CN109711658A - A kind of industrial production optimizing detection system and method - Google Patents
A kind of industrial production optimizing detection system and method Download PDFInfo
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- CN109711658A CN109711658A CN201811333681.8A CN201811333681A CN109711658A CN 109711658 A CN109711658 A CN 109711658A CN 201811333681 A CN201811333681 A CN 201811333681A CN 109711658 A CN109711658 A CN 109711658A
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Abstract
The present invention discloses a kind of industrial production optimizing detection system and method, including data source, data acquisition cleaning unit, big data analysis platform and application platform, the data source enters big data analysis platform after acquiring cleaning unit processing by data, distributed computing storage is carried out to mass data by big data algorithm by big data analysis platform, carries out industrial production management by data of the application platform after transferring optimization processing in big data analysis platform.The present invention is suitable for TB grades of industrial big datas and tests and analyzes use, realizes industrial comprehensive detection, substantially increases inquiry velocity, improve the production efficiency of entire industrial production system；It is good and timeliness is fast for the effect of problem detection in production.
Description
Technical field
The invention belongs to industrial production detection technique fields, more particularly to a kind of industrial production optimizing detection system and side
Method.
Background technique
Each link is likely to generate defect in the industrial production, is not individually present between each manufacturing parameter, past
It is past to influence each other.Growing, perfect with plant produced data, conceptual data amount has reached TB grades.In face of TB rank
Data analysis, traditional data analysing method inquiry velocity is slow, or even can not inquire as a result, directly affecting the effect of bad analysis
Rate.With data acquisition it is improved day by day, seek big data in yield management, quality from data plane by the means of big data
The levels applications such as management become feasible, from the core reasons of data plane analyzing influence yield, excavate influence quality it is crucial because
Element.
Conventional database systems do not support TB grades of industrial data quick search analyses, and valuable data resource does not obtain benefit
With；Production problem is determined by artificial, experience, and often effect is poor, and timeliness is slow, is not able to satisfy the fast development of enterprise；Production hair
Existing problem, can not intuitively position, and searching trouble node, which often consumes, presents as a gift a large amount of financial resources, material resources, time.
Summary of the invention
To solve the above-mentioned problems, the invention proposes a kind of industrial production optimizing detection system and method, are suitable for TB
The industrial big data of grade, which tests and analyzes, to be used, and is realized industrial comprehensive detection, is substantially increased inquiry velocity, improve whole
The production efficiency of a industrial production system；It is good and timeliness is fast for the effect of problem detection in production.
In order to achieve the above objectives, the technical solution adopted by the present invention is that: a kind of industrial production optimizing detection system, including number
Cleaning unit is acquired by data according to source, data acquisition cleaning unit, big data analysis platform and application platform, the data source
Enter big data analysis platform after processing, distributed meter is carried out to mass data by big data algorithm by big data analysis platform
Storage is calculated, carries out industrial production management by data of the application platform after transferring optimization processing in big data analysis platform；
The data source is the initial data in industrial processes；
The data acquire cleaning unit, are acquired cleaning to data source, output big data analysis platform is analyzed
The basic data of processing；
The big data analysis platform, including big data storage computing unit, big data algorithm unit, big data visualization
Unit and resource scheduling management unit；The big data storage computing unit passes through the magnanimity that big data algorithm obtains data source
Data carry out distributed computing and storage, and the big data algorithm unit provides platform big data algorithm, and the big data is visual
Change unit and the data after calculating retrieve and by showing user after visualization processing by engine；The scheduling of resource
Administrative unit realizes the management and running of each unit in big data analysis platform.
The application platform, including process management unit, device management unit and security monitoring unit；The process management
Data that unit transfers that treated from big data analysis platform carry out bad analysis to optimize industrial flow, the equipment pipe
Reason unit transfers that treated from big data analysis platform, and data are monitored equipment state, the security monitoring unit from
Transferring treated in big data analysis platform, data are monitored safely workshop.
Further, the data source includes equipment operating data and operation system data；Not only for detection website
Data, and be associated with creation data, pass through the production residence time or other parameters constitute complete data and analyze ring
Road；The complete set column data generated in industrial processes can be detected.
Further, real by sqoop, kettle and custom script mode in data acquisition cleaning unit
Now to the acquisition of basic data and cleaning；The big data analysis of mass data is carried out convenient for the later period.
Further, the big data analysis platform include big data storage computing unit, it is big data algorithm unit, big
Data visualization unit and resource scheduling management unit；
The big data storage computing unit carries out data with HDFS distributed file system and calculates storage, and uses Hive
Database is as datum number storage according to library；
The big data algorithm unit using CDH big data platform as the basic calculation platform of big data algorithm unit, and
Realize Various types of data analysis and algorithm process logic；
The big data visualization carries out data retrieval, Impala big data by Impala big data analysis engine
Analysis engine determines that bottom stores compressed format using multistage subregion index, and fast by partition data and HDFS block
Size, calculation optimization block size promote memory scan performance；
The resource scheduling management unit carries out the allocation schedule of resource by Yarn resource manager.
Further, the datum number storage of the big data storage computing unit includes distribution type file data according to library
Library, distributed full-text search database, distributed data base and distributed file system, to mass data according to type difference point
It carry out not distributed storage.
Further, being superimposed multi-dimensional data in the big data algorithm unit forms basic data, by individual event
After indicator-specific statistics, each dimension report is assembled；Repeated data handling procedure is reduced to once, operation expanding is convenient for.
In the data statistics that original index item or index item are related to, directly adds index and calculated, encapsulate each layer and refer to
Target calculates, and improves data expanding function；Different dimensions data are set on data subregion；All dimensions are all made of self-propagation
1 int number is calculated, and is directly added and subtracted at several periods before taking current period, and maintenance period length can be greatly simplified
Time and treatment effeciency when subregion.
Further, the application platform includes process management unit, device management unit and security monitoring unit；
The process management unit transfers process data and from big data algorithm by searching for from big data analysis platform
Yield administrative model is transferred in unit, based on machine learning techniques comparative analysis production similar product in different wire bodies, cavity
Bad incidence otherness Deng between, orients the position of bad generation；
The device management unit transfers device data and from big data algorithm by searching for from big data analysis platform
Equipment fault model is transferred in unit, and according to equipment fault model monitoring equipment failure state, equipment fault is monitored；
The security monitoring unit transfers workshop monitoring data and in big data by searching for from big data analysis platform
Security monitoring model is transferred in algorithm unit, by identifying the characteristic of monitoring image, and passes through security monitoring model inspection
Precarious position simultaneously makes warning；By the detection point and detection data that go wrong while showing.
On the other hand, the present invention also provides a kind of industrial production optimizing detection methods, comprising steps of
The initial data in industrial processes is detected as data source；
The data source is acquired cleaning by data acquisition cleaning unit, and output big data analysis platform is analyzed
The basic data of processing；
Computing unit is stored by big data in the big data analysis platform to obtain data source using big data algorithm
The mass data taken carries out distributed computing and storage, provides platform big data algorithm basis by big data algorithm unit, leads to
Excessive data visualization unit retrieves the data after calculating using engine and shows management after carrying out visualization processing
Member；The management and running of each unit in big data analysis platform are realized by resource scheduling management unit；
It is several by the process management unit to transfer that treated from big data analysis platform for platform in the application is flat
According to carrying out bad analysis to optimize industrial flow, the device management unit transfers that treated from big data analysis platform
Data are monitored equipment state, and data that the security monitoring unit transfers that treated from big data analysis platform are to factory
Room is monitored safely.
Further, in the application is flat in platform:
It is searched for from big data analysis platform by the process management unit and transfers process data and from big data algorithm
Yield administrative model is transferred in unit, based on machine learning techniques comparative analysis production similar product in different wire bodies, cavity
Bad incidence otherness Deng between, orients the position of bad generation；By big data analysis find bad because；Improve industry
Business personnel's analysis efficiency is quickly positioned and is solved the problems, such as；Establish dynamic product quality management control；
It is searched for from big data analysis platform by the device management unit and transfers device data and from big data algorithm
Equipment fault model is transferred in unit, and according to equipment fault model monitoring equipment failure state, equipment fault is monitored；
It is searched for from big data analysis platform by the security monitoring unit and transfers workshop monitoring data and from big data
Security monitoring model is transferred in algorithm unit, by identifying the characteristic of monitoring image, and passes through security monitoring model inspection
Precarious position simultaneously makes warning.
Using the technical program the utility model has the advantages that
The present invention is suitable for TB grades of industrial big datas and tests and analyzes, in terms of process management, equipment management and security monitoring
Comprehensive detection is carried out to industrial production, by carrying out distributed storage and retrieval to mass data, substantially increases inquiry speed
Degree, ensure that the working efficiency of application platform optimum management, improves the production efficiency of entire industrial production system；
The present invention can support TB grades of industrial data quick search analyses, be utilized core data resource；For life
The effect of problem detection is good in production and timeliness is fast, is effectively saved a large amount of manpower and material resources, greatly reduces industrial production cost,
It can satisfy the fast development of enterprise.
Detailed description of the invention
Fig. 1 is a kind of structural schematic diagram of industrial production optimizing detection system of the invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention is made into one with reference to the accompanying drawing
Step illustrates.
In the present embodiment, shown in Figure 1, the invention proposes a kind of industrial production optimizing detection systems, including number
Cleaning unit is acquired by data according to source, data acquisition cleaning unit, big data analysis platform and application platform, the data source
Enter big data analysis platform after processing, distributed meter is carried out to mass data by big data algorithm by big data analysis platform
Storage is calculated, carries out industrial production management by data of the application platform after transferring optimization processing in big data analysis platform；
The data source is the initial data in industrial processes；
The data acquire cleaning unit, are acquired cleaning to data source, output big data analysis platform is analyzed
The basic data of processing；
The big data analysis platform, including big data storage computing unit, big data algorithm unit, big data visualization
Unit and resource scheduling management unit；The big data storage computing unit passes through the magnanimity that big data algorithm obtains data source
Data carry out distributed computing and storage, and the big data algorithm unit provides platform big data algorithm basis, the big data
Visualization retrieve and by showing user after visualization processing to the data after calculating by engine；The resource
Management and running unit realizes the management and running of each unit in big data analysis platform；
The application platform, including process management unit, device management unit and security monitoring unit；The process management
Data that unit transfers that treated from big data analysis platform carry out bad analysis to optimize industrial flow, the equipment pipe
Reason unit transfers that treated from big data analysis platform, and data are monitored equipment state, the security monitoring unit from
Transferring treated in big data analysis platform, data are monitored safely workshop.
As the prioritization scheme of above-described embodiment, the data source includes equipment operating data and operation system data；No
It only for the data of detection website, and is associated with creation data, has been made up of production residence time or other parameters
Whole data analyze loop；The complete set column data generated in industrial processes can be detected.
As the prioritization scheme of above-described embodiment, by sqoop, kettle and certainly in data acquisition cleaning unit
Define acquisition and cleaning of the script mode realization to basic data；The big data analysis of mass data is carried out convenient for the later period.
As the prioritization scheme of above-described embodiment, the big data analysis platform includes big data storage computing unit, big
Data algorithm unit, big data visualization and resource scheduling management unit；
The big data storage computing unit carries out data with HDFS distributed file system and calculates storage, and uses Hive
Database is as datum number storage according to library；
The big data algorithm unit using CDH big data platform as the basic calculation platform of big data algorithm unit, and
Realize Various types of data analysis and algorithm process logic；
The big data visualization carries out data retrieval, Impala big data by Impala big data analysis engine
Analysis engine determines that bottom stores compressed format using multistage subregion index, and fast by partition data and HDFS block
Size, calculation optimization block size promote memory scan performance；
The resource scheduling management unit carries out the allocation schedule of resource by Yarn resource manager.
Wherein, the datum number storage of the big data storage computing unit includes distribution type file database, distribution according to library
Formula Full-text database, distributed data base and distributed file system carry out mass data according to type difference respectively
Distributed storage.
It is superimposed multi-dimensional data in the big data algorithm unit and forms basic data, after single index counts,
Assemble each dimension report；Repeated data handling procedure is reduced to once, operation expanding is convenient for.
In the data statistics that original index item or index item are related to, directly adds index and calculated, encapsulate each layer and refer to
Target calculates, and enhances data expanding function；
Different dimensions data are set on data subregion；All dimensions are all made of the int number that self-propagation is 1 and are counted
It calculates, is directly added and subtracted at several periods before taking current period, time when can greatly shorten the long subregion of maintenance period and mentioned
High treatment efficiency.
Such as: in data zoning design, different dimensions data (year, season, the moon, week, day) include day subregion, such as
Year dimension data according to year, day, the moon dimension designed according to the moon, day, the advantages of this design, is: over more new data can be according to day
It updates, updates nearest 10 days or a month data, at the time and raising when can greatly shorten the long subregion of maintenance period
Manage efficiency；
All dimensions are all made of the int number that self-propagation is 1 and are calculated on time dimension, are taking current period former
It when a period, can directly add and subtract, facilitate data query, process is data first to be switched to two fields of a dimension, one is
The name character (, November, 5 weeks in 2017, Q3 season etc.) normally shown, increasing certainly for the anchoring based on some time point
Int type (for example not becoming 2017/2018 year, the moon is 2018*12+5 some months started based on Christian era, is opened for Christian era in season
It is which season begun, all then fixed some day (2017/1/5), calculate current time and all numbers of anchoring time are poor).
As the prioritization scheme of above-described embodiment, the application platform include process management unit, device management unit and
Security monitoring unit；
The process management unit transfers process data and from big data algorithm by searching for from big data analysis platform
Yield administrative model is transferred in unit, based on machine learning techniques comparative analysis production similar product in different wire bodies, cavity
Bad incidence otherness Deng between, orients the position of bad generation；
The device management unit transfers device data and from big data algorithm by searching for from big data analysis platform
Equipment fault model is transferred in unit, and according to equipment fault model monitoring equipment failure state, equipment fault is monitored；
The security monitoring unit transfers workshop monitoring data and from big data by searching for from big data analysis platform
Security monitoring model is transferred in algorithm unit, by identifying the characteristic of monitoring image, and passes through security monitoring model inspection
Precarious position simultaneously makes warning；By the detection point and detection data that go wrong while showing.
For the realization for cooperating the method for the present invention, it is based on identical inventive concept, the present invention also provides a kind of industrial productions
Optimizing detection method, comprising steps of
The initial data in industrial processes is detected as data source；
The data source is acquired cleaning by data acquisition cleaning unit, and output big data analysis platform is analyzed
The basic data of processing；
Computing unit is stored by big data in the big data analysis platform to obtain data source using big data algorithm
The mass data taken carries out distributed computing and storage, provides platform big data algorithm basis by big data algorithm unit, leads to
Excessive data visualization unit retrieves the data after calculating using engine and shows management after carrying out visualization processing
Member；The management and running of each unit in big data analysis platform are realized by resource scheduling management unit；
It is several by the process management unit to transfer that treated from big data analysis platform for platform in the application is flat
According to carrying out bad analysis to optimize industrial flow, the device management unit transfers that treated from big data analysis platform
Data are monitored equipment state, and data that the security monitoring unit transfers that treated from big data analysis platform are to factory
Room is monitored safely.
As the prioritization scheme of above-described embodiment, in the application is flat in platform:
It is searched for from big data analysis platform by the process management unit and transfers process data and from big data algorithm
Yield administrative model is transferred in unit, based on machine learning techniques comparative analysis production similar product in different wire bodies, cavity
Bad incidence otherness Deng between, orients the position of bad generation；By big data algorithm find bad because；Improve industry
Business personnel's analysis efficiency is quickly positioned and is solved the problems, such as；Establish dynamic product quality management control；
It is searched for from big data analysis platform by the device management unit and transfers device data and from big data algorithm
Equipment fault model is transferred in unit, and according to equipment fault model monitoring equipment failure state, equipment fault is monitored；
It is searched for from big data analysis platform by the security monitoring unit and transfers workshop monitoring data and in big data
Security monitoring model is transferred in algorithm unit, by identifying the characteristic of monitoring image, and passes through security monitoring model inspection
Precarious position simultaneously makes warning.
The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the above embodiments and description only describe this
The principle of invention, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its
Equivalent thereof.
Claims (9)
1. a kind of industrial production optimizing detection system, which is characterized in that acquire cleaning unit, big data including data source, data
Analysis platform and application platform, the data source is acquired after cleaning unit is handled by data enters big data analysis platform, by
Big data analysis platform carries out distributed computing storage to mass data by big data algorithm, is divided by application platform from big data
Data after transferring optimization processing in analysis platform carry out industrial production management；
The data source is the initial data in industrial processes；
The data acquire cleaning unit, are acquired cleaning to data source, output big data analysis platform is analyzed and processed
Basic data；
The big data analysis platform, including big data store computing unit, big data algorithm unit, big data visualization
With resource scheduling management unit；The big data storage computing unit passes through the mass data that big data algorithm obtains data source
Distributed computing and storage are carried out, the big data algorithm unit provides platform big data algorithm basis, and the big data is visual
Change unit and the data after calculating retrieve and by showing user after visualization processing by engine；The scheduling of resource
Administrative unit realizes the management and running of each unit in big data analysis platform；
The application platform, including process management unit, device management unit and security monitoring unit；The process management unit
Transferring treated from big data analysis platform, data carry out bad analysis to optimize industrial flow, the equipment management list
Member transfers that treated from big data analysis platform, and data are monitored equipment state, and the security monitoring unit is from big number
According to transferring that treated in analysis platform, data are monitored safely workshop.
2. a kind of industrial production optimizing detection system according to claim 1, which is characterized in that the data source includes setting
Standby operation data and operation system data.
3. a kind of industrial production optimizing detection system according to claim 2, which is characterized in that clear in data acquisition
Wash in unit the acquisition and cleaning realized by sqoop, kettle and custom script mode to basic data.
4. a kind of industrial production optimizing detection system according to claim 3, which is characterized in that the big data analysis is flat
Platform includes big data storage computing unit, big data algorithm unit, big data visualization and resource scheduling management unit；
The big data storage computing unit carries out data with HDFS distributed file system and calculates storage, and uses Hive data
Library is as datum number storage according to library；
The big data algorithm unit is realized using CDH big data platform as the basic calculation platform of big data algorithm unit
Various types of data analysis and algorithm process logic；
The big data visualization carries out data retrieval, Impala big data analysis by Impala big data analysis engine
Engine determines that bottom stores compressed format using multistage subregion index, and passes through partition data and the fast size of HDFS block,
Calculation optimization block size promotes memory scan performance；
The resource scheduling management unit carries out the allocation schedule of resource by Yarn resource manager.
5. a kind of industrial production optimizing detection system according to claim 4, which is characterized in that the big data storage meter
The datum number storage of calculation unit includes distribution type file database, distributed full-text search database, distributed data base according to library
And distributed file system, distributed storage is carried out respectively according to type difference to mass data.
6. a kind of industrial production optimizing detection system according to claim 5, which is characterized in that the big data algorithm list
Member superposition multi-dimensional data composition basic data assembles each dimension report after single index counts；
In the data statistics that original index item or index item are related to, directly adds index and calculated, encapsulate each layer of index
It calculates；Different dimensions data are set on data subregion；All dimensions are all made of the int number that self-propagation is 1 and are calculated,
It is directly added and subtracted when taking several periods before current period.
7. a kind of industrial production optimizing detection system according to claim 6, which is characterized in that the application platform includes
Process management unit, device management unit and security monitoring unit；
The process management unit transfers process data and from big data algorithm unit by searching for from big data analysis platform
In transfer yield administrative model, based on machine learning techniques comparative analysis production similar product between different wire bodies, cavity etc.
Bad incidence otherness, orient the position of bad generation；
The device management unit transfers device data and from big data algorithm unit by searching for from big data analysis platform
In transfer equipment fault model, according to equipment fault model monitoring equipment failure state, equipment fault is monitored；
The security monitoring unit transfers workshop monitoring data and from big data algorithm by searching for from big data analysis platform
Security monitoring model is transferred in unit, by identifying the characteristic of monitoring image, and it is dangerous by security monitoring model inspection
State simultaneously makes warning；By the detection point and detection data that go wrong while showing.
8. a kind of industrial production optimizing detection method, which is characterized in that any proposed industrial production in claim 1-7
Industrial production detection method based on detection system, comprising steps of
The initial data in industrial processes is detected as data source；
The data source is acquired cleaning by data acquisition cleaning unit, and output big data analysis platform is analyzed and processed
Basic data；
Store what computing unit obtained data source using big data algorithm by big data in the big data analysis platform
Mass data carries out distributed computing and storage, platform big data algorithm basis is provided by big data algorithm unit, by big
Data visualization unit retrieves the data after calculating using engine and shows administrator after carrying out visualization processing；It is logical
Cross the management and running that resource scheduling management unit realizes each unit in big data analysis platform；
In the application is flat platform by process management unit data of transferring that treated from big data analysis platform into
The bad analysis of row is to optimize industrial flow, data that the device management unit transfers that treated from big data analysis platform
Equipment state is monitored, the security monitoring unit transfers that treated from big data analysis platform, and data pacify workshop
It is monitored entirely.
9. a kind of industrial production optimizing detection method according to claim 8, which is characterized in that the platform in the application is flat
In:
It is searched for from big data analysis platform by the process management unit and transfers process data and from big data algorithm unit
In transfer yield administrative model, based on machine learning techniques comparative analysis production similar product between different wire bodies, cavity etc.
Bad incidence otherness, orient the position of bad generation；
It is searched for from big data analysis platform by the device management unit and transfers device data and from big data algorithm unit
In transfer equipment fault model, according to equipment fault model monitoring equipment failure state, equipment fault is monitored；
It is searched for from big data analysis platform by the security monitoring unit and transfers workshop monitoring data and from big data algorithm
Security monitoring model is transferred in unit, by identifying the characteristic of monitoring image, and it is dangerous by security monitoring model inspection
State simultaneously makes warning.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111159645A (en) * | 2019-12-19 | 2020-05-15 | 成都数之联科技有限公司 | Bad root cause positioning method based on product production record and parameters |
| CN112288317A (en) * | 2020-11-17 | 2021-01-29 | 北京三维天地科技股份有限公司 | Industrial big data analysis platform and method based on multi-source heterogeneous data governance |
| CN112382375A (en) * | 2020-10-28 | 2021-02-19 | 浙江工业大学 | Hospital doctor seeing process optimization method based on difference detection |
| CN112637572A (en) * | 2021-03-09 | 2021-04-09 | 北京容联易通信息技术有限公司 | Industrial process supervision system based on scene recognition |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104915793A (en) * | 2015-06-30 | 2015-09-16 | 北京西塔网络科技股份有限公司 | Public information intelligent analysis platform based on big data analysis and mining |
| CN107361396A (en) * | 2017-07-10 | 2017-11-21 | 红云红河烟草(集团)有限责任公司 | Tobacco based on big data dries the prediction of silk moisture and control system |
| CN108228830A (en) * | 2018-01-03 | 2018-06-29 | 广东工业大学 | A kind of data processing system |
| CN108470228A (en) * | 2017-02-22 | 2018-08-31 | 国网能源研究院 | Financial data auditing method and audit system |
-
2018
- 2018-11-09 CN CN201811333681.8A patent/CN109711658A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104915793A (en) * | 2015-06-30 | 2015-09-16 | 北京西塔网络科技股份有限公司 | Public information intelligent analysis platform based on big data analysis and mining |
| CN108470228A (en) * | 2017-02-22 | 2018-08-31 | 国网能源研究院 | Financial data auditing method and audit system |
| CN107361396A (en) * | 2017-07-10 | 2017-11-21 | 红云红河烟草(集团)有限责任公司 | Tobacco based on big data dries the prediction of silk moisture and control system |
| CN108228830A (en) * | 2018-01-03 | 2018-06-29 | 广东工业大学 | A kind of data processing system |
Non-Patent Citations (1)
| Title |
|---|
| 冯海杰: "工业大数据背景下的石化企业安全风险评估研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111159645A (en) * | 2019-12-19 | 2020-05-15 | 成都数之联科技有限公司 | Bad root cause positioning method based on product production record and parameters |
| CN111159645B (en) * | 2019-12-19 | 2023-06-06 | 成都数之联科技股份有限公司 | Bad root cause positioning method based on product production histories and parameters |
| CN112382375A (en) * | 2020-10-28 | 2021-02-19 | 浙江工业大学 | Hospital doctor seeing process optimization method based on difference detection |
| CN112288317A (en) * | 2020-11-17 | 2021-01-29 | 北京三维天地科技股份有限公司 | Industrial big data analysis platform and method based on multi-source heterogeneous data governance |
| CN112637572A (en) * | 2021-03-09 | 2021-04-09 | 北京容联易通信息技术有限公司 | Industrial process supervision system based on scene recognition |
| CN112637572B (en) * | 2021-03-09 | 2021-06-18 | 北京容联易通信息技术有限公司 | Industrial process supervision system based on scene recognition |
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