CN110376972A - Hadoop+Spring framework method for MES system - Google Patents
Hadoop+Spring framework method for MES system Download PDFInfo
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- CN110376972A CN110376972A CN201810325031.2A CN201810325031A CN110376972A CN 110376972 A CN110376972 A CN 110376972A CN 201810325031 A CN201810325031 A CN 201810325031A CN 110376972 A CN110376972 A CN 110376972A
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- 238000000034 method Methods 0.000 title claims abstract description 18
- 230000000007 visual effect Effects 0.000 claims abstract description 8
- 238000004519 manufacturing process Methods 0.000 abstract description 18
- 238000007726 management method Methods 0.000 description 17
- 238000010586 diagram Methods 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 4
- 235000013399 edible fruits Nutrition 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
Classifications
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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]
- G05B19/41885—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 modeling, simulation of the manufacturing system
-
- 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
- G05B2219/32339—Object oriented modeling, design, analysis, implementation, simulation language
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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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- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- General Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- General Factory Administration (AREA)
Abstract
The invention discloses a kind of Hadoop+Spring framework methods for MES system.Method includes the following steps: step 1, workshop sensors for data, are transferred to data center, stored by big data platform；Step 2, sensing data is stored in relational database by data center；Step 3, MES system obtains data from big data platform, carries out real-time visual displaying；Step 4, data processing request is sent big data platform, big data platform returned data processing result by MES system；Step 5, the part B/S framework MES handles traditional MES system demand, and the data in step 3~4 carry out the real-time visual of sensor big data.The present invention combines the MES of the B/S framework of high efficient and flexible with the big quantity sensor in workshop, so that production management system has the processing capacity to mass data.
Description
Technical field
The present invention relates to shop floor production control technical field, especially a kind of Hadoop+Spring frame for MES system
Structure method.
Background technique
MES (Manufacturing Execution System) i.e. manufacturing enterprise's production process executes system, is a set of
The production information management system of Manufacture Enterprise workshop execution level can be provided for enterprise including Manufacturing Data Management, meter
Draw scheduling management, Production scheduling management, stock control, quality management, human resource management, work centre/equipment management, project
The management modules such as kanban system, production process control.But current MES both domestic and external not yet has to the big of workshop sensor acquisition
Data carry out handling the ability with analysis in real time.
Summary of the invention
The purpose of the present invention is to provide a kind of Hadoop+Spring framework methods for MES system, by high efficient and flexible
The MES of B/S framework combined with the big quantity sensor in workshop, enable production management system to have the processing to mass data
Power.
The technical solution for realizing the aim of the invention is as follows: a kind of framework side Hadoop+Spring for MES system
Method, comprising the following steps:
Step 1, workshop sensors for data is transferred to data center, is stored by big data platform；
Step 2, sensing data is stored in relational database by data center；
Step 3, MES system obtains data from big data platform, carries out real-time visual displaying；
Step 4, data processing request is sent big data platform, big data platform returned data processing knot by MES system
Fruit；
Step 5, the part B/S framework MES handles traditional MES system demand, and the data in step 3~4 carry out sensor
The real-time visual of big data.
Further, big data platform described in step 1 includes MES based on Spring frame, workshop appliance management
System and big data system based on Hadoop.
Further, web access task is undertaken by local server, and the storage of big data is with calculating by based on Hadoop's
The processing of big data system；And workshop need to only install corresponding sensor, billboard and be responsible for uploading the server of data.
Compared with prior art, the present invention its remarkable advantage are as follows: (1) by the MES system of B/S framework and Hadoop big data
Platform docking, realizes the real-time processing of workshop big data；(2) workshop need to only install corresponding sensor, billboard and on being responsible for
The server of data is passed, calculating pressure is lower, so that production management system has the processing capacity to mass data.
The real-time processing and analysis ability for having the mass data obtained to workshop sensor.
Detailed description of the invention
Fig. 1 is distributed storage network architecture diagram of the invention.
Fig. 2 is big data business process flow diagram in the present invention.
Fig. 3 is the MVC structure chart of MES system in the present invention.
Fig. 4 is the architecture diagram after integrating in the present invention.
Fig. 5 is functional block diagram of the present invention for the Hadoop+Spring framework method of MES system.
Specific embodiment
This system is based on Spring and Hadoop big data platform designs, and is intended for the realization of MES system.This platform is main
It is made of three sets of systems, based on the MES of Spring frame, workshop appliance management system, and the big data system based on Hadoop
System.
Main development target is the MES system for realizing a high efficient and flexible, and collects pairs of workshop on this basis and largely pass
The big data system that the mass data that sensor generates is stored and analyzed.
Fig. 1 is global distributed storage network framework, and the daily web access task of this system is undertaken by local server,
The storage of big data is handled with calculating by the big data system based on Hadoop；And workshop need to only install corresponding sensor, see
It is lower to calculate pressure for plate and the server for being responsible for upload data.Fig. 2 is big data business process flow, and Fig. 3 is MVC structure chart.
For the business characteristic of this system, Web needs to access and requests Hadoop big data platform to the sea of Workshop Production
Measure the data of data processing, it is therefore desirable to Spring frame be integrated with Hadoop, be the software architecture after integration below
Figure: Fig. 4 is the architecture diagram after integration, specific as follows:
1, comprising modules
1) workshop appliance system:
Workshop appliance is managed, is responsible for data acquisition transmission and is shown with workshop billboard.
2) data processing system:
Including big data platform and traditional relational, it is responsible for real time access and the analysis of production line data.
3) production line manufacture execution system:
It receives lower data and realizes production report work, planning management, quality management, material response, endowed management, equipment pipe
The system functions such as reason, handling of goods and materials, process management.
4) big data analysis system:
It is combined with the big data platform in data processing system, it is big using deep learning, analysis assessment, artificial intelligence etc.
Data mining technology finds and grasps production law, realizes that equipment fault prediction, Real-time process scheduling, employee's operation behavior chase after
It the functions such as traces back.
Fig. 5 is functional block diagram of the present invention for the Hadoop+Spring framework method of MES system, for MES system
Hadoop+Spring framework method, comprising the following steps:
Step 1, workshop sensors for data is transferred to data center, is stored by big data platform；
Step 2, sensing data is stored in relational database by data center；
Step 3, MES system obtains data from big data platform, carries out real-time visual displaying；
Step 4, data processing request is sent big data platform, big data platform returned data processing knot by MES system
Fruit；
Step 5, the part B/S framework MES handles traditional MES system demand, and the data in step 3~4 carry out sensor
The real-time visual of big data.
Further, big data platform described in step 1 includes MES based on Spring frame, workshop appliance management
System and big data system based on Hadoop.
Further, web access task is undertaken by local server, and the storage of big data is with calculating by based on Hadoop's
The processing of big data system；And workshop need to only install corresponding sensor, billboard and be responsible for uploading the server of data.
The present invention docks the MES system of B/S framework with Hadoop big data platform, realizes the real-time of workshop big data
Processing；Workshop need to only install corresponding sensor, billboard and the server for being responsible for upload data, and calculating pressure is lower, so that raw
It produces management system and has the processing capacity to mass data.
Claims (3)
1. a kind of Hadoop+Spring framework method for MES system, which comprises the following steps:
Step 1, workshop sensors for data is transferred to data center, is stored by big data platform；
Step 2, sensing data is stored in relational database by data center；
Step 3, MES system obtains data from big data platform, carries out real-time visual displaying；
Step 4, data processing request is sent big data platform, big data platform returned data processing result by MES system；
Step 5, the part B/S framework MES handles traditional MES system demand, and the data in step 3~4 carry out the big number of sensor
According to real-time visual.
2. being used for the Hadoop+Spring framework method of MES system according to claim 1, which is characterized in that in step 1
The big data platform includes MES, workshop appliance management system and the big number based on Hadoop based on Spring frame
According to system.
3. being used for the Hadoop+Spring framework method of MES system according to claim 1, which is characterized in that web access
Task is undertaken by local server, and the storage of big data is handled with calculating by the big data system based on Hadoop；And workshop is only
Corresponding sensor, billboard need to be installed and are responsible for uploading the server of data.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810325031.2A CN110376972A (en) | 2018-04-12 | 2018-04-12 | Hadoop+Spring framework method for MES system |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810325031.2A CN110376972A (en) | 2018-04-12 | 2018-04-12 | Hadoop+Spring framework method for MES system |
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| CN110376972A true CN110376972A (en) | 2019-10-25 |
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| CN201810325031.2A Pending CN110376972A (en) | 2018-04-12 | 2018-04-12 | Hadoop+Spring framework method for MES system |
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Citations (6)
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|---|---|---|---|---|
| CN104808639A (en) * | 2015-04-29 | 2015-07-29 | 中国石油大学(华东) | Pharmaceutical product manufacturing execution system and method |
| CN104898608A (en) * | 2015-04-10 | 2015-09-09 | 南京理工大学 | Hadoop-based crop growth monitoring cloud platform and realization method thereof |
| CN105045856A (en) * | 2015-07-09 | 2015-11-11 | 中国资源卫星应用中心 | Hadoop-based data processing system for big-data remote sensing satellite |
| CN105467946A (en) * | 2015-02-05 | 2016-04-06 | 贵阳铝镁设计研究院有限公司 | Aluminum electrolytic MES system based on accurate perception and intelligent decision |
| KR20170099078A (en) * | 2016-02-23 | 2017-08-31 | 주식회사 와이티 | Management Estimating Platform System Based on Big Data Using Manufacturing Facilities-Related Information from MES |
| CN107168263A (en) * | 2017-06-16 | 2017-09-15 | 江南大学 | A kind of knitting MES Production-Plan and scheduling methods excavated based on big data |
-
2018
- 2018-04-12 CN CN201810325031.2A patent/CN110376972A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105467946A (en) * | 2015-02-05 | 2016-04-06 | 贵阳铝镁设计研究院有限公司 | Aluminum electrolytic MES system based on accurate perception and intelligent decision |
| CN104898608A (en) * | 2015-04-10 | 2015-09-09 | 南京理工大学 | Hadoop-based crop growth monitoring cloud platform and realization method thereof |
| CN104808639A (en) * | 2015-04-29 | 2015-07-29 | 中国石油大学(华东) | Pharmaceutical product manufacturing execution system and method |
| CN105045856A (en) * | 2015-07-09 | 2015-11-11 | 中国资源卫星应用中心 | Hadoop-based data processing system for big-data remote sensing satellite |
| KR20170099078A (en) * | 2016-02-23 | 2017-08-31 | 주식회사 와이티 | Management Estimating Platform System Based on Big Data Using Manufacturing Facilities-Related Information from MES |
| CN107168263A (en) * | 2017-06-16 | 2017-09-15 | 江南大学 | A kind of knitting MES Production-Plan and scheduling methods excavated based on big data |
Non-Patent Citations (2)
| Title |
|---|
| 段胜泽: "基于Hadoop的线缆生产的大数据服务平台的设计与实现", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
| 郝昕等: "海量MES监控数据的高效存储与处理", 《科技创新与应用》 * |
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Application publication date: 20191025 |