CN107341614A - Based on internet+cane sugar manufacture factory chemical analysis management system - Google Patents
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- 238000004458 analytical method Methods 0.000 title claims abstract description 61
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 42
- 239000000126 substance Substances 0.000 title claims abstract description 37
- CZMRCDWAGMRECN-UGDNZRGBSA-N Sucrose Chemical compound O[C@H]1[C@H](O)[C@@H](CO)O[C@@]1(CO)O[C@@H]1[C@H](O)[C@@H](O)[C@H](O)[C@@H](CO)O1 CZMRCDWAGMRECN-UGDNZRGBSA-N 0.000 title claims abstract description 19
- 229930006000 Sucrose Natural products 0.000 title claims abstract description 19
- 229960004793 sucrose Drugs 0.000 title claims abstract description 16
- 238000007726 management method Methods 0.000 claims abstract description 56
- 238000000034 method Methods 0.000 claims abstract description 34
- 230000008569 process Effects 0.000 claims abstract description 28
- 235000000346 sugar Nutrition 0.000 claims abstract description 26
- 238000003556 assay Methods 0.000 claims abstract description 10
- 238000007619 statistical method Methods 0.000 claims abstract description 7
- 238000004891 communication Methods 0.000 claims abstract description 4
- 238000005516 engineering process Methods 0.000 claims description 14
- 239000003814 drug Substances 0.000 claims description 12
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- 238000001514 detection method Methods 0.000 claims description 7
- 238000012423 maintenance Methods 0.000 claims description 7
- 229940079593 drug Drugs 0.000 claims description 5
- 238000005538 encapsulation Methods 0.000 claims description 5
- 238000011160 research Methods 0.000 claims description 4
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 230000007547 defect Effects 0.000 claims description 3
- 235000021552 granulated sugar Nutrition 0.000 claims description 3
- 230000003862 health status Effects 0.000 claims description 3
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- 238000005065 mining Methods 0.000 claims description 3
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- 230000001360 synchronised effect Effects 0.000 claims 1
- 238000010276 construction Methods 0.000 abstract description 4
- 238000003908 quality control method Methods 0.000 abstract description 2
- 235000011389 fruit/vegetable juice Nutrition 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 2
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- 238000012351 Integrated analysis Methods 0.000 description 1
- 238000010923 batch production Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
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- 230000002950 deficient Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 238000001704 evaporation Methods 0.000 description 1
- 230000008020 evaporation Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
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- 238000009533 lab test Methods 0.000 description 1
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- 230000009897 systematic effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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Abstract
The invention provides it is a kind of based on internet+cane sugar manufacture factory chemical analysis management system, including five assay subsystem, technological check subsystem, statistical analysis of quality subsystem, chemicals management subsystem, analytical equipment management subsystem parts, each subsystem is on cloud host platform using Flex, Hibemate technical operation in high in the clouds, and both-way communication is realized by internet and terminal device, user is serviced accordingly by terminal device through network access using each subsystem.The present invention strengthens the chemical analysis management in sugar manufacturing process by internet correlation technique, improve the effective rate of utilization of process data, pass through big data technical support, system can automatically generate running optimizatin parameter guidance program according to chemical analysis data, promote full factory's quality control system to upgrade, and solution directly perceived and comprehensive is provided for sugar refinery user.And hardware configuration cost of the present invention is low, sugar refinery construction funds invested is greatly reduced.
Description
Technical field
The present invention relates to a kind of sugar refinery chemical analysis management system, it is specifically a kind of based on internet+cane sugar manufacture factory
Chemical analysis management system, belong to factory automation, information system management technical field.
Background technology
During chemical analysis management is carried out, chemical analysis operates artificial amount of calculation in most sugar refinery in China
Greatly, data deficiency is shared between analytical equipment, depth is excavated and is integrated, and calculates and count drawn result, logical using manually sending
Know single mode.Under this traditional mode of operation, the degree of accuracy of the chemical examination result of calculation drawn and efficiency are all very
It is low, it is unfavorable for implementing full factory's unified management and integrated artistic Improvement, brings influence directly to other production managements work, give
Enterprise causes damage.Simultaneously as sugar refinery, generally positioned at remote districts, IT infrastructure is weak, and IT talent is deficient, be in sugar
Server is built in factory, exploitation and maintaining information management system need to put into substantial amounts of man power and material, brought to enterprise heavy
Financial burden.
Therefore, it is intended that build one based on internet+cane sugar manufacture factory chemical analysis management system, pass through interconnection
Net correlation technique strengthens the chemical analysis management in sugar manufacturing process, to effectively improve the effect of sugar refinery chemical analysis management work
Rate, and make full use of the road for starting solution for the industrialization upgrading in sugar refinery, energy-saving and equipment resource.
The content of the invention
It is an object of the invention to provide one based on internet+cane sugar manufacture factory chemical analysis management system, with solve
The chemical analysis operation of current cane sugar manufacture factory is artificial computationally intensive, and data deficiency is shared between analytical equipment, depth is excavated and is integrated,
It is unfavorable for implementing the problem of full factory's unified management is with integrated artistic Improvement.
The concrete technical scheme of the present invention is as follows：
It is a kind of based on internet+cane sugar manufacture factory chemical analysis management system, including assay subsystem, technological check
Five system, statistical analysis of quality subsystem, chemicals management subsystem, analytical equipment management subsystem parts, each subsystem
System uses Flex, Hibemate technical operation in high in the clouds on cloud host platform, and passes through internet and terminal device realization pair
To communication, user is serviced accordingly by terminal device through network access using each subsystem.
The detection of various samples specified in routine analysis project of the assay subsystem to sugar refinery laboratory
Mesh original analysis data is transported to high in the clouds and is calculated and handled, and returns to the final result of sample detection project；Result of calculation
Automatic synchronization generation chemical examination advice note, is sent to production station terminal device by notice forms data in real time；All laboratory analysis of data
Data preservation is carried out using cloud database is stored in.
The technological check subsystem is transported according to the operational factor of each main processes production link in sugar refinery to stable
Row operating mode carries out natural division, forms several operating mode clusters, selects one of operating mode cluster to do specific fuzzy clustering algorithm and grind
Study carefully to obtain a series of Strong association rules, and a series of optimum combination of adjustable parameters is obtained using this rule；Finally counting greatly
According under technical support, the data vouched to each main processes, calculating and analysis are carried out modularized encapsulation in high in the clouds by system,
Make the process of calculation analysis sequencing vouched.
The data that the statistical analysis of quality subsystem stores according to cloud database draw white granulated sugar product quality automatically
The production value of index and technical process important indicator, average value and Dynamic Control Chart, programming count cause White Sugar Quality defect
Factor chart；User by terminal can be to certain time, certain stage all kinds of indexs of technical process, major economic indicators production value
Arbitrarily recall, and show the wave pattern of index automatically.
The chemicals management subsystem includes the stock control of medicine, the management of circulation links of pharmaceutical, medicine use
The management of specification, after the big data technical Analysis of this subsystem application high in the clouds, medical procurement Early-warning Model is established, by current quantity in stock
Compared with default spare part order point, when quantity in stock is had been lowered under reorder level, then stock's automatic early-warning function opens
It is dynamic；System regard each important step of the article in factory's process of circulation as information throughput node, all medicines by the use of technology of Internet of things
Recorded with numbering, actual consumption, consumption node, the multidate information of currency in system and inquiry be provided；System is same
When according to these multidate informations, auxiliary generation procurement plan, instruction, the configured information of dissipation index.
The analytical equipment management subsystem includes the acquisition of device analysis data and shared and equipment state prediction
Two parts, and analysis management is carried out to this two-part multidate information；The analyze data of equipment is obtained with shared i.e. using in factory
The shared data integration completed with versatility to full factory's analytical equipment of analyze data；The prediction of equipment state passes through big data
Technology carries out comprehensive analysis to online monitoring data, device history service data, same category of device statistics, utilizes assessment algorithm
The health status of equipment is assessed, the equipment maintained needs provides reasonable maintaining suggestion and plan, to non-conforming equipment
Provide unqualified reason and maintenance is suggested.
Advantages of the present invention is：
（1）, the speed, precision, the integrality that improve process data processing, improve the effective rate of utilization of process data.
Sucrochemistry analyze data is handled by cloud computing platform completely, has prevented a variety of interference of human factor, has had
Effect improves the processing speed and accuracy of data, and the data provided for production operating personnel and administrative staff are more rapid and accurate
Really.
（2）, running optimizatin parameter guidance side automatically generated according to chemical analysis data by big data technical support, system
Case, full factory's quality control system is promoted to upgrade.
System application big data platform and technology of Internet of things, the chemical analysis data of each link in the production procedure of sugar refinery is entered
Row depth data is excavated, and optimal models is established according to data analysis, obtains exercisable running optimizatin parameter, forms facing to manufacture
Be specifically directed towards row operational order, the past is made into artificial judgment by two-dimensional data table, is changed into using under big data platform
Intelligence decision support system, fundamentally proceeding from the reality, substantially reducing quality of production controlling cycle.
（3）, take suggestion, the operation of guiding, solution directly perceived and comprehensive is provided for sugar refinery user.
Each subsystem uses advanced analysis methodology, big data and machine learning algorithm to high power capacity and high complexity data
Deng analysis technique construction integrated analysis environment, to accelerate advanced analysis modeling and operationalization flow, so as to identify the big number of deep plant
Operable value in, for each rank in sugar refinery and different posies user provide online high-speed decision support with it is difference special
Industry angle solution；And these decision-makings and scheme, propose that there is very high operability with the operational order of phrase formula,
Fully adapt to that batch production is quick, quick environment of operation.
（4）, thin active station and the inexpensive hardware configuration at no data center, substantially reduce sugar refinery construction funds invested.
The server in high in the clouds is the cluster of many high-performance servers, and huge information processing can be carried out to user, and
Result is supplied to client by internet, sugar refinery does not have to buy special server to set up data center.In addition, with it is conventional
Unlike the personal computer for needing the disposal ability of multifunction and height, after cloud, diversified function
With the disposal ability of height, obtained by network from outside, therefore high-performance computer that need not be expensive can be completed
Operation task.
Brief description of the drawings
Fig. 1 be based on internet+cane sugar manufacture factory chemical analysis management system system architecture figure.
Fig. 2 be based on internet+cane sugar manufacture factory chemical analysis management system composition schematic diagram.
Embodiment
The present invention is described further below in conjunction with the accompanying drawings.
As shown in figure 1, the present invention based on internet+cane sugar manufacture factory chemical analysis management system Technical Architecture from
Top to bottm includes user interface layer, key-course, Business Logic and data access layer successively, is connected each other between each layer of system,
And it is incorporated on a multi-tenant software frame.
User interface layer package system interface and user interface, for the display to Business Logic.In this layer, mainly
Developed with Web2.0 technologies, to improve the interactivity at interface and rich.
The traffic control of key-course package system, play link up user interface layer and Business Logic in the entire system
Effect, it is responsible for input of the user on view, and is transmitted to Business Logic and is handled.
Business Logic is the core of whole system, and its main operational logic of package system please for handling user
The data asked.For Business Logic and key-course, realized using Struts and metadata development mode.With Struts technologies
To build basic program frame, the separation of Business Logic and key-course is realized.Describe respectively should in program frame with metadata
With program module, client can have personalized application program by creating and configuring new metadata to customize, so as to reach
To the configurability of software.
Data access layer is independent to the content of data management aspect by Business Logic and key-course, is responsible for data
Conversion between the operation in storehouse, including the management of data structure, data access and physical data structure and logic data structure.Data
Access behavior of the access layer to physical data source has carried out effective encapsulation, either Business Logic, user interface layer still
It key-course, need not all be concerned about the construction and its access mode of data source, the logical data that data access layer returns need to only be carried out
Operation.Data access layer is realized using Hibernate technologies.
As shown in Fig. 2 the present invention based on internet+cane sugar manufacture factory chemical analysis management system include assay
Subsystem, technological check subsystem, statistical analysis of quality subsystem, chemicals management subsystem, analytical equipment management subsystem
Five parts of system, each subsystem uses Flex, Hibemate technical operation in high in the clouds on cloud host platform, and passes through internet
Both-way communication is realized with terminal device, user is serviced accordingly by terminal device through network access using each subsystem.Eventually
End equipment can use computer or mobile terminal.
The detection of various samples specified in routine analysis project of the assay subsystem to sugar refinery laboratory
Mesh original analysis data is transported to high in the clouds and is calculated and handled, and returns to the final result of sample detection project, so can be with
Effectively improve effective rate of utilization of each post of assay to the calculating speed of sample detection project, accuracy rate and data.Meter
Result automatic synchronization generation chemical examination advice note is calculated, notice forms data is sent to production station terminal device in real time, makes production scene
Operating personnel's very first time obtains the result of laboratory test of sample, and production operation is adjusted immediately for there are abnormal conditions, subtracted
Few production loss, so as to improve product quality and productivity effect.All laboratory analysis of data uses are stored in cloud database and entered
Row data preserve, sugar refinery relevant staff can by terminal device whenever and wherever possible, conveniently to laboratory analysis of data
Inquired about and traced, foundation is provided for process technology management.
The technological check subsystem is transported according to the operational factor of each main processes production link in sugar refinery to stable
Row operating mode carries out natural division, forms several operating mode clusters, selects one of operating mode cluster to do specific fuzzy clustering algorithm and grind
Study carefully to obtain a series of Strong association rules, and a series of optimum combination of adjustable parameters is obtained using this rule；Finally counting greatly
According under technical support, the data vouched to each main processes, calculating and analysis are carried out modularized encapsulation in high in the clouds by system,
Make the process of calculation analysis sequencing vouched.
The detailed process of above-mentioned fuzzy clustering algorithm research is：Adjustable parameter data in operating mode cluster are blurred respectively and taken out
As for basic, normal, high three fuzzy concepts, the fuzzy data set formed using the fuzzy membership matrix of all operational factors is base
Plinth, using Mining fuzzy association rules, a series of Strong association rules are obtained under given minimum support and min confidence.
The purpose of technological check is to find production problem crux, realizes the optimum choice of processing parameter, allows production line
Reach optimal operational condition.So that the important step stove drying of sulfitation sugar mill clarifying process neutralizes as an example, the operation of this process
Parameter includes：Intensity of sulfitation, mixed juice flow, a heating-up temperature, pre- grey pH, effective P2O5Amount；System using intensity of sulfitation,
Mixed juice flow to carry out natural division to steady running condition, forms several operating mode clusters, seeks to meet that juice,liming degree will
Best parameter group under each operating mode cluster asked.Specific method is to select one of them to come with intensity of sulfitation, mixed juice flow
The operating mode cluster of division does specific fuzzy clustering algorithm research：By the adjustable parameter data in operating mode cluster：It is heating-up temperature, pre-
Grey pH, effective P2O5Blurring is abstracted as basic, normal, high three fuzzy concepts to amount etc. respectively, with the fuzzy membership of all operational factors
Spend based on the fuzzy data set that matrix is formed, using Mining fuzzy association rules, in given minimum support and minimum confidence
Under degree, a series of Strong association rules are obtained.Obtained using this rule：Under specific intensity of sulfitation, mixed juice flow rate working conditions, bag
Include a heating-up temperature, pre- grey PH, effective P2O5A series of optimum combination of adjustable parameters such as amount.Finally in big data technology branch
Hold down, system will to the dry squeezing of squeezing and it is wet squeeze experiment, evaporation performance is vouched, clarify orthogonal test and to boil sugared sugar producing rate etc. multiple
Data that technical process is vouched, calculating and analysis carry out modularized encapsulation in high in the clouds, make the process of calculation analysis sequencing vouched,
So that require that skill level is high, it is complicated to calculate, the work of cycle length is simplified, beneficial to vouching that work effectively carries out, help
Production technology is improved.
The data that the statistical analysis of quality subsystem stores according to cloud database draw white granulated sugar product quality automatically
The production value of index and technical process important indicator, average value and Dynamic Control Chart, programming count cause White Sugar Quality defect
Factor chart, intuitively to reflect the main and secondary cause of a certain section of time effects product quality.Meanwhile user passes through
Terminal can arbitrarily be recalled to all kinds of indexs of technical process of certain time, certain stage, major economic indicators production value, and shown automatically
The wave pattern of index.This systematic difference contributes to analysis to judge production, abnormal quality state, makes the control afterwards of quality management
It is changed into Prior Control to be possibly realized, promotes quality management efficiency and horizontal raising.
The chemicals management subsystem includes the stock control of medicine, the management of circulation links of pharmaceutical, medicine use
The management of specification.Quantity of drugs that sugar refinery uses is big, type is more, consumption is fast and it is irregular, occupied fund amount is big.It is special according to these
Point, after the big data technical Analysis of this subsystem application high in the clouds, establish medical procurement Early-warning Model, by current quantity in stock with it is default
Spare part order point compares, when quantity in stock is had been lowered under reorder level, then stock's automatic early-warning function on.Stock's pipe
The plan of replenishing is submitted according to early warning situation by reason department, and purchasing department sends order, is so repeated, and property performance period stock mends
Give.In addition, this subsystem by the use of technology of Internet of things using article factory's process of circulation each important step as information throughput node,
All medicines are recorded and provided in system and look into numbering, actual consumption, consumption node, the multidate information of currency
Ask；System generates procurement plan, instruction, the configured information of dissipation index according to these multidate informations, auxiliary simultaneously, so as to
The drug flow time is substantially reduced, avoids the unnecessary consumption of medicine.
The analytical equipment management subsystem includes the acquisition of device analysis data and shared and equipment state prediction
Two parts, and analysis management is carried out to this two-part multidate information.At present, conventional analytical equipment is managed still with account formula pipe
Based on reason, management content mainly includes unit type, value, depreciation, maintenance maintenance record, standby redundancy etc., and these information are only
It is the quiescent conditions for reflecting equipment, and analytical equipment management subsystem is then dynamic to device analysis data, Condition Prediction of Equipment etc.
State information carries out analysis management.The analyze data of equipment obtains utilizes the shared complete with versatility of in-plant assay data with shared
The data integration of full factory analytical equipment in pairs, builds together, to life so as to solve the Data Analysis Model stored up such as more instruments of same type
A series of problems, such as producing the instrument configuration scheme of load variations dynamic response.The prediction of equipment state passes through big data technology pair
Online monitoring data, device history service data, same category of device statistics carry out comprehensive analysis, using assessment algorithm to equipment
Health status assessed, reasonable maintaining suggestion and plan are provided to the equipment maintained of needs, non-conforming equipment is provided not
Qualified reason and maintenance are suggested, so as to greatly reduce the failure of equipment, the maintenance cost of expensive precision instrument in saving.
The present invention in factory without building local data center, while the investment of user and maintenance cost is greatlyd save,
It can freely expand and upward-compatible, realize more factory system group managements.Cross-platform being run with software for system, can be same
When support the mainstream operation system of computer, tablet personal computer and smart mobile phone, it is effective to improve sugar refinery chemical analysis management work
Efficiency.
Claims (3)
1. it is a kind of based on internet+cane sugar manufacture factory chemical analysis management system, it is characterized in that：Including assay subsystem
System, technological check subsystem, statistical analysis of quality subsystem, chemicals management subsystem, analytical equipment management subsystem five
Individual part, each subsystem uses Flex, Hibemate technical operation in high in the clouds on cloud host platform, and passes through internet and end
End equipment realizes both-way communication, and user is serviced accordingly by terminal device through network access using each subsystem；
The detection project of various samples specified in routine analysis project of the assay subsystem to sugar refinery laboratory is former
Beginning analyze data is transported to high in the clouds and is calculated and handled, and returns to the final result of sample detection project；Result of calculation is automatic
Synchronous generation chemical examination advice note, is sent to production station terminal device by notice forms data in real time；All laboratory analysis of data use
It is stored in cloud database and carries out data preservation；
The technological check subsystem is according to the operational factor of each main processes production link in sugar refinery come to stable operation work
Condition carries out natural division, forms several operating mode clusters, selects one of operating mode cluster to do specific fuzzy clustering algorithm research and comes
A series of Strong association rules are obtained, and a series of optimum combination of adjustable parameters is obtained using this rule；Finally in big data skill
Under art is supported, the data vouched to each main processes, calculating and analysis are carried out modularized encapsulation in high in the clouds by system, make to look into
Fixed process of calculation analysis sequencing；
The data that the statistical analysis of quality subsystem stores according to cloud database draw white granulated sugar product quality indicator automatically
With the production value, average value and Dynamic Control Chart of technical process important indicator, programming count cause White Sugar Quality defect because
Sketch map table；User can be any to all kinds of indexs of technical process of certain time, certain stage, major economic indicators production value by terminal
Recall, and show the wave pattern of index automatically；
The chemicals management subsystem includes the stock control of medicine, the management of circulation links of pharmaceutical, medicine operating specification
Management, after the big data technical Analysis of this subsystem application high in the clouds, establish medical procurement Early-warning Model, by current quantity in stock with it is pre-
If spare part order point compare, when quantity in stock is had been lowered under reorder level, then stock's automatic early-warning function on；System
Unite by the use of technology of Internet of things using article factory's process of circulation each important step as information throughput node, all medicines with
Numbering, actual consumption, consumption node, the multidate information of currency record in system and provide inquiry；System while basis
These multidate informations, auxiliary generation procurement plan, instruction, the configured information of dissipation index；
The analytical equipment management subsystem includes the acquisition of device analysis data and shared and equipment state prediction two
Point, and analysis management is carried out to this two-part multidate information；The analyze data of equipment obtains utilizes in-plant assay with shared
The shared data integration completed with versatility to full factory's analytical equipment of data；The prediction of equipment state passes through big data technology
Comprehensive analysis is carried out to online monitoring data, device history service data, same category of device statistics, set using assessment algorithm pair
Standby health status is assessed, and the equipment maintained needs provides reasonable maintaining suggestion and plan, and non-conforming equipment is provided
Unqualified reason and maintenance are suggested.
2. cane sugar manufacture factory chemical analysis management system according to claim 1, it is characterized in that：The technological check subsystem
System fuzzy clustering algorithm research detailed process be：Adjustable parameter data in operating mode cluster are blurred respectively be abstracted as it is low,
Middle and high three fuzzy concepts, based on the fuzzy data set formed by the fuzzy membership matrix of all operational factors, using mould
Association rule mining is pasted, a series of Strong association rules are obtained under given minimum support and min confidence.
3. cane sugar manufacture factory chemical analysis management system according to claim 1, it is characterized in that：Described cane sugar manufacture factory
The Technical Architecture of chemical analysis management system includes user interface layer, key-course, Business Logic and data successively from top to bottom
Access layer, connect each other between each layer of system, and be incorporated on a multi-tenant software frame.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201710555794.1A CN107341614A (en) | 2017-07-10 | 2017-07-10 | Based on internet+cane sugar manufacture factory chemical analysis management system |
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| CN201710555794.1A CN107341614A (en) | 2017-07-10 | 2017-07-10 | Based on internet+cane sugar manufacture factory chemical analysis management system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110412960A (en) * | 2019-08-22 | 2019-11-05 | 广东省生物工程研究所（广州甘蔗糖业研究所） | Into squeezing and wisdom production management method and system are squeezed based on the sugar refinery of cloud computing |
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