CN212623707U

CN212623707U - Megametric equipment management system

Info

Publication number: CN212623707U
Application number: CN202021344995.0U
Authority: CN
Inventors: 黄玮; 孙飞; 杜振东; 王兵
Original assignee: Tianjin FAW Toyota Motor Co Ltd
Current assignee: Faw Toyota Motor Co ltd
Priority date: 2020-07-10
Filing date: 2020-07-10
Publication date: 2021-02-26
Anticipated expiration: 2030-07-10

Abstract

The utility model discloses a megasonic equipment management system, which relates to the technical field of the production of interior and exterior ornaments of a vehicle, and comprises a plurality of sensors, a plurality of sensors and a plurality of sensors, wherein the sensors are used for establishing an internal network control and screening equipment detection points; monitoring related parameters including oil pressure, cooling, heating, servo control and injection molding quality systems; a PLC linked with a plurality of sensors; the server is linked with TCP/IP equipment of the PLC through a network cable and Ping is connected, a server data service thread reads PLC address data through an FAT protocol and stores the data into a server database through a network protocol in real time; data acquisition and real-time state monitoring are realized; and the data analysis end reads the data from the database, calculates and analyzes the data according to the management content. The utility model discloses with digital, networked, intelligent solution three dumb problems, also solved and not gone into the net, can not report automatically, can not carry out the problem of transparence management.

Description

Megametric equipment management system

Technical Field

The utility model discloses an interior gadget production technical field of vehicle especially relates to a million waiting equipment management system.

Background

At present, a new factory molding class comprises three processes of injection molding, slush molding foaming and spraying, and is an internal and external ornament production workshop with the capacity of 22 thousands. The main equipment of the workshop is a control system constructed by Toyopuc PLC based on the Japanese Toyota industrial and mechanical system development (manufactured by JTEKT). And connecting each input and output by using an FL-remote network at the field network level. Take various signals and output a warning lamp signal or the like. The communication between each PLC controller is realized by adopting an FL-NET network in a PLC control layer, for example, the PLC controller is a servo motor which realizes the communication with the Mitsubishi company PLC to control the Mitsubishi motor, thereby realizing the synchronous control. And the connection with a host system, various display screens and the like is realized through Ethernet.

The display screen connection can be realized through Ethernet network cables of various Toyopuc PLC built-in Ethernet ports, and the high-speed communication can be realized with upper computers such as computers. It may be helpful to implement standardized designs, especially for enterprises like toyota to implement a global standardized technology system. The redesign cost is saved, and meanwhile, the open network can absorb other advanced technologies to be used.

The upper computer system of the system is weak, does not have a processing method of the system, cannot be connected with other brands of PLCs, and needs to establish a protocol for the information outgoing of the upper computer system on an IT layer and a PLC layer so as to realize information processing.

The equipment is the most important equipment in a forming course, and has the advantages of considering the production of the three lines of the Tada line and the new line, having no backup machine and needing a large amount of preservation to maintain the equipment daily. The heavy production tasks cause equipment to suddenly fail to cause equipment halt, and the capacity output is severely restricted. For example, the small fire condition of the Tim machine in 14 years is caused by short circuit abnormality after the heater is coated by the molten resin, and the fire is caused after electric ignition, so that the equipment is seriously damaged, and the shutdown time reaches half a year.

Because daily point inspection and cleaning are not in place, the heater is not maintained sufficiently, particularly the change of current is not monitored, so that some signs before abnormity occurs are not found, and finally a fire disaster is caused. The problem of blockage of the cooling water jacket of the TIM machine is also that due to the fact that daily maintenance point detection is not in place, megaly prediction and fault early warning cannot be effectively achieved. The water channel is slowly blocked by water scale, foreign matters and the like, the water flow is continuously changed and reduced until the blockage can not be found in time, but the problem is passively found when the resin is cooled and clamped into the die to cause damage, the problem can be found out at that time, the treatment is needed, a large amount of working hours are needed to be corresponded, and the equipment mobility is seriously influenced. As in table 1 below.

TABLE 1 failure of Forming machine

(1) As shown in table 1 above, the downtime of 530 minutes within 2 months due to the equipment failure is more difficult to perform daily maintenance and management, the maintenance point is not clear, the maintenance time is not sufficient, and a vicious circle is formed, especially when the production task is heavy.

Through the above analysis, the problems and defects of the prior art are as follows: (1) in a control system constructed by Toyopuc PLC in the prior art, an upper computer system is weak, a processing method of the system is not available, the system cannot be connected with PLCs of other brands, and an information exit protocol of the upper computer system needs to be established on an IT level and a PLC level to realize information processing.

(2) The forming class equipment in the prior art cannot automatically monitor daily point inspection, cleaning, heater maintenance and current change in real time, so that some signs before abnormity occurs are not found, finally, fire disasters are caused, and the equipment mobility is seriously influenced.

(3) The existing equipment only can manufacture products, and cannot fully play the function of interconnection and intercommunication of the equipment, so that the utilization rate of the equipment is low; the precision equipment does not automatically acquire data, does not have remote monitoring, and causes running state and production information, even fault information is opaque and cannot be visually presented, and related personnel cannot know problems in time, so that greater loss is easily caused; because the equipment is not interconnected and intercommunicated, the equipment state and the production information are not known, and the efficiency is low and the error is easy to occur only by manual feedback, thereby causing unscientific and low intelligent degree.

The difficulty in solving the above problems and defects is: how to reflect real-time dynamic, real and accurate of the equipment. The sensors in the equipment need to be connected in series in a FL-NET local area network mode, data are sent to a server from a PLC at a frequency of 0.2s, and a simple and understandable real-time transition diagram is generated after database operation and analysis. Meanwhile, the trend of the data is calculated by utilizing an algorithm, so that the purpose of counting in mind is achieved.

The significance of solving the problems and the defects is as follows: the equipment achieves 'hearing and eyesight' and feeds back the self condition to the user in real time. Thereby improving the quality and the mobility and paving the road for the future popularization of intelligent factories.

SUMMERY OF THE UTILITY MODEL

In order to overcome the problems existing in the related art, the embodiment of the utility model provides a megametric device management system.

The megametric device management system includes:

the sensors are used for establishing internal network control and screening equipment detection point positions; monitoring parameters of an oil pressure system, a cooling system, a heating system, a servo control system and an injection molding quality system;

a PLC linked with a plurality of sensors;

the server is linked with TCP/IP equipment of the PLC through a network cable and Ping is connected, a server data service thread reads PLC address data through an FAT protocol and stores the data into a server database through a network protocol in real time; data acquisition and real-time state monitoring are realized;

the data analysis end reads the data from the database, calculates and analyzes the data according to the management content, and puts the corresponding data into a response memory for waiting to be displayed; and after the data display process is started, reading data from the memory at regular time according to the refreshing time, refreshing the data on the data display interface in real time according to the management content, and simultaneously performing data acquisition, calculation, storage, grouping and analysis according to the service thread.

Further, the megametric device management system further includes: the background is used for checking the application condition of the system resources and timely sinking the data memory and releasing the thread;

the alarm unit collects corresponding data according to the characteristics of the equipment, automatically compares the data according to a set value, and automatically generates alarm information when the exceeding time occurs;

the injection molding machine records the management data of all related items according to a time axis, traces the state of equipment at the time according to the survey of historical data, performs data analysis on unqualified products and finds out key factors influencing the quality; and calculating a plurality of groups of data to form a correlation waveform, and displaying the state trend and trend of the equipment by using the correlation waveform during fault analysis.

Further, an internal network control device is built in the plurality of sensors.

Further, the data analysis end is connected with a data alarm device.

The utility model discloses a technical scheme that embodiment provided can include following beneficial effect:

based on the theory of wisdom mill, the utility model discloses use TIM machine (innovation injection molding machine) as the examination point, carry out industry internet's relevant exploration, created IOT megaly equipment management system. The method comprises the following steps: 1) screening the detection point positions of the equipment, additionally installing a sensor and establishing an internal network control; 2) collecting corresponding data according to the equipment characteristics; 3) early warning management is carried out on the data, and the abnormal and historical data are inquired, so that more accurate positioning can be realized in fault analysis; 4) and introducing an algorithm to manage the equipment megametrics.

The utility model provides a digital equipment in workshop imbeds sensor, integrated circuit, software and other digital components and parts in production facility to mechanical, electron, the equipment that the information technology degree of depth fuses have been formed. The digital equipment is an important tool for workshop production and is a physical foundation for digital workshop construction. The utility model discloses with digital, networked, intelligent solution "three dumb" problems, also solved and not gone into the net, can not report automatically, can not carry out the problem of transparence management, realized equipment and external information exchange, resource sharing, ability in coordination.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure, as claimed

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.

Fig. 1 is a flowchart of a control method of an megametric device management system (IOT) according to an embodiment of the present invention.

Fig. 2 is a schematic diagram of a sensor general control device provided in an embodiment of the present invention.

Fig. 3 is a schematic diagram of heater current meter monitoring provided by an embodiment of the present invention.

Fig. 4 is a schematic diagram of data transmission in a control method of an internet megafunction unit (IOT) according to an embodiment of the present invention.

Fig. 5 is an interface diagram for upper and lower limit alarm setting provided by the embodiment of the present invention.

Fig. 6 is a diagram of an inquiry interface of historical data according to an embodiment of the present invention.

Fig. 7 is a display interface diagram of relevance waveforms according to an embodiment of the present invention.

Fig. 8 is an analysis schematic diagram of the MT method in the megametric management provided by the embodiment of the present invention.

Wherein, in (a), the MT algorithm is adopted to analyze the correlation among the items, and the abnormity can be judged only according to the limit value of each variable; (b) through the utility model discloses calculate mahalanobis distance and come to carry out the analysis to the big data of production facility, carry out the megaly and manage.

Fig. 9 is a diagram of a megametric management interface according to an embodiment of the present invention.

Fig. 10 is a graph showing the mobility rate of the Tim machine according to the embodiment of the present invention.

Fig. 11 is a schematic diagram of an implementation method of a new factory molding class reforming injection molding machine IoT according to an embodiment of the present invention.

Fig. 12 is an application schematic diagram provided by the embodiment of the present invention.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

As shown in fig. 1, the control method of an embodiment of the present invention for an internet megafunction unit (IOT) includes:

s101, screening equipment detection point positions, additionally installing a sensor and establishing an internal network control.

And S102, collecting corresponding data according to the equipment characteristics.

S103, early warning management is carried out on the data, abnormal data and historical data are inquired, and accurate positioning can be achieved in fault analysis.

And S104, introducing an algorithm to manage the equipment megacharacters.

Fig. 2 is a schematic diagram of a control method of an megametric device management system (IOT) according to an embodiment of the present invention.

Step S101, point location selection comprises:

through a recent fault list, 138 important management points are screened out, which mainly cover oil pressure, cooling, heating, servo control and injection quality systems, and parameters are monitored, as shown in the following table 2.

TABLE 2Tim Point sampling List (part)

Based on this table 2, the utility model discloses 145 sensors have been installed on equipment (fig. 2 is the utility model discloses the sensor is always controlled device picture in kind that the embodiment provided, fig. 3 is the utility model provides a heater ampere meter control picture in kind is transferred the back with equipment PLC, and the server passes through the net twine and is linked and Ping logical with PLC's TCP/IP equipment, and the server data service thread reads PLC address data through the FAT agreement to in the server database is deposited through network protocol with data in real time.

By the scheme, data acquisition is realized, the 'dumb' of equipment is solved, and real-time state monitoring is carried out.

The connection method for collecting corresponding data according to the device characteristics in step S102 includes:

depending on the original local area network of the equipment, the data analysis end reads out the data from the database, calculates and analyzes the data according to the management content, and puts the corresponding data into a response memory for waiting to be displayed. After the data display process is started, data can be read from the memory at regular time according to the refreshing time and refreshed on the data display interface in real time according to the management content, and meanwhile, the system arranges the resources according to the conditions of data acquisition, calculation, storage, grouping, analysis and the like reasonably by the service thread. And the background checks the application condition of the system resources at regular time, and timely and clearly sinks the data to proper memory to release the thread. The operating principle is shown in fig. 4.

In step S103, the big data comparison includes:

and the data is automatically compared according to a set value, and when the data exceeds the set value, alarm information is automatically generated. For example when the temperature of cooling water has reached 25 degrees centigrade, can influence the quality of production product, this time the utility model discloses the temperature that can set for the cooling water is no longer than 25 degrees centigrade, if surpass and remind relevant personnel check out test set with regard to reporting to the police to ensure production quality's stability. As shown in the upper and lower limit alarm setting interface diagram of fig. 5.

The utility model discloses in, the situation of the present stage equipment of real-time notice security, the problem appears and can in time report, falls to the minimum with the risk. Fig. 6 is a diagram of an inquiry interface of historical data according to an embodiment of the present invention.

The utility model discloses in, historical data is the top of the great importance of this system, and the management data of all relevant items of injection molding machine all can be according to the time axis record, and this provides favourable foundation to tracing back of product from now on, according to the investigation to historical data, can trace back the state of equipment at that time, carries out data analysis to unqualified product to find out the key factor who influences the quality. For better carding data, it is understandable, the utility model discloses calculate multiunit data, form the associativity waveform, make work develop more accurately when carrying out failure analysis, equipment status trend and trend are more clear. Such as the correlation waveform display interface diagram of fig. 7.

In step S104, the megametric management includes:

the function is the most important part and is one of the innovations of the industrial internet exploration. The utility model discloses a more MT method of megasonic management application carries out data analysis. The deviation between the correct value and the actual value is measured by the mahalanobis distance (mahalanobis distance) representing the distance between a point and a distribution. The method is an effective method for calculating the similarity of two unknown sample sets.

Multivariate analysis is performed by using mahalanobis distance, which is called mahalanobis algorithm, also called MT method. It is used to predict and optimize manufacturing engineering data to facilitate diagnosis of current conditions.

For multivariate systems X' (X)₁,x₂,…x_k) Counting the distance T²Has the general formula:

T²＝(X-X)S^-1(X-X)＝Z′C^-1Z；

the general formula of the modified Mahalanobis distance in the Mahalanobis approach is

Where k represents the number of variables of the system. From the above two equations, the distance T is counted²The nature of the modified mahalanobis distance used in the mahalanobis method is the same, but numerically differs by an integral multiple.

Wherein MD represents the Mahalanobis distance (Mahalanobis distance) X' represents a multivariate system. T is²Representing the statistical distance and x representing the respective variable. S represents the sample variance.

The principle of MT analysis in megametric management is shown in fig. 8.

The MT algorithm can analyze the correlation between items, and can only determine the abnormality according to the threshold value of each variable, as shown in fig. 8 (a), and fig. 8 (b) by calculating the mahalanobis distance according to the present invention, the big data of the production equipment is analyzed, and the megametric management is performed. At this time, the analysis state 2 is an abnormal point, deviates from a normal trend and needs to be confirmed in time. The relation among all variables is fully considered, and the abnormal state can be predicted more accurately.

In the Tim machine IOT management system, the analysis management will show the specific results of the analysis, the graphical display area will show the discreteness of the data in the form of scatter, and the use of the equipment can be predicted by analyzing the discreteness of the data. The larger the value of the MT is, the greater the discreteness of the data is, the more unstable the working condition of the equipment is proved, and the rule and the use condition of the equipment can be found from the data stored and analyzed every day. Of course, the discrete points in fig. 9 can also be combined with alarm information to analyze when and when the equipment is in problem, which plays a very positive role in promoting and directing field prevention and security.

The present invention will be further described with reference to specific application examples.

Practical field application improving example 1

19

days

10 and 9 months in 2019, the IOT equipment alarms and displays that the PJ4 cooling water flow is abnormal, the equipment pipeline and the water tank are kept between two shifts to be investigated and confirmed, the pipeline is blocked, the water tank is dirty, the problem is not easy to be found at ordinary times because the part is positioned in the equipment, and after an external monitoring flowmeter is installed, the problem point can be quickly found and countermeasures can be taken in time, so that the normal operation of the equipment and the product quality are ensured.

Through the utility model discloses an improve, equipment is no longer deaf and dumb, and the work efficiency of safekeeping also promotes rapidly, does the foreshadowing for making whole smart transparent mill of intelligence.

After the IOT system is introduced, the utilization rate of the Tim machine is stable, the quality of the whole bumper is controllable in real time, the loss caused by poor equipment is avoided, the number of security workers is greatly reduced, 111.66 ten thousand yuan is saved due to poor quality, and the security cost is reduced by 46 ten thousand yuan. Through the utility model discloses, combine smart machine, let whole workshop be full of intelligent power to the intelligent mill has been made to the point area face. Such as the rate transition diagram of Tim machine in fig. 10.

Cloud based on IT system development calculates to ITs cloud service who is the core does the utility model discloses set up wider world, information reaches cell-phone APP, and all developments in workshop and data report form are mastered to a key, the utility model discloses the IOT megametric equipment that uses the Tim machine is the starting point, knows the unification, realizes the implementation of smart mill at the in-process of analysis industry thing networking. The method realizes that the Toyota New Global architecture factory creates a super-first resin molding workshop, leads the continuous development of the resin molding industry and promotes the continuous advance of the manufacturing industry.

Application example 2

Fig. 11 is a schematic diagram of a new factory reforming injection molding machine IoT implementation method.

Definition of IoT:

in order to realize interconnection of people, machines and objects, information exchange and communication are carried out, so that a network for intelligently identifying, positioning, tracking, monitoring and managing the objects is realized.

The concrete application of the forming course is as follows:

and analyzing the fault condition of the equipment in the past year by using the TIM injection molding machine as a test point, screening monitoring points and carrying out sensor installation and signal acquisition. The method comprises the following steps:

1) and the dynamic state of the equipment is grasped through real-time analysis of the data, and the equipment is comprehensively monitored by the upper limit management breadth and the lower limit management breadth.

2) And the part which can not be checked in normal production can be monitored in real time, so that the problem that the point check can not be carried out when the production is busy is solved.

3) The data can be reviewed in history, and the conditions of each related device in abnormal conditions can be analyzed.

4) And the data can be modeled to perform trend analysis, and the current equipment state is judged according to the trend.

5) And establishing a quick calling system of the equipment.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure should be limited only by the attached claims.

Claims

1. A megametric device management system, comprising:

a PLC linked with a plurality of sensors;

2. The megasonic device management system of claim 1, further comprising: the background is used for checking the application condition of the system resources and timely sinking the data memory and releasing the thread;

3. The megametric device management system of claim 1, wherein the plurality of sensors are organized with an intranet control device.

4. The megametric device management system of claim 1, wherein a data alarm device is connected to the data parsing side.