruction of the central control processing unit and comparing the plurality of groups of quality detection data in the test data output unit;
the feedback unit is used for receiving instructions of the central control processing unit, comparing a plurality of groups of quality detection data in the test data deriving unit, sending a comparison result to the automatic generating unit, integrating the comparison result by the automatic generating unit to improve the matched process parameter data in the process of processing the corresponding grade raw materials, wherein the feedback unit comprises a comparison module and a comparison algorithm model, the comparison module compares the plurality of groups of finished product quality detection data produced by the plurality of groups of process parameter data according to the comparison algorithm model to obtain single item data dominant items in the quality detection data of each group, further obtaining parameter settings corresponding to the single item data dominant items, combining the parameter settings corresponding to the single item data dominant items obtained by the feedback unit by the automatic generating unit, improving the matched process parameter data in the process of processing the corresponding grade raw materials, and the operation steps of the comparison algorithm model are as follows: (1) Solving the minimum value Min of the key codes in the list array and the subscript suf thereof, and counting the number MinNum of the minimum values; (2) placing the minimum value at the split position, i.e., low; (3) determining a segmentation limit of low, high=low+MinNum; (4) Performing one-pass segmentation, and arranging the minimum values with the same numerical value at proper positions; (5) The rest of the values are processed as above until all the values are ordered; the specific algorithm program is as follows:
void DataI ist::QuickSort ()
{ inte, low=0, high=length-1;// determine the range of the quick ordering
Element temp ,Min=list[ow];
while (low<length- 1)
{high=length- 1 ;
The minimum value is initialized and its subscript is recorded
int MinNum=1 ,sufHlow;
Min=list[low];
for (i=low+ 1;i < =high; i++)// find minimum value
{ number of statistical minimums
if(Min.key=: =list[i].key) MinNum++;
if(Min.key>listi].key)
{Min=list[i]; suf=i;MinNum=1;}
}
The minimum value is put to low position
if(suf!=low) {temp=list[suf];
list[suf]=list[ow];list[low]=temp;}
Low++// determine the extent of the division
high=low+MinNum;// one division
while (low < low+MinNum && high <=length- 1)
{while (high<= -length- 1&& listhigh].key >Min.key)
In the sequence of ++high; +/from back to front
if (high > length-1) break;// out of range
while (low<low+MinNum &&
list[ow]key=-Min.key)
++ Low;// sequential front-to-back comparison
Exchange when the condition is met
if( low < low+MinNum && high<=length- 1)
{temp=list[low];list[low]=list[high];
list[high]=temp;low++;high++;}
One-time partitioning by }// while
The value of/(Low is Low+MinNum, and the front subinterval and the rear subinterval are obtained
In which list [ low ] -list [ ow+MinNum ] is ordered
The// list [ low+MinNum+1] -list [ length-1 ] is to be ranked.
Working principle: when in use, the central control processing unit sends out a data acquisition instruction from the data acquisition unit, the raw material data acquisition module in the data acquisition unit acquires the raw material data grade required by producing the traditional Chinese medicine formula particles, the process parameter acquisition module acquires all production process parameters under corresponding raw materials, the quality detection data acquisition module acquires the product quality detection data produced under corresponding raw materials by using corresponding production process parameters, then the data acquisition unit sends all the data to the data classification unit for arrangement, the data classification unit classifies the raw material data of the same grade, the production process parameters used by the raw material of the same grade and the product quality detection data obtained by the raw material data of the same grade according to the corresponding production process parameters to obtain a plurality of groups of data, the data classification unit sends the obtained plurality of groups of data to the data evaluation unit, the data evaluation unit sequentially evaluates each technological parameter according to different quality detection data obtained by different technological parameters according to raw material data under the same grade to obtain the influence degree of a specific single technological parameter under the same grade on the quality detection single data, wherein the specific influence degree is represented by the influence degree of the adjustment of the technological parameter of a raw material of a certain grade on a certain numerical value of the product quality during production, the data evaluation unit sends the obtained data to the automatic generation unit, the automatic generation unit analyzes the result obtained by the data evaluation unit based on the deep neural network, and prepares production technological parameters corresponding to the data according to the grade of the raw material to ensure the quality of the production finished products of the raw materials of different grades, the specific technological parameter setting value of the raw material of a certain grade is higher in the production quality of the raw material of the grade during production, and the feedback unit receives the instructions of the central control processing unit, compares the multiple groups of quality detection data in the test data deriving unit, and the comparison module in the feedback unit compares the multiple groups of quality detection data produced by the multiple groups of process parameter data according to the comparison algorithm model to obtain single item data dominant items in the quality detection data, further obtains parameter settings corresponding to the single item data dominant items, and sends the parameter settings to the automatic generation unit.
While certain exemplary embodiments of the present invention have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the invention, which is defined by the appended claims.
Claims (10)
1. The data processing system for the traditional Chinese medicine formula particle production process based on artificial intelligence comprises a central control processing unit and is characterized by further comprising a data acquisition unit, wherein the data acquisition unit is used for receiving an instruction sent by the central control processing unit to acquire raw material data, process parameters and finished product quality detection data of the traditional Chinese medicine formula particle production process;
the data classification unit is connected with the data acquisition unit and is used for classifying each item of data acquired by the data acquisition unit according to batches;
the data evaluation unit is connected with the data classification unit and is used for evaluating the degree of influence of each technological parameter of the raw materials in the same batch on the processing quality of the product;
the automatic generation unit is connected with the data processing unit and is used for generating a plurality of groups of matched process parameter data when different raw materials are processed and transmitting the data to the central control processing unit, the central control processing unit sends an instruction to the production system according to the plurality of groups of process parameter data, and the production system respectively produces according to the plurality of groups of process parameter data;
the test data deriving unit is respectively connected with the data acquisition unit and the central control processing unit, and is used for obtaining a plurality of groups of quality detection data of products produced by the production system according to the data of the automatic generating unit and returning the quality detection data to the central control processing unit;
the feedback unit is used for receiving the instruction of the central control processing unit, comparing the multiple groups of quality detection data in the test data deriving unit and sending the comparison result to the automatic generating unit, and the automatic generating unit synthesizes the comparison result to improve the matched technological parameter data when the corresponding grade raw materials are processed.
2. The system of claim 1, wherein the data acquisition unit comprises a raw material data acquisition module, a process parameter acquisition module and a quality detection data acquisition module, wherein the raw material data acquisition module is used for acquiring raw material data grades required for producing the traditional Chinese medicine formula particles, and the raw material data grades are divided according to raw material quality.
3. The artificial intelligence-based traditional Chinese medicine formula granule production process data processing system according to claim 2, wherein the process parameter acquisition module is used for acquiring various production process parameters under corresponding raw materials.
4. The system of claim 2, wherein the quality detection data acquisition module is configured to acquire quality detection data of a product produced by using corresponding production process parameters under corresponding raw materials.
5. The system for processing data of the production process of the traditional Chinese medicine formula particles based on artificial intelligence according to claim 1, wherein the data classification unit classifies the same batch of data according to the same grade of raw material data, the production process parameters used by the grade of raw material and the quality detection data of the grade of raw material obtained according to the corresponding production process parameters.
6. The artificial intelligence-based traditional Chinese medicine formula particle production process data processing system according to claim 1, wherein the data evaluation unit sequentially evaluates each process parameter according to different quality detection data obtained by raw material data under the same grade according to different process parameters to obtain the influence degree of a specific single process parameter under the same grade on quality detection single data.
7. The artificial intelligence-based traditional Chinese medicine formula granule production process data processing system according to claim 1, wherein the automatic generation unit performs comprehensive analysis according to each result obtained in the data evaluation unit, and formulates corresponding production process parameters according to the raw material grade so as to ensure the quality of the production finished products of different grades of raw materials.
8. The system according to claim 1, wherein the quality detection data acquisition module receives instructions from the central control processing unit to acquire a plurality of sets of quality detection data of the finished product produced by the production system according to the plurality of sets of process parameter data, and sends the data to the test data deriving unit.
9. The system for processing data in the production process of traditional Chinese medicine formula particles based on artificial intelligence according to claim 1, wherein the feedback unit comprises a comparison module and a comparison algorithm model, the comparison module compares a plurality of groups of finished product quality detection data produced by a plurality of groups of process parameter data according to the comparison algorithm model to obtain single item data dominant items in each group of composition quality detection data, and further obtains parameter settings corresponding to the single item data dominant items.
10. The system for processing data in the production process of traditional Chinese medicine formula particles based on artificial intelligence according to claim 1, wherein the automatic generation unit combines parameter settings corresponding to single data advantage items obtained by the feedback unit, and improves matched process parameter data in processing of corresponding grade raw materials.
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| CN106371409A (en) * | 2016-08-27 | 2017-02-01 | 绍兴兴明染整有限公司 | Dyeing and finishing production line management system and management method |
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| CN101840530A (en) * | 2008-10-09 | 2010-09-22 | 北京农业信息技术研究中心 | Management method and system of farming information collection and safe production of fruit-and-vegetable agricultural products |
| CN107219779A (en) * | 2016-03-22 | 2017-09-29 | 周楠 | The addition method and device of a kind of water treatment agent |
| CN112163688A (en) * | 2019-08-16 | 2021-01-01 | 重庆华森制药股份有限公司 | Full-flow intelligent manufacturing system for multi-dosage form Chinese and western medicine products and construction method |
| CN112712262A (en) * | 2020-12-31 | 2021-04-27 | 广东飞企互联科技股份有限公司 | Drug production data management system based on intelligent management |
| CN112859778A (en) * | 2021-01-06 | 2021-05-28 | 辽宁华润本溪三药有限公司 | Quality management method and system for traditional Chinese medicine production process |
| KR102343059B1 (en) * | 2021-08-05 | 2021-12-27 | 주식회사 인피닉 | Data collecting system for artificial intelligence machine learning, and device therefor |
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