CN108241343A - A kind of intelligent plant management platform system - Google Patents
A kind of intelligent plant management platform system Download PDFInfo
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- CN108241343A CN108241343A CN201611209946.4A CN201611209946A CN108241343A CN 108241343 A CN108241343 A CN 108241343A CN 201611209946 A CN201611209946 A CN 201611209946A CN 108241343 A CN108241343 A CN 108241343A
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- 238000007726 management method Methods 0.000 claims abstract description 67
- 238000004519 manufacturing process Methods 0.000 claims abstract description 53
- 230000003862 health status Effects 0.000 claims abstract description 27
- 238000012423 maintenance Methods 0.000 claims abstract description 27
- 238000004458 analytical method Methods 0.000 claims abstract description 23
- 238000012544 monitoring process Methods 0.000 claims abstract description 21
- 238000007405 data analysis Methods 0.000 claims abstract description 11
- 230000003993 interaction Effects 0.000 claims abstract description 3
- 230000036541 health Effects 0.000 claims description 28
- 238000003745 diagnosis Methods 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 8
- 230000007423 decrease Effects 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 5
- 238000004891 communication Methods 0.000 claims description 4
- 238000002405 diagnostic procedure Methods 0.000 claims description 4
- 230000008439 repair process Effects 0.000 claims description 4
- 238000013068 supply chain management Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 2
- 230000002452 interceptive effect Effects 0.000 claims description 2
- 238000011156 evaluation Methods 0.000 claims 1
- 238000004445 quantitative analysis Methods 0.000 abstract description 2
- 238000000034 method Methods 0.000 description 8
- 238000005299 abrasion Methods 0.000 description 5
- 238000005457 optimization Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 4
- 238000005265 energy consumption Methods 0.000 description 3
- 239000000284 extract Substances 0.000 description 3
- 230000006855 networking Effects 0.000 description 3
- 238000012800 visualization Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000006731 degradation reaction Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 206010054949 Metaplasia Diseases 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 239000002826 coolant Substances 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 238000013399 early diagnosis Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000001050 lubricating effect Effects 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 230000015689 metaplastic ossification Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000009467 reduction Effects 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]
- G05B19/41865—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 job scheduling, process planning, material flow
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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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- 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
- Y02P90/80—Management or planning
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- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Factory Administration (AREA)
Abstract
The present invention relates to a kind of intelligent plant management platform system, including：Intellisense layer is summarized, arranged and is stored for the data to information source each in production process；Intelligent data analysis layer, it is analyzed in real time for the Various types of data to acquisition, the quality state of health status and product to equipment is monitored, assesses and predicts, and analysis result is shown in human-computer interaction interface is visualized, and generates corresponding decision support suggestion；For analysis result and decision recommendation to be pushed to each department of company management on demand, decision and plan foundation are provided for upper layer information system for management and decision-making level.It is of the invention fully to excavate history and real-time monitoring data and creation data, accurately quantitative analysis and management and control is carried out to the health status of equipment, by formulating the rational production schedule and maintenance plan to the predictive analysis of equipment state, it prevents equipment and product from failing due to failure, effectively reduces O＆M cost, improve into production efficiency, ensure product quality and raising market synthesized competitiveness.
Description
Technical field
The present invention relates to a kind of intelligent plant management platform systems, belong to intelligent manufacturing technology field.
Background technology
For manufacturing business, production equipment and enterprise produce it is closely related, expensive and operation and maintenance into
Originally the ratio for occupying entreprise cost is very big, therefore realizes lean, precision and the intelligence of production equipment O＆M, and equipment is made
Enterprise is made with very great meaning.
There is the following in the production management of existing manufacturing business：First, existing CNC Machine Network manufacture
Mass data, these data are often stored in the database of enterprise and nobody shows any interest in, without good analysis mode, at present
Be only limited to initial data reproduction, included in huge potential value be not fully utilized and excavate；Second is that
Since numerically-controlled machine tool quantity is more, type is more, system is various, although data interconnection, for each different type of machines, lack each machine
The specific aim health status monitoring result of platform；Third, existing mold production management system is more from design angle, do not have
Have and equipment health status is monitored, and do not connect production efficiency and equipment health in management, use machine
Device will cause control unknown risks because of the unknown of decline situation to the completion of production task.Such as the maintenance pipe of identical equipment
Reason, due to often relying on experience and equipment user's handbook, used maintenance mode is mostly convergent, however, according to equipment
The different operating modes undergone, the process that identical equipment may fail are not quite similar, if real for the not serious equipment that fails
Maintenance is applied, then the wasting of resources and downtime can be caused, and then influence production efficiency, if for serious set of failing
Standby delay is safeguarded, then may cause equipment accelerated ageing or even serious production safety hidden danger.
The unexpected generation of manufacturing enterprise's equipment fault, can not only increase the maintenance cost of enterprise, and can seriously affect enterprise
The production efficiency of industry, makes enterprise sustain a great loss.The health status of manufacturing equipment and the abrasion condition of machining tool are to influence
The key factor and risk of product quality, even in a state that equipment obvious fault does not occur and shuts down, due to equipment
Loss of significance caused by health status decline, though invisible objective reality.
Invention content
The technical problem to be solved in the present invention is to provide a kind of reduction O＆M cost, improve the intelligent plant pipe into production efficiency
Platform system.
To achieve the above object, the technical scheme is that：
A kind of intelligent plant management platform system, including：Intellisense layer, for information source each in production process
Data are acquired, summarize, arrange and store；Intelligent data analysis layer is analyzed in real time for the Various types of data to acquisition,
The quality state of health status and product to equipment is monitored, assesses and predicts, and analysis result is man-machine in visualization
It is shown in interactive interface, generates corresponding decision support suggestion；Management and decision-making level, for analysis result and decision recommendation to be pressed
Each department of company management need to be pushed to, decision and plan foundation are provided for upper layer information system.
Further, the data acquired include sensing data, MDC data, production schedule data, repair and safeguard note
Record, qualitative data, supply chain data, inventory data.
Further, the Intelligent data analysis layer include algorithm function module, data modeling module, equipment health in advance examine and
Diagnostic module, board cluster management module, tool life management module, managing power consumption and analysis module, personal management module, matter
Amount monitoring and management module, the full production cycle quality tracing module of product, intelligent maintenance arranging module, intelligent production management and row
Journey module, equipment operation violation alert module, mobility statistics and one or more combinations in analysis module.
Further, the equipment health examines the diagnosis that model is taken based on diagnostic module and board cluster management module in advance
The feature vector of other same categories of device in the feature vector of each board and cluster is carried out otherness and compared by method and/or use
Diagnostic method.
Further, the model be associated with cutter, tooling, plant machinery precision model, to device history monitoring and
Creation data feature is targetedly extracted, and is examined and fault diagnosis model in advance using the characteristic value adjustment of extraction, to equipment
Carry out health status monitoring.
Further, it is the model is corresponding with the heat engine program before equipment every time booting, in the warm-up operations before booting
Equipment health status is monitored by the model.
Further, the equipment health is examined in advance includes health, guards against and suggests maintenance, tight with the analysis result of diagnostic module
Weight simultaneously suggests repairing three ranks.
Further, the tool life management module in the equipment vibrating sensor, Noise Acquisition device and
PLC controller connects, and extracts data characteristics from the signal of vibrating sensor, Noise Acquisition device and PLC controller, calculates
Health value predicts decline curve when the trend to fail occurs in health value, while sets actual effect threshold value according to historical data,
Extrapolate cutter remaining life.
Further, the upper layer information system includes ERP system, supply-chain management system, order management system, equipment dimension
Keeping reason system, personal management and performance assessment system.
Further, the equipment with visualization human-computer interaction interface includes hand-hold communication appliance, PC machine, tablet.
A kind of to sum up content, intelligent plant management platform system of the present invention, makes full use of and excavates history and reality
When monitoring data and creation data, accurately quantitative analysis and management and control is carried out to the health status of equipment, by being good for equipment
The rational production schedule and maintenance plan are formulated in the predictive analysis of health state, prevent equipment and product from failing due to failure, have
Effect reduces O＆M cost, improves into production efficiency, guarantee product quality and improve market synthesized competitiveness.In addition, the present invention realizes
The automatic collection of the real time data of machine tool network, plant data are analyzed in real time, health forecast and diagnosis, quality of production pipe
Reason, production process monitoring, operating statistic and optimization, nearly zero UNPLANNED DOWNTIME make all numerical control devices really become an information
Node becomes a part for entire corporate networks, by the clustering of lathe, networking, precise management, realizes from management level
Seamless information to individual equipment connects.
Description of the drawings
Fig. 1 is management platform system composition figure of the present invention.
Specific embodiment
The present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings：
As shown in Figure 1, a kind of intelligent plant management platform system provided by the invention, including Intellisense layer, intelligent number
According to analysis layer, management and decision-making level.
Wherein, Intellisense layer is factory's central data library management system, for information source each in production process
Data are acquired, summarize, arrange and store.The data acquired in Intellisense layer are primarily directed to numerically-controlled machine tool key portion
The creation data of part, the acquisition for managing data, monitoring data.Numerically-controlled machine tool critical component is mainly axis driving motor, cutter, master
Axis, feed system, coolant pump and lubricating system etc. carry out data acquisition for these critical components, are broadly divided into two
Class, one kind be by PLC controller carry out signal acquisition, it is another kind of be by the various kinds of sensors being installed on critical component into
Row signal acquisition.It specifically includes sensing data, MDC data, production schedule data, repair and safeguards record, qualitative data, confession
Answer chain data, inventory data etc..
Intelligent data analysis layer, in Intellisense layer and acquisition and the Various types of data that summarizes are analyzed in real time,
Middle Various types of data includes historical data and the data acquired in real time, generation and the relevant information of types of functionality in production activity, right
The health status of equipment and the quality state of product are monitored, assess and predict, and analysis result is being visualized man-machine friendship
It is shown in mutual interface, generates corresponding decision support suggestion.
Intelligent data analysis layer includes algorithm function module, data modeling module, equipment health and examines and diagnostic module, machine in advance
Platform cluster management module, tool life management module, managing power consumption and analysis module, personal management module, quality monitoring and pipe
Reason module, intelligent maintenance arranging module, intelligent production management and arranging module, is set the full production cycle quality tracing module of product
Standby operation violation alert module, mobility statistics and analysis module etc..
Equipment is mainly the key components and parts of mold machine tool, such as cutter, feed system, bearing and main shaft etc., each is closed
The decline in health of key member is directly related to the online situation of entire board, and the abrasion of a component may result in die quality
Decline machine of even delaying.Pass through monitoring data of the algorithm function module in Intellisense layer to collected each critical component, pipe
Reason data, creation data are analyzed, to realize the health evaluating of each single device and cluster device in cluster, cutter life
It estimates, quality of production management, production process monitoring, managing power consumption, the health control of board cluster, equipment operating statistic, optimize life
The functions such as production and maintenance scheduling, and finally realize and the performance state of equipment and product is monitored, assessed and predicted and generated
Corresponding decision support suggestion, for each administrative department's real-time monitoring equipment operating status of company, control product quality, timely processing
Various problems in production process.Intelligent data analysis layer can also only set a portion module as needed, to realize
Which part function.
Wherein, equipment health examines the diagnosis side that model is preferably taken based on diagnostic module and board cluster management module in advance
Method can also use the feature vector progress otherness by other same categories of device in the feature vector of each board and cluster to compare
Diagnostic method.Wherein for the catastrophic failure of single device, using kernel model based diagnosis method and use the spy of separate unit
Sign vector is compared with the feature vector of same categories of device other in cluster, the method diagnosed according to the difference after comparison.
This system realizes the information of equipment room by the comparison in difference between similar board on the basis of unit platform health control is realized
Interconnection and Experience, to provide relatively reliable health evaluating and diagnostic result, realize the cluster pipe of entire shop equipment
Reason.The failure of board cluster is examined in advance, can improve, which can not integrate the health and fitness informations of factory all boards, carries out O＆M scheduling
Optimization and it is pre- examine and diagnostic model establish during do not cover all environmental aspects and lead to model prediction misalignment, unit model
Can not be to this progress self study and adjustment the problems such as.
Diagnostic model is established by the data modeling module in Intelligent data analysis layer, after system installation, according to
The characteristics of mold is processed targetedly extracts device history monitoring and creation data feature, including MDC machine tool datas
With IMS sensor data etc., the model for being associated with cutter, tooling, machine tool mechanical precision and other relation factors is established, using carrying
The characteristic value adjustment taken is examined in advance and fault diagnosis model, and actual operating data and model are compared, health status is carried out to equipment
Monitoring.It is in the present embodiment, model is corresponding with the heat engine program before equipment every time booting, pass through in the warm-up operations before booting
The model adjusted is monitored equipment health status, and operator is made to understand the health status of board critical component, ensures
The reliability of equipment.Can be with alarm for predictable unsound state, and deviating cause is prejudged simultaneously.It is right
In the lathe newly to come into operation, will can also directly give tacit consent in the mode input to system under serviceable condition.
Discrete classification will be carried out to the health status of each equipment, distinguish which kind of degree is in designed visualization interface
Health, which kind of degree be warning and suggest being safeguarded and which kind of degree is serious and have that repair is necessary, and administrative staff can be with
With reference to the suggestion, corresponding maintenance and maintenance project etc. are worked out.
The abrasion of cutter is mainly the abrasion of cutter tooth, cracking of cutter etc., and different degrees of abrasion can cause abnormal shake
Dynamic and noise causes cut quality bad, and this system is mounted with additional vibrating sensor and noise gathering in equipment
Device, to detect the abnormal vibrations and noise that cutter generates in process, by from vibrating sensor and noise gathering
The signal acquired in device in combination with the signal of PLC controller, extracts related data, is analyzed with intelligent algorithm is advanced
Go out the health value of current cutter, when the trend to fail occurs in health value, predict and decline with the algorithm of appropriate regression fit
Curve is moved back, while actual effect threshold value is set according to historical data, estimated threshold value is compared, extrapolates cutter remaining life.
For production process monitoring, mainly collected creation data is analyzed in real time, such as Vibration Condition, carry
Speed, speed of service etc. provide online malfunction monitoring early warning and product quality forecast in real time in process of production.
It for managing power consumption, is mainly analyzed by the creation data to acquisition, monitors the main energy consumption portion of board
Part, such as the energy consumption of motor, according between board energy consumption it was found that potential faults, to reduce downtime.
In monitoring data, creation data and management data that Intelligent data analysis layer slave device in this system generates, lead to
It crosses the current health status of intelligent algorithm analytical equipment, and utilizes the quality risk and board of equipment health prediction product
Failure risk, and then health status to equipment and the quality state of product are monitored, assess and predict, and by production efficiency
It links together with equipment health status, different equipment uses different maintenance modes according to health status, according to risk
Cost function carries out collaboration optimization to maintenance plan and the production schedule, by equipment health status and the production schedule and maintenance project phase
Matching proposes that production optimizes scheduling suggestion, to prevent equipment from failing because of failure, realizes the waste reduced in production and stops
Cost allowance caused by the machine time ensures the maximum output efficiency of whole system or device clusters, realizes the plan close to zero
Outer shutdown and the accurate management to product quality.
Management is used for the analysis result of function module each in Intelligent data analysis layer and decision recommendation is on-demand with decision-making level
Each department of company management is pushed to, decision and plan foundation is provided for upper layer information system, realizes the letter of entire decision chain
Cease closed loop.Wherein, upper layer information system includes ERP (Enterprise Resource Planning) system, supply chain
Management system, order management system, equipment maintenance management system, personal management and performance assessment system.
This system is the intelligent plant management platform system based on industry 4.0, and pre- according to implementation above examines and diagnose, real
Now manage all numerically-controlled machine tools of entire factory concentratedly, the online situation of every lathe of real-time display, health status is timely excellent
Metaplasia is produced and schedule ahead maintenance work.The information such as the health status of every a machine tool and its key part and component will be backed up in cloud
In the data bank at end, manager can access the platform of cloud computing by communication apparatus such as hand-hold communication appliance, PC machine, tablets,
With reference to the production schedule, safeguard that guarantee plan and resource information, plant manager directly can remotely monitor factory's operation conditions,
The abnormality of equipment is understood in time, and most equipment health status matches offer production most with the production schedule and maintenance project at last
Cost allowance caused by waste and the downtime reduced in production is realized in goodization scheduling suggestion.
This system manages all numerically-controlled machine tools the equipment networking in factory concentratedly using a platform,
Realize the automatic collection of real time data of machine tool network, plant data analyze in real time, health forecast and diagnosis, quality of production pipe
Reason, production process monitoring, operating statistic and optimization, nearly zero UNPLANNED DOWNTIME make all numerical control devices really become an information
Node becomes a part for entire corporate networks, by the clustering of lathe, networking, precise management, realizes from management level
Seamless information to individual equipment connects.
This system can improve the lathe effective time, and the failure of board critical component is predicted and diagnosed, machine
The maintenance of platform critical component can accomplish to be prompted before parts damages and early warning, is caused due to component catastrophic failure
Maintenance time and cost will significantly reduce.This system before manufacture assesses lathe health status, makes technician more
It is absorbed in improvement to product design rather than to the maintenance of lathe and using upper, matches so that human resources obtain optimization
It puts, improves labor efficiency.
This system can be predicted and be assessed to the performance degradation process of equipment and product, and equipment or product are predicted
It safeguards, its performance degradation state of look-ahead.Unlike failure early diagnosis, intelligent maintenance is laid particular emphasis on to equipment or product
The whole process of future performance decay state is predicted rather than performance state diagnosis sometime.Secondly, in analysis of history data
Meanwhile intelligent maintenance introduces and is compared (Peer-to-Peer) adjustment corresponding information transmission frequency in time with same category of device
Make simple data sampling signal transmission and analysis in analysis on demand rather than traditional sense with quantity, more improve prediction and
Decision accuracy.
As described above, the plan content with reference to given by attached drawing, can derive similar technical solution.In every case it is not de-
Content from technical solution of the present invention, any simple modification that technical spirit according to the present invention makees above example, etc.
With variation and modification, in the range of still falling within technical solution of the present invention.
Claims (10)
1. a kind of intelligent plant management platform system, which is characterized in that including：
Intellisense layer is acquired, summarizes, arranges and stores for the data to information source each in production process；
Intelligent data analysis layer is analyzed in real time for the Various types of data to acquisition, the health status and product to equipment
Quality state is monitored, assesses and predicts, and analysis result is shown in human-computer interaction interface is visualized, and generates corresponding
Decision support suggestion；
Management and decision-making level are upper strata for analysis result and decision recommendation to be pushed to each department of company management on demand
Information system provides decision and plan foundation.
2. a kind of intelligent plant management platform system according to claim 1, it is characterised in that：The data acquired include
Sensing data, MDC data, production schedule data, repair and maintenance record, qualitative data, supply chain data, inventory data.
3. a kind of intelligent plant management platform system according to claim 1, it is characterised in that：The Intelligent data analysis
Layer includes algorithm function module, data modeling module, equipment health and examines and diagnostic module, board cluster management module, cutter in advance
Life-span management module, managing power consumption and analysis module, personal management module, quality monitoring and management module, product produce week entirely
Phase quality tracing module, intelligent maintenance arranging module, intelligent production management and arranging module, equipment operation violation alert module,
Mobility counts and one or more combinations in analysis module.
4. a kind of intelligent plant management platform system according to claim 3, it is characterised in that：The equipment health is examined in advance
With diagnostic module and board cluster management module be taken based on model diagnostic method and/or using by the feature of each board to
Amount and the feature vector of other same categories of device in cluster carry out the diagnostic method that otherness compares.
5. a kind of intelligent plant management platform system according to claim 4, it is characterised in that：The model is is associated with
Cutter, tooling, plant machinery precision model, to device history monitoring and creation data feature targetedly extracted,
It is examined and fault diagnosis model in advance using the characteristic value adjustment of extraction, health status monitoring is carried out to equipment.
6. a kind of intelligent plant management platform system according to claim 5, it is characterised in that：By the model and equipment
The heat engine program before booting corresponds to every time, and equipment health status is supervised by the model in the warm-up operations before booting
It surveys.
7. a kind of intelligent plant management platform system according to claim 3, it is characterised in that：The equipment health is examined in advance
Include health with the analysis result of diagnostic module, guard against and suggest safeguarding, is serious and suggest repairing three ranks.
8. a kind of intelligent plant management platform system according to claim 3, it is characterised in that：The tool life management
Module is connect with vibrating sensor, Noise Acquisition device and the PLC controller in equipment, from vibrating sensor, noise
Data characteristics is extracted in harvester and the signal of PLC controller, calculates health value, when the trend to fail occurs in health value
Decline curve is predicted, while actual effect threshold value is set according to historical data, extrapolates cutter remaining life.
9. a kind of intelligent plant management platform system according to claim 1, it is characterised in that：The upper layer information system
Including ERP system, supply-chain management system, order management system, equipment maintenance management system, personal management and performance evaluation system
System.
10. a kind of intelligent plant management platform system according to claim 1, it is characterised in that：It is man-machine with visualizing
The equipment of interactive interface includes hand-hold communication appliance, PC machine, tablet.
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| CN201611209946.4A CN108241343A (en) | 2016-12-24 | 2016-12-24 | A kind of intelligent plant management platform system |
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| CN201611209946.4A CN108241343A (en) | 2016-12-24 | 2016-12-24 | A kind of intelligent plant management platform system |
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| CN110083135A (en) * | 2019-05-15 | 2019-08-02 | 浙江先博节能科技有限公司 | Air compressor machine remotely monitor and control system |
| CN110378547A (en) * | 2019-01-09 | 2019-10-25 | 常州易管智能科技有限公司 | A kind of Performance Performance Management System Internet-based |
| CN110617209A (en) * | 2019-09-20 | 2019-12-27 | 江苏欣皓测试技术有限公司 | Online monitoring and diagnosing method and system for pump station unit |
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