CN117055503A - Intelligent production line system based on industrial Internet electromechanical control - Google Patents
Intelligent production line system based on industrial Internet electromechanical control Download PDFInfo
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Abstract
The application belongs to the technical field of industrial Internet, and discloses an intelligent production line system based on electromechanical control of the industrial Internet; the cloud monitoring system comprises data monitoring equipment, a controller, a cloud server and a mobile terminal. The data monitoring equipment is used for collecting operation data of the conveying equipment, the processing equipment and the packaging equipment in real time. The controller is used for controlling the operation state of each device according to the operation data. The cloud server is used for identifying abnormal data of the production line pair and generating alarm information. The application simplifies the data processed by the controller based on the operation data and the product state acquired in real time, improves the accuracy and timeliness of electromechanical control, and rapidly finds the unqualified reasons of the products by integrally binding personnel, equipment, products and packages, thereby timely making the adjustment of working procedures or equipment and improving the qualification rate and the production efficiency of the products.
Description
Technical Field
The application relates to the technical field of industrial Internet, in particular to an intelligent production line system based on electromechanical control of the industrial Internet.
Background
An electromechanical control intelligent production line system based on the industrial Internet is a production line system which combines the Internet technology and the electromechanical control technology. The intelligent and automatic management system realizes data exchange and remote control among devices by connecting the devices such as the sensor, the actuator, the controller and the like to the Internet, thereby realizing intelligent and automatic management of a production line.
The existing intelligent production line system lacks management on personnel and equipment, and the problems of failure or disqualification of products in a detection stage or a sold stage often exist such as difficulty in accurate responsibility tracking, difficulty in analysis of reasons and the like. For example, for product quality detection, generally, depending on the judgment of detection equipment or detection personnel, after-sales feedback of unqualified products is difficult to quickly analyze the root cause of the unqualified products, related responsible personnel are difficult to find in time, and the equipment or process causing the unqualified products cannot be adjusted in time, so that not only is the production yield affected, but also the maintenance and improvement cost is increased. In addition, the existing intelligent production line system focuses on cloud data processing, although accuracy in aspects of equipment and processing safety, equipment service life prediction and the like is enhanced, electromechanical control of equipment often depends on initially set parameters, self-adaptive adjustment is difficult to carry out according to feedback of the equipment, and accuracy and timeliness of the electromechanical control are poor.
In view of the above, the application provides an intelligent production line system based on electromechanical control of the industrial Internet.
Disclosure of Invention
In order to overcome the defects in the prior art, the application provides an intelligent production line system based on electromechanical control of an industrial Internet.
In order to achieve the above purpose, the present application provides the following technical solutions: an intelligent production line system based on industrial Internet electromechanical control comprises data monitoring equipment, a controller, a cloud server and a mobile terminal.
The data monitoring equipment is used for collecting operation data of the conveying equipment, the processing equipment and the packaging equipment in real time.
The controller is used for: and binding the equipment label, the operator information, the product label and the packaging label of each procedure according to the operation data. And controlling the running states of the conveying equipment, the processing equipment and the packaging equipment.
The cloud server is used for identifying abnormal data of the production line pair through data interaction with the data monitoring equipment and the controller and generating corresponding alarm information.
According to the production line system, the running data and the product state of each device in the production line are collected in real time, the set output information is combined, the conveying frequency of the production line is adjusted in real time, meanwhile, whether a processing procedure accords with the set processing standard is judged based on the running data and the product state, and an alarm is sent when abnormality of the processing procedure or the product state is found, so that related operators are prompted to timely process, and larger economic loss is avoided. In addition, through the whole binding to personnel, equipment, product and packing, can all inquire about relevant equipment and operating personnel fast to any unqualified product to according to the state about each process completion, the unqualified reason is found fast, and then makes the adjustment of process or equipment in time, improves qualification rate and the production efficiency of product.
Further, the data monitoring device comprises a device monitoring module and a personnel monitoring module, wherein the device monitoring module is used for collecting conveying frequency, displacement data, initial product images of each procedure, packaging images and fault data, and start and stop signals of the conveying device, the processing device and the packaging device. The personnel monitoring module is used for collecting face information or fingerprint information.
Further, the controller comprises a conveying frequency control module, a processing control module and an information binding module.
The conveying frequency control module is used for: and generating an initial conveying frequency according to the preset processing efficiency, and sending the initial conveying frequency to conveying equipment. And adjusting the conveying frequency according to the start-stop signal fed back in real time.
The processing control module is used for: judging whether the product materials, semi-finished products and finished products are at preset positions or not according to the displacement data, if yes, starting the equipment monitoring module to acquire initial product images and packaging images based on the semi-finished products, the finished products and the packages, and starting corresponding processing equipment or packaging equipment to operate.
The information binding module is used for: binding the equipment label, the operator information, the product label and the packaging label of each procedure, judging whether each procedure is bound, and if so, sending a verification completion signal to the conveying equipment. If the conveying equipment does not receive the verification completion signal, an alarm signal is sent out after a preset period.
Further, the adjusting method of the conveying frequency control module specifically comprises the following steps:
calculating an initial conveying frequency according to the daily yield and the planned operation duration, and then the initial conveying frequency f 0 The expression is as follows:
f 0 ＝(T p -T e )/C
wherein T is p To plan the working time length, T e Reserved time length for planning, C is daily planned production.
Correcting the conveying frequency according to the start-stop signal fed back in real time, and then correcting the conveying frequency f r The expression is as follows:
wherein m is the sampling frequency, f ij The single completion frequency for the ith sample for the jth device, n being the number of devices.
Further, the cloud server predicts and corrects the conveying frequency according to the operation data, and the concrete method comprises the following steps:
firstly, calculating the standard deviation sigma of the frequency of the completion of each device compared with the preset processing frequency in each processing period j The expression is as follows:
in the method, in the process of the application,the average single completion frequency for the j-th device.
Secondly, calculating the deviation degree of each device, and then calculating the deviation degree E j The expression is as follows:
E j ＝σ j /f r 。
judging whether the deviation degree exceeds a preset deviation threshold E 0 If yes, an alarm is sent out, and the ideal single-time completion frequency of each device is adjusted. Ideal single-pass completion frequency f h The expression is as follows:
finally, according to the fault information of each device in a preset statistical period, carrying out prediction correction on the conveying frequency, and predicting the corrected conveying frequency f rs The expression is as follows:
f rs ＝T t -(1-μ)∑T bj ]/C p
wherein T is t T is the total operation duration in one statistical period bj For the fault or maintenance duration of the jth device in a statistical period, mu is the repetition coefficient of the fault or maintenance duration of each device, C p To complete the yield in one statistical period.
Further, the processing control module comprises an instruction generation sub-module, an alarm sub-module, a starting control sub-module and an information binding module.
The instruction generation submodule is used for: judging whether the current working procedure is finished according to the current product position and state, and generating a processing instruction if the current working procedure is not finished. If so, continuing to judge whether each procedure is completed with information binding, and if so, generating a conveying instruction. And judging whether the daily yield reaches the planned yield or not, and if so, sending a stop instruction.
The alarm submodule is used for: judging whether fault data exist in the operation data, and if so, generating a fault alarm signal. Judging whether the initial product image, the packaging image and the corresponding comparison image are matched or not, if not, marking the product label, and generating a disqualification alarm signal.
The starting control sub-module is used for sending a starting instruction to the conveying equipment according to the conveying instruction, and sending the starting instruction to the processing equipment, the packaging equipment and the equipment monitoring module after receiving a stopping signal fed back by the conveying equipment.
Further, the information binding module comprises a device binding sub-module, a personnel binding sub-module and a packaging binding sub-module.
The equipment binding sub-module is used for identifying the product labels in the initial product image after the conveying equipment finishes conveying each time, and collecting the equipment labels corresponding to each product label, so that a temporary data set based on the product labels is established.
The personnel binding sub-module is used for identifying the face information or the fingerprint information, binding the face information or the fingerprint information with the product tag and adding the face information or the fingerprint information into the corresponding temporary data set.
The packaging binding sub-module is used for identifying packaging labels in the packaging image, binding the packaging labels with the product labels and adding the packaging labels and the product labels into corresponding temporary data sets.
Further, the cloud server comprises a communication module, a storage module, an evaluation module and an alarm signal generation module.
The communication module is used for carrying out remote communication with the controller, the data monitoring equipment and the mobile terminal, and receiving or transmitting corresponding data or control instructions.
The storage module is used for storing the operation data and the temporary data set. The stored data sets are classified according to personnel and equipment.
The evaluation module is used for evaluating the personnel and the equipment according to a preset evaluation period to obtain corresponding personnel operation scores and equipment quality scores.
The alarm signal generation module is used for: 1. and extracting features of the initial product image, calculating the Euclidean distance between the extracted feature image and a preset product comparison chart, and generating a processing disqualification alarm signal if the Euclidean distance is higher than a preset Euclidean distance threshold value. 2. And performing defect detection on the package image, extracting distinguishing features of the package image compared with a preset package comparison chart, judging whether the distinguishing features exceed a preset allowable defect range, and if so, generating a package disqualification alarm signal. 3. Judging whether the face information or the fingerprint information is matched with the control information pre-stored in the corresponding procedure, and if not, generating a personnel abnormality alarm signal. 4. Judging whether the personnel operation scores and the equipment quality scores exceed a preset score range, and if so, generating corresponding personnel and equipment disqualification alarm signals.
Further, the evaluation method of the evaluation module specifically comprises the following steps:
calculating personnel operation scores according to the personnel operation efficiency and the finished product qualification rate, and then calculating personnel operation scores rho P The expression is as follows:
wherein omega is P For the preset personnel operation efficiency weight, n D For the number of times of personnel operation, f hP For each frequency of operation of the person,for average delivery frequency ρ Q Is the yield of finished products of personnel, ρ QS Is the preset minimum qualification rate.
Calculating equipment quality score according to the operation efficiency and the fault frequency of the equipment, and then calculating equipment quality score rho E The expression is as follows:
wherein f hE For each operating frequency of the apparatus, n E Omega for the number of operations of the plant E For the preset equipment fault weight, f b Is the failure frequency.
Further, the mobile terminal comprises a permission verification module, a query module and a remote control module.
The permission verification module is used for acquiring corresponding permission through actively inputting verification information. The rights include query rights, remote control rights.
The query module is used for sending a request query signal by the cloud server and querying corresponding operation data or alarm information by retrieving key terms or according to data types set by the cloud server.
The remote control module is used for sending a control instruction to the cloud server, and further remotely controlling the conveying equipment, the processing equipment, the packaging equipment and the data monitoring equipment through the controller.
The intelligent production line system based on the industrial Internet electromechanical control has the technical effects and advantages that:
according to the application, the running data and the product state of each device in the production line are collected in real time, the conveying frequency of the production line is adjusted in real time by combining the set yield information, meanwhile, whether the processing procedure accords with the set processing standard is judged based on the running data and the product state, and an alarm is sent when the abnormality of the processing procedure or the product state is found, so that related operators are prompted to process in time, and larger economic loss is avoided. In addition, through the whole binding to personnel, equipment, product and packing, can all inquire about relevant equipment and operating personnel fast to any unqualified product to according to the state about each process completion, the unqualified reason is found fast, and then makes the adjustment of process or equipment in time, improves qualification rate and the production efficiency of product.
Drawings
FIG. 1 is a schematic diagram of the overall structure of an intelligent production line system of the present application;
fig. 2 is a schematic structural diagram of the data monitoring device, the controller and the cloud server in fig. 1.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
Referring to fig. 1, the embodiment provides an intelligent production line system based on industrial internet electromechanical control, which comprises conveying equipment, processing equipment, packaging equipment, data monitoring equipment, a controller, a cloud server and a mobile terminal. The conveying equipment, the processing equipment and the packaging equipment are basic equipment of a production line, and the conveying equipment is used for conveying product materials, semi-finished products and finished products to preset positions respectively. The conveying equipment can adopt stage conveying belts, and the conveying belts are mutually connected through a rotary conveying table or a mechanical arm and the like, so that a product material in a production line sequentially passes through each processing device and is gradually a finished product. The processing equipment is used for processing the product materials into semi-finished products and finished products in sequence. The processing equipment comprises a plurality of processing devices, each processing device is used for completing the processing procedures divided in advance, and the preset time length of each processing procedure is the same or similar. For example, the product material needs to be subjected to main procedures such as cutting, drilling, cutting, polishing and the like, wherein each main procedure can be subdivided into a plurality of small procedures, and then the combination operation is carried out according to the duration of each small procedure, so that the actual preset time of each procedure is close. The packaging equipment is used for packaging finished products. The conveying equipment, the processing equipment and the packaging equipment can be controlled manually or intelligently and automatically.
Referring to fig. 2, the data monitoring device is used for collecting operation data of the conveying device, the processing device and the packaging device in real time.
Specifically, the data monitoring equipment comprises an equipment monitoring module and a personnel monitoring module, wherein the equipment monitoring module is used for collecting conveying frequency, displacement data, initial product images of each procedure, packaging images and fault data, and start and stop signals of conveying equipment, processing equipment and packaging equipment. The start-stop signal can be actively transmitted to the controller through corresponding equipment, so that the acquisition time of the start-stop signal can be shortened, and the timeliness of equipment control is improved. The conveying frequency determines the yield of the production line and can be collected according to the actual running state of the conveying equipment. The displacement data can be obtained by collecting the displacement signals of the semi-finished product or the finished product according to the arranged displacement sensor, and the pose of the semi-finished product or the finished product can be obtained by combining the corresponding processing device in some precision processing procedures. The product image, the package image and the like can be acquired by installing the camera device, and the image of the corresponding visual angle is acquired according to the change of the semi-finished product or the finished product in each procedure compared with the previous procedure. The fault data comprises fault signals sent by all devices independently and fault signals acquired by the equipment monitoring module. For example, when an operation parameter fault occurs to an autonomous alarm, a fault signal is actively sent to the controller, or a fault signal cannot be actively sent due to a circuit fault caused by an unexpected short circuit or a short circuit, and an abnormality such as voltage, current and the like is detected by the equipment monitoring module, the equipment monitoring module sends the fault signal to the controller.
The personnel monitoring module is used for collecting face information or fingerprint information. The face information or the fingerprint information has the characteristics of high acquisition speed and obvious distinguishing characteristics, and the existing face or fingerprint acquisition device is mature and relatively low in cost. The operators can be confirmed through the face or fingerprint information, so that misoperation of non-relevant operators is prevented, when the product quality is wrong, the corresponding operators can be quickly found, so that improper operation of the operators is corrected, and the reject ratio of products is reduced. In an intelligent production line, although the processing of products can be independently completed by an automatic intelligent device, manual operation is still required for maintenance, parameter setting and the like of the device. Moreover, for the partial detection method of the product quality, the cost of manual detection is lower and the accuracy is higher compared with that of intelligent image detection.
The controller is used for binding the equipment label, the operator information, the product label and the packaging label of each procedure according to the operation data and controlling the operation states of the conveying equipment, the processing equipment and the packaging equipment. Specifically, the controller comprises a conveying frequency control module, a processing control module and an information binding module.
The conveying frequency control module is used for: and generating an initial conveying frequency according to the preset processing efficiency, and sending the initial conveying frequency to conveying equipment. And adjusting the conveying frequency according to the start-stop signal fed back in real time. The adjusting method of the conveying frequency control module comprises the following specific steps:
calculating an initial conveying frequency according to the daily yield and the planned operation duration, and then the initial conveying frequency f 0 The expression is as follows:
f 0 ＝(T p -T e )/C
wherein T is p To plan the working time length, T e Reserved time length for planning, C is daily planned production.
Correcting the conveying frequency according to the start-stop signal fed back in real time, and then correcting the conveying frequency f r The expression is as follows:
wherein m is the sampling frequency, f ij The single completion frequency for the ith sample for the jth device, n being the number of devices.
In actual production, the use wear and maintenance conditions of each processing device are different, and the time period for actually completing the process is also changed, so that the conveying frequency needs to be adjusted according to the actual running state of the production line. In this embodiment, in order to reduce the working pressure of the controller and improve the timeliness of the controller, the history data of the production and processing are stored in the cloud server. The cloud server predicts and corrects the conveying frequency according to the operation data, and the concrete method comprises the following steps:
firstly, calculating the standard deviation sigma of the frequency of the completion of each device compared with the preset processing frequency in each processing period j The expression is as follows:
in the method, in the process of the application,the average single completion frequency for the j-th device.
Secondly, calculating the deviation degree of each device, and then calculating the deviation degree E j The expression is as follows:
E j ＝σ j /f r 。
judging whether the deviation degree exceeds a preset deviation threshold E 0 If yes, an alarm is sent out, and the ideal single-time completion frequency of each device is adjusted. Ideal single-pass completion frequency f h The expression is as follows:
finally, according to the fault information of each device in a preset statistical period, carrying out prediction correction on the conveying frequency, and predicting the corrected conveying frequency f rs The expression is as follows:
f rs ＝[T t -(1-μ)∑T bj ]/C p
wherein T is t T is the total operation duration in one statistical period bj For the fault or maintenance duration of the jth device in a statistical period, mu is the repetition coefficient of the fault or maintenance duration of each device, C p To complete the yield in one statistical period.
The processing control module is used for: judging whether the product materials, semi-finished products and finished products are at preset positions or not according to the displacement data, if yes, starting the equipment monitoring module to acquire initial product images and packaging images based on the semi-finished products, the finished products and the packages, and starting corresponding processing equipment or packaging equipment to operate. Specifically, the processing control module comprises an instruction generation sub-module, an alarm sub-module, a starting control sub-module and an information binding module.
The instruction generation submodule is used for: judging whether the current working procedure is finished according to the current product position and state, and generating a processing instruction if the current working procedure is not finished. If so, continuing to judge whether each procedure is completed with information binding, and if so, generating a conveying instruction. In this embodiment, each device enters a stop state after the production line completes the daily production every day. According to the preset, each process should be in a state of not starting the processing or completing the processing, rather than shutting down the devices when the processing is not completed. When the production line is started initially every day, whether the current working procedure is finished or not is judged, and then a corresponding instruction is output, so that the unqualified product caused by the missing of the working procedure is prevented.
And judging whether the daily yield reaches the planned yield or not, and if so, sending a stop instruction. In actual production, considering the service life of the equipment, after the equipment continuously works for a preset time period, the operation should be suspended integrally, and especially in a production line with manual participation, the operation period of the equipment needs to be planned reasonably, and especially after the daily output is finished, a certain time is reserved for maintaining the equipment or cleaning the operation environment.
The alarm submodule is used for: judging whether fault data exist in the operation data, and if so, generating a fault alarm signal. As described above, the fault data is actively transmitted by each device or detected by the data monitoring device.
Judging whether the initial product image, the packaging image and the corresponding comparison image are matched or not, if not, marking the product label, and generating a disqualification alarm signal. In order to relieve the data processing pressure of the controller, the image recognition is coarse recognition, and only the basic shapes and positions of the semi-finished products and the finished products are compared, so that the former process is confirmed to be finished and the former process is within a preset processing area.
The starting control sub-module is used for sending a starting instruction to the conveying equipment according to the conveying instruction, and sending the starting instruction to the processing equipment, the packaging equipment and the equipment monitoring module after receiving a stopping signal fed back by the conveying equipment.
The information binding module is used for: binding the equipment label, the operator information, the product label and the packaging label of each procedure, judging whether each procedure is bound, and if so, sending a verification completion signal to the conveying equipment. If the conveying equipment does not receive the verification completion signal, an alarm signal is sent out after a preset period. Specifically, the information binding module comprises a device binding sub-module, a personnel binding sub-module and a packaging binding sub-module.
The equipment binding sub-module is used for identifying the product labels in the initial product image after the conveying equipment finishes conveying each time, and collecting the equipment labels corresponding to each product label, so that a temporary data set based on the product labels is established.
The personnel binding sub-module is used for identifying the face information or the fingerprint information, binding the face information or the fingerprint information with the product tag and adding the face information or the fingerprint information into the corresponding temporary data set. The face information or the fingerprint information is stored in the controller and the cloud server in advance. In the controller, face information or fingerprint information is bound with the device it operates. In the cloud server, each face information or fingerprint information corresponds to a person data set, and corresponding identity information such as name, age, identity card number and the like is stored.
The packaging binding sub-module is used for identifying packaging labels in the packaging image, binding the packaging labels with the product labels and adding the packaging labels and the product labels into corresponding temporary data sets. After the packaging label is bound with the product label, corresponding product information can be obtained by identifying the packaging label on the premise that the packaging label is not opened, and in the product selling stage, a customer can observe relevant product parameters, product pictures and the like in advance, so that the experience of the customer is improved, and the sales of the product is improved.
The cloud server is used for identifying abnormal data of the production line pair through data interaction with the data monitoring equipment and the controller and generating corresponding alarm information. Specifically, the cloud server comprises a communication module, a storage module, an evaluation module and an alarm signal generation module.
The communication module is used for carrying out remote communication with the controller, the data monitoring equipment and the mobile terminal, and receiving or transmitting corresponding data or control instructions. In some embodiments, the data monitoring device may first communicate with the controller and then send relevant data to the cloud server via the controller.
The storage module is used for storing the operation data and the temporary data set. The storage module may also categorize the stored data sets according to personnel, equipment, products. For example, the image of the product at any process and the final product parameters can be queried by scanning the packaging label identifying the product according to the data set of the product classification, including all information of the product from raw materials to packaging. Alternatively, the manager may query the job status of the device by retrieving the tag number of the device.
The evaluation module is used for evaluating the personnel and the equipment according to a preset evaluation period to obtain corresponding personnel operation scores and equipment quality scores.
Specifically, calculating a personnel operation score according to the personnel operation efficiency and the finished product qualification rate, and then calculating a personnel operation score ρ P The expression is as follows:
wherein omega is P For the preset personnel operation efficiency weight, n D For the number of times of personnel operation, f hP For each frequency of operation of the person,for average delivery frequency ρ Q Is the yield of finished products of personnel, ρ QS Is the preset minimum qualification rate.
Calculating equipment quality score according to the operation efficiency and the fault frequency of the equipment, and then calculating equipment quality score rho E The expression is as follows:
wherein f hE For each operating frequency of the apparatus, n E Omega for the number of operations of the plant E For the preset equipment fault weight, f b Is the failure frequency.
The alarm signal generation module is used for: 1. and extracting features of the initial product image, calculating the Euclidean distance between the extracted feature image and a preset product comparison chart, and generating a processing disqualification alarm signal if the Euclidean distance is higher than a preset Euclidean distance threshold value. The euclidean distance is used to describe the similarity between two images, and the smaller the euclidean distance is, the higher the similarity between the two images is characterized. Compared with a controller, the image processing in the cloud server is more accurate, and can be used as a judging basis for product quality detection.
2. And performing defect detection on the package image, extracting distinguishing features of the package image compared with a preset package comparison chart, judging whether the distinguishing features exceed a preset allowable defect range, and if so, generating a package disqualification alarm signal. The inspection of the package image basically includes surface blemishes, scratches, specifications, etc., and allows a larger range of defects than the precision inspection of the product image.
3. Judging whether the face information or the fingerprint information is matched with the control information pre-stored in the corresponding procedure, and if not, generating a personnel abnormality alarm signal. In the stage of personnel information input, working procedures or equipment which are responsible for each worker are bound, personnel information which is not input and verified or is not matched with the equipment and the working procedures is alarmed, and therefore product loss caused by personnel misoperation is avoided. Meanwhile, the defect of unclear responsibility following caused by personnel replacement can be effectively prevented, and responsible personnel can be quickly and accurately found in tracing the reasons of unqualified products.
4. Judging whether the personnel operation scores and the equipment quality scores exceed a preset score range, and if so, generating corresponding personnel and equipment disqualification alarm signals.
The mobile terminal is used for carrying out remote data interaction with the cloud server to acquire operation data and alarm information in real time or sending a control instruction to the cloud server to carry out remote control on the conveying equipment, the processing equipment, the packaging equipment and the data monitoring equipment. The mobile terminal comprises a permission verification module, a query module and a remote control module.
The permission verification module is used for acquiring corresponding permission through actively inputting verification information. The rights include query rights, remote control rights. In practical application, APP based on customer and manager can be developed, and the customer or manager logs in through personal account number to obtain different rights.
The query module is used for sending a request query signal by the cloud server and querying corresponding operation data or alarm information by retrieving key terms or according to data types set by the cloud server. The cloud server classifies the stored data, so that the efficiency of data query can be effectively improved.
The remote control module is used for sending a control instruction to the cloud server, and further remotely controlling the conveying equipment, the processing equipment, the packaging equipment and the data monitoring equipment through the controller. The remote control module is suitable for a manager of the production line, for example, a maintainer corrects equipment programs or parameters through remote operation, so that remote maintenance of equipment is realized, or the manager remotely controls the processing efficiency or start-stop signals of the production line when receiving a temporary yield change plan.
The intelligent production line system of the embodiment is used for collecting the operation data and the product state of each device in the production line in real time, combining the set output information, adjusting the conveying frequency of the production line in real time, judging whether the processing procedure accords with the set processing standard or not based on the operation data and the product state, and sending an alarm when abnormality of the processing procedure or the product state is found, so that related operators can be prompted to timely process the information, and larger economic loss is avoided. In addition, through the whole binding to personnel, equipment, product and packing, can all inquire about relevant equipment and operating personnel fast to any unqualified product to according to the state about each process completion, the unqualified reason is found fast, and then makes the adjustment of process or equipment in time, improves qualification rate and the production efficiency of product.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (10)
1. An intelligent production line system based on industrial Internet electromechanical control comprises conveying equipment, processing equipment and packaging equipment; the conveying equipment is used for conveying the product materials, the semi-finished products and the finished products to preset positions respectively; the processing equipment is used for sequentially processing the product materials into the semi-finished product and the finished product; the packaging equipment is used for packaging the finished product; characterized in that the production line system further comprises:
the data monitoring equipment is used for collecting operation data of the conveying equipment, the processing equipment and the packaging equipment in real time;
a controller for: binding equipment labels, operator information, product labels and packaging labels of each procedure according to the operation data; controlling the running states of the conveying equipment, the processing equipment and the packaging equipment;
and the cloud server is used for identifying abnormal data of the production line pair through data interaction with the data monitoring equipment and the controller and generating corresponding alarm information.
2. The intelligent production line system based on the electromechanical control of the industrial internet according to claim 1, wherein the data monitoring equipment comprises an equipment monitoring module and a personnel monitoring module, wherein the equipment monitoring module is used for collecting conveying frequency, displacement data, initial product images of each procedure, packaging images and fault data, and start-stop signals of the conveying equipment, the processing equipment and the packaging equipment; the personnel monitoring module is used for collecting face information or fingerprint information.
3. An industrial internet-based, electromechanically controlled intelligent production line system according to claim 2, wherein said controller comprises:
a delivery frequency control module for: generating an initial conveying frequency according to preset processing efficiency, and sending the initial conveying frequency to conveying equipment; adjusting the conveying frequency according to the start-stop signal fed back in real time;
a process control module for: judging whether the product materials, semi-finished products and finished products are at preset positions or not according to the displacement data, if yes, starting an equipment monitoring module, acquiring initial product images and packaging images based on the semi-finished products, the finished products and the packages, and starting corresponding processing equipment or packaging equipment to operate;
an information binding module for: binding the equipment label, the operator information, the product label and the packaging label of each procedure, judging whether each procedure is bound, and if so, sending a verification completion signal to the conveying equipment; and if the conveying equipment does not receive the verification completion signal, sending an alarm signal after a preset period.
4. An intelligent production line system based on industrial internet electromechanical control according to claim 3, wherein the adjustment method of the conveying frequency control module is specifically as follows:
calculating an initial conveying frequency according to daily output and planned operation duration, and then obtaining the initial conveying frequency f 0 The expression is as follows:
f 0 ＝(T p -T e )/C
wherein T is p To plan the working time length, T e Reserving a time length for planning, wherein C is daily planned output;
correcting the conveying frequency according to the start-stop signal fed back in real time, and then correcting the conveying frequency f r The expression is as follows:
wherein m is the sampling frequency, f ij The single completion frequency for the ith sample for the jth device, n being the number of devices.
5. The intelligent production line system based on the industrial internet electromechanical control according to claim 4, wherein the cloud server predicts and corrects the conveying frequency according to the operation data, and the specific method is as follows:
firstly, calculating the standard deviation sigma of the frequency of the completion of each device compared with the preset processing frequency in each processing period j The expression is as follows:
in the method, in the process of the application,an average single completion frequency for the j-th device;
secondly, calculating the deviation degree of each device, and then the deviation degree E j The expression is as follows:
E j ＝σ j /f r ；
judging whether the deviation degree exceeds a preset deviation threshold E 0 If yes, an alarm is sent out, and the ideal single completion frequency of each device is adjusted; the ideal single-pass completion frequency f h The expression is as follows:
finally, according to the fault information of each device in a preset statistical period, carrying out prediction correction on the conveying frequency, and predicting the corrected conveying frequency f rs The expression is as follows:
wherein T is t T is the total operation duration in one statistical period bj For the fault or maintenance duration of the jth device in a statistical period, mu is the repetition coefficient of the fault or maintenance duration of each device, C p To complete the yield in one statistical period.
6. An industrial internet-based, electromechanically controlled intelligent production line system according to claim 3, wherein said process control module comprises:
an instruction generation sub-module for: judging whether the current working procedure is finished according to the current product position and state, and generating a processing instruction if the current working procedure is not finished; if yes, continuing to judge whether each procedure is completed with information binding, and if yes, generating a conveying instruction; judging whether the daily yield reaches the planned yield or not, if so, sending a stop instruction;
an alarm sub-module for: judging whether fault data exist in the operation data, and if so, generating a fault alarm signal; judging whether the initial product image, the packaging image and the corresponding comparison image are matched or not, if not, marking the product label, and generating a disqualification alarm signal;
and the starting control sub-module is used for sending a starting instruction to the conveying equipment according to the conveying instruction, and sending the starting instruction to the processing equipment, the packaging equipment and the equipment monitoring module after receiving a stopping signal fed back by the conveying equipment.
7. An industrial internet-based electromechanically controlled intelligent production line system according to claim 3, wherein said information binding module comprises:
the equipment binding sub-module is used for identifying the product labels in the initial product image after the conveying equipment finishes conveying each time, and collecting the equipment labels corresponding to each product label, so that a temporary data set based on the product labels is established;
the personnel binding sub-module is used for identifying the face information or the fingerprint information, binding the face information or the fingerprint information with the product tag and adding the face information or the fingerprint information into a corresponding temporary data set;
and the packaging binding sub-module is used for identifying packaging labels in the packaging image, binding the packaging labels with the product labels and adding the packaging labels and the product labels into corresponding temporary data sets.
8. An industrial internet-based electromechanically controlled intelligent production line system according to claim 2, wherein said cloud server comprises:
the communication module is used for carrying out remote communication with the controller, the data monitoring equipment and the mobile terminal and receiving or sending corresponding data or control instructions;
a storage module for storing operational data, a temporary data set; classifying the stored data sets according to personnel and equipment;
the evaluation module is used for evaluating the personnel and the equipment according to a preset evaluation period to obtain corresponding personnel operation scores and equipment quality scores;
an alarm signal generation module for: 1. extracting features of the initial product image, calculating the Euclidean distance between the extracted feature image and a preset product comparison chart, and generating a processing disqualification alarm signal if the Euclidean distance is higher than a preset Euclidean distance threshold; 2. performing defect detection on the packaging image, extracting distinguishing features of the packaging image compared with a preset packaging comparison chart, judging whether the distinguishing features exceed a preset allowable defect range, and generating a packaging disqualification alarm signal if the distinguishing features exceed the preset allowable defect range; 3. judging whether the face information or the fingerprint information is matched with the control information pre-stored in the corresponding procedure, and if not, generating a personnel abnormality alarm signal; 4. and judging whether the personnel operation scores and the equipment quality scores exceed a preset score range, and if so, generating corresponding personnel and equipment disqualification alarm signals.
9. The intelligent production line system based on the industrial internet electromechanical control according to claim 8, wherein the evaluation module is specifically configured as follows:
calculating personnel operation scores according to the personnel operation efficiency and the finished product qualification rate, and then calculating the personnel operation scores ρ P The expression is as follows:
wherein omega is P For the preset personnel operation efficiency weight, n D For the number of times of personnel operation, f hP For each frequency of operation of the person,for average delivery frequency ρ Q Is the yield of finished products of personnel, ρ QS Is the preset minimum qualification rate;
calculating equipment quality score according to the operation efficiency and failure frequency of equipment, and then calculating equipment quality score rho E The expression is as follows:
wherein f hE For each operating frequency of the apparatus, n E Omega for the number of operations of the plant E For the preset equipment fault weight, f b Is the failure frequency.
10. An intelligent production line system based on industrial internet electromechanical control according to claim 1, characterized in that the production line system further comprises a mobile terminal comprising:
the permission verification module is used for acquiring corresponding permission by actively inputting verification information; the rights include query rights and remote control rights;
the query module is used for sending a request query signal by the cloud server and querying corresponding operation data or alarm information by retrieving key terms or according to data types set by the cloud server;
and the remote control module is used for sending a control instruction to the cloud server, and further remotely controlling the conveying equipment, the processing equipment, the packaging equipment and the data monitoring equipment through the controller.
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| CN117873007A (en) * | 2024-03-11 | 2024-04-12 | 成都秦川物联网科技股份有限公司 | Manufacturing flow management method, system, equipment and medium based on industrial Internet of things |
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| CN117873007A (en) * | 2024-03-11 | 2024-04-12 | 成都秦川物联网科技股份有限公司 | Manufacturing flow management method, system, equipment and medium based on industrial Internet of things |
| CN117873007B (en) * | 2024-03-11 | 2024-05-24 | 成都秦川物联网科技股份有限公司 | Manufacturing flow management method, system, equipment and medium based on industrial Internet of things |
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