CN109886606A - A kind of component intellectualized detection production management system and method - Google Patents

Abstract

A kind of component intellectualized detection production management system implementation method based on Internet of Things and big data analysis, by the full-service process that the component of aerospace enterprise group detects accomplish it is visual, can analyze, controllably, detection progress, production efficiency, production bottleneck are provided in real time, reach and improve production capacity, improve manufacturer, the design using unit, manufacture level, improves the target of the success rate of space product.

Description

A system and method for intelligent detection and production management of components

technical field

The invention belongs to the application field of component detection engineering, and relates to an intelligent detection and production management system and method for components based on the Internet of Things and big data analysis.

Background technique

Aerospace products have the characteristics of many varieties, small batches, complex product configurations and processes, frequent research and development changes, high product quality requirements, and the entire development process must be traceable, which brings certain difficulties to the organization and management of research and development units. The characteristic production conditions of enterprises are exactly the requirements of today's market for products to be increasingly multi-functional and specialized. At present, most aerospace research and development units have implemented Enterprise Resource Management System (ERP), but its core modules plan management, quality management in the production process, command and control system, etc. have unreasonable plans, opaque process control, insufficient flexibility, and lack of responsibility. In place, too much manual participation and other issues. The secondary supplementary screening business of components is especially faced with such a problem because of its complex and strict technological process. Therefore, the realization of informatization, automation and intelligence of inspection business can play a revolutionary role in the development of enterprises.

The intelligent component inspection and production management system based on the Internet of Things and big data analysis can make the whole business process of component inspection of aerospace enterprises visible, analyzable and controllable, and can solve the above problems well. The massive data generated in the detection process, including machine energy consumption, product technology, electrical performance, sensor sensing, detection environment, appearance graphics, etc., can be collected into the system through the Internet of Things platform, reducing the time and cost of manual entry into the system. Errors, various quality analysis are carried out through big data analysis technology, and the detection progress, production efficiency, and production bottlenecks are provided in real time, so as to achieve the goal of increasing production capacity, improving the design and manufacturing level of manufacturers and users, and improving the success rate of aerospace products.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide an intelligent detection and production management system for components, which is characterized in that it includes: a command and dispatch system center, a scientific research and production management system, an Internet of Things system platform, a detection and production unit and a data center; wherein:

The command and dispatch system center is used to realize the graphical display and analysis of command and dispatch and real-time data of various dimensions of intelligent detection demonstration lines;

The scientific research and production management system is used to realize the scheduling, production scheduling and execution control of the component operation plan;

The IoT system platform is used to establish a communication mechanism between devices and systems, realize the intelligent interconnection of IoT devices, heterogeneous system integration, data acquisition, transmission, storage, query and data analysis, dynamically monitor the operating status of devices, and Real-time early warning of abnormal situations;

The detection and production unit includes an intelligent logistics module and an automatic detection module; wherein,

The intelligent logistics module is used for wireless communication management and information transmission and analysis to realize automatic AGV driving trajectory guidance, AGV running speed, direction control, AGV operation node automatic addressing RFID, AGV automatic parking timing, AGV operating status feedback, AGV operation fault detection and alarm, AGV automatic collision avoidance and alarm function;

The automatic detection module performs the pre-screening preliminary test and the post-screening final test of the components;

The data center is used for processing the data of the scientific research and production management system and the Internet of Things system platform.

Preferably, the dimensions include: a first dimension and a second dimension, the first dimension is a process dimension, which is used to view the task execution process, historical data analysis and statistical analysis information, mainly for scheduling, screening team leaders and Ordinary screening technicians; the second dimension is the time dimension, and the task execution data of each key time node is displayed through the time axis, and this dimension is mainly oriented to the department and the leaders in charge.

Preferably, the automatic detection module includes an appearance defect automatic detection sub-module and a comprehensive parameter automatic detection sub-module; wherein, the appearance defect detection and inspection sub-module realizes the appearance defect detection of the ceramic capacitor through machine vision technology; the comprehensive parameter The parameter automatic detection sub-module is used to automatically detect parameters such as appearance, capacity accuracy, loss, insulation resistance and dielectric withstand voltage of components.

Preferably, the intelligent logistics system includes an automated warehousing module and an intelligent distribution module; the automated warehousing module communicates with the IoT platform through an interface for task management, process management, operation monitoring, job execution, and the scientific research and production management system docking.

Preferably, the automated warehouse module includes an automated vertical warehouse warehouse management module and an AGV task management module;

The automatic vertical warehouse storage management module is used for the warehouse state management of components, the execution management of in-out and out-of-warehouse actions, the in-warehouse management, the out-of-warehouse management, the kanban visual management, the warehouse information query management, etc.;

The AGV task management module is used for calling, task query, status query, task clearing, running path optimization planning, etc. of the AGV car.

Preferably, the data center further includes a Hadoop data platform; the Hadoop data platform is used to construct a big data analysis platform for production operation plans, warehousing information, test data, and MES system historical data.

Another embodiment of the present invention also provides an intelligent detection and production management method for components, which is characterized in that it includes the steps of:

Step 1: detection preparation stage, the detection preparation stage is used to create detection tasks and allocate corresponding inventory positions;

Step 2: the detection phase, the detection phase is used to detect the assignment, execution, export and storage of tasks;

Step 3: the user sampling stage, the user sampling stage is used for the closed loop of finished product delivery and inspection tasks.

Preferably, the step 1 specifically includes:

Step 101: The business department receives the sample box, and the bottom right corner of the sample box is attached with the manufacturer's QR code. The business personnel scan the QR code, enter the relevant information into the ERP system, and generate a management account;

Step 102: Replace the components from the manufacturer's material box to the standard material box of the three-dimensional warehouse;

Step 103: Print the task list with the two-dimensional code of the production task information through the ERP corresponding function module, and place the task list on the material box;

Step 104: The AGV trolley transports the material box to the three-dimensional warehouse;

Step 105: Move the material box from the AGV to the vertical warehouse conveying platform. The moving material box scans the QR code and RFID to obtain the component information and logistics information, and sets the relevant warehouse location information in the management software interface, and returns after confirmation. Send relevant information to the ERP system;

Step 106: The material box is moved to the stacker, the material box is placed on the stacker, the stacker starts to move the material box to the corresponding storage location, and the material box is stacked into the storage location.

Preferably, the step 2 specifically includes:

201. The appearance inspection station receives the ERP task entrustment prompt, click to accept, click the AGV call system to send the goods picking and delivery information to the warehouse, and send the components to be inspected to the corresponding inspection station through the AGV;

202. Through the automatic detection device for appearance defects and comprehensive parameters, the initial test data is obtained and transmitted to the big data analysis platform;

203. The management information and control information generated during the detection process are communicated through ERP and the Internet of Things platform;

204. After high-temperature storage and temperature shock test, it passes through the automatic detection device for appearance defects and comprehensive parameters again, and obtains the detection data after screening and transmits it to the big data analysis platform;

205. The big data analysis platform conducts quality analysis on batch testing targets.

Preferably, the step 3 specifically includes:

Step 301: The user submits an application for sample collection;

Step 302: query the ERP system according to the sampling conditions;

Step 303: If the checked sample has completed the aging screening and detection work, the ERP system and the three-dimensional warehouse update the warehouse task information;

Step 304: According to the sample receiving information, print the paper certificate uniformly, and seal it automatically;

Step 305: The warehouse receives the ERP finished product delivery information, and transports the finished product to the reception hall through the AGV;

Step 306: The user receives the sample, and the process is completed.

Description of drawings

FIG. 1 is an overall architecture diagram of an intelligent detection and production management system for components based on the Internet of Things and big data analysis in the present invention.

FIG. 2 is a preparation stage of a component aging screening process according to an embodiment of the present invention.

FIG. 3 is a detection stage of a component aging screening process according to an embodiment of the present invention.

FIG. 4 is a sample of a user of a component aging screening process according to an embodiment of the present invention.

Detailed ways

In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

The purpose of the invention is to help aerospace enterprises to realize real-time tracking, control and analysis of the whole process of supplementary secondary screening of components, and to provide a system for intelligent detection of components.

As shown in FIG. 1 , it is a structural diagram of a system according to an embodiment of the present invention. Specifically:

An intelligent detection and production management system for components includes: a command and dispatch system center, a scientific research and production management system, an Internet of Things system platform, a detection and production unit and a data center.

in:

The command and dispatch system center is used to realize the graphical display and analysis of command and dispatch and real-time data of various dimensions of intelligent detection demonstration lines.

In one embodiment of the present invention, the center of the command and dispatch system is designed from the functional design to the leaders of the department, dispatching, screening team leaders and ordinary screening personnel. The function design of the command and dispatch system center mainly starts from two dimensions. The first dimension is: In the process dimension, the "Key Process Function" node should be used as the main line to view the task execution process, historical data analysis and statistical analysis information. This function node is mainly for scheduling, screening team leaders and ordinary screening technicians. The second dimension is the time dimension. Through this dimension, the system takes "today", "this month" and "last month" as key time nodes, and displays the task execution data of each key time node through the time axis. This dimension is mainly for the leaders of departments and supervisors.

The scientific research and production management system is used to realize the scheduling, production scheduling and execution control of the component operation plan.

The IoT system platform is used to establish a communication mechanism between devices and systems, realize the intelligent interconnection of IoT devices, heterogeneous system integration, data acquisition, transmission, storage, query and data analysis, dynamically monitor the operating status of devices, and Real-time warning of abnormal situations.

The detection and production unit includes an intelligent logistics module and an automatic detection module.

in:

The intelligent logistics module is used for wireless communication management and information transmission and analysis to realize automatic AGV driving trajectory guidance, AGV running speed, direction control, AGV operation node automatic addressing RFID, AGV automatic parking timing, AGV operating status feedback, AGV operation fault detection and alarm, AGV automatic collision avoidance and alarm function;

The automatic detection module is used for the pre-screening preliminary test and the post-screening final test of the components. In an embodiment of the present invention, the automatic detection module includes an automatic appearance defect detection sub-module and an automatic comprehensive parameter detection sub-module, mainly for the pre-screening pre-screening and post-screening final testing services of components. ; wherein, the appearance defect detection and inspection sub-module realizes the appearance defect detection of ceramic capacitors through machine vision technology; the comprehensive parameter automatic detection sub-module is used to automatically detect the appearance, capacity accuracy, loss, insulation resistance and media pressure and other parameters.

In an embodiment of the present invention, the intelligent logistics system includes an automated warehousing module and an intelligent distribution module; the automated warehousing module communicates with the IoT platform through an interface for task management, process management, operation monitoring, job execution and The scientific research and production management system is connected.

Wherein, the automated warehouse module includes an automated vertical warehouse warehouse management module and an AGV task management module;

The automatic vertical warehouse storage management module is used for the warehouse state management of the components, the execution management of the warehouse entry and exit actions, the warehouse entry management, the warehouse exit management, the kanban visual management, the warehouse information query management, and the like. Specifically, the automated warehouse management module has the following functions:

①. The system state (warehousing, outgoing) is issued by thingworx; once the system enters a certain state, it will block the execution of other states.

②. Thingworx is responsible for the unified generation and management of the batch number and other related information of the inspection components.

③. The storage location is managed and optimized by WMS, and is provided to thingworx inventory information query, storage information of a certain batch of items and other information query interfaces.

④.thingworx is responsible for providing necessary information such as a certain batch of items, quantity, delivery location, etc. WMS is responsible for arranging out of the warehouse according to some optimization methods (for example, first-in, first-out, first-in-first-out, first-in-first-out, first-in-first-out), and delivered to a certain location by an AGV car End the entire outbound operation.

⑤. Inventory management

★Inbound goods are manually moved to the inbound and outbound platform

★There is a photoelectric sensor installed in the loading and unloading platform

★An RFID reader is installed on the inbound and outbound platform (note: it should be equipped with a metal shield to avoid misreading the material box information that should not be obtained inside and outside the warehouse)

A.thingworx first generates a "test report" and attaches the relevant information to the test components in batches and delivers it to the warehouse. The WMS manager obtains the relevant information through the QR code on the "test report" and associates the item information with a logistics box. RFID number binding.

B.WMS will automatically match the bound logistics box with the empty position (or specify it manually), and generate a warehouse receipt. When the personnel place the logistics box on the inbound and outbound platform, the RFID equipment installed on the inbound and outbound platform will respond to the The RFID card number on the logistics box is checked. If it is detected that the logistics box matches the relevant information of the warehousing order, the stacker will be mobilized to perform the warehousing operation.

C. Storage management is divided into two modes: "manual assignment" and "automatic assignment".

D.WMS provides WebService warehousing information query interface, thingworx push task field, including batch number. WMS feedbacks True or Flase, and also feeds back information such as the receipt number, warehouse location, material box number, quantity, warehouse time, and executor.

E.Thingworx provides WebService product query interface, WMS push task field, including batch number. Thingworx returns the item name, item number, specification, unit, manufacturer and other information.

⑥. Warehouse management

★There is a back-to-stock button at the front of the loading and unloading table

★There is an AGV calling and running start button at the end of the loading and unloading platform

★The warehouse monitoring computer should be placed in a suitable position near the entry and exit pallets, so that the barcode gun connected to the USB port of the computer can be easily dismantled.

★The material boxes/boxes out of the warehouse are manually moved away from the loading and unloading platform

★Accept goods delivery information from thingworx:

A.WMS provides WebService outbound request interface, and thingworx pushes task fields, including item name, item number, outbound quantity, delivery location and other information. WMS feedback True or Flase (Note: It may be accompanied by error checking code feedback such as out-of-stock, unable to find goods, etc.), and feedback the outbound order number, commodity name, commodity number, pre-allocated outbound location, material box number, Quantity, scattered/completed status, etc.

B.WMS provides the WebService outbound query interface, and the thingworx pushes the task field, including the outbound order number. WMS feedback True or Flase, and feedback error checking code (such as out-of-stock, unable to find goods, etc.), item name, item number, outbound location, material box number, quantity, bulk/full-out status, execution status , delivery time, executor, etc.

⑦. Kanban visual management

A. The moving picture information of the real-time running status and position of the stacker;

B. Current warehousing information (material box code, location of storage location);

C. Current outbound information (material box code, location location, FCL or unpacking, unpacking material box code and quantity);

D. The working state of the testing table;

E. The current position and status of the AGV car;

F. Due to the large amount of displayed information, the kanban is divided into multiple screens to display relevant information, and can be freely switched through the keys on the storage computer.

The AGV task management module is used for calling, task query, status query, task clearing, running path optimization planning, etc. of the AGV car. The AGV task management module has the following functions:

①. Soft buttons for summoning AGV trolleys are provided on the computers on each inspection stand. WMS provides WebService car call interface, thingworx push task field, including delivery location (inspection bench call or storage point). WMS feedbacks True or Flase, and forms a queuing mechanism, and runs in sequence when the car is idle;

②.WMS provides WebService AGV car task query interface, thingworx does not need to push task fields. WMS feedback AGV trolley task queuing status information;

③.WMS provides WebService AGV car status query interface, thingworx does not need to push task fields. WMS feeds back information of the AGV car, such as whether it is online, job status, current address, pre-arrival address, and current task;

④.WMS provides WebService AGV car task clearing interface, thingworx does not need to push task fields. WMS feedback True or Flase. Queue and clear AGV car tasks;

⑤.Digital map modeling of AGV operation;

⑥. AGV operation path optimization planning;

⑦. A call button (and AGV operation start button) is installed at the storage position.

(3) WMS inventory and other query functions

①.WMS provides WebService warehouse status information query interface, thingworx does not need to push task fields. WMS feeds back whether each location is free, batch number, storage material box number, item name, item number, quantity, the last storage time of the storage location, the last storage time of the storage location, the last storage executor, and the last storage execution. personal information;

②.WMS provides WebService batch query interface. thingworx push task field, containing batch number. WMS feeds back storage location, storage material box number, item name, item number, quantity, last warehousing time, last warehousing time, last warehousing executor, last warehousing executor and other information;

③.WMS provides WebService warehouse query interface. thingworx pushes the task field, containing the warehouse number (there is only one warehouse so it is 1). WMS feeds back information on warehouse operation status, such as normal, fault, job status (standby, in-warehouse, out-of-warehouse), and the cause of the failure.

The data center is used for processing the data of the scientific research and production management system and the Internet of Things system platform. Based on the Hadoop data platform, build a big data analysis platform for production job plans, warehousing information, test data, and MES system historical data. According to the requirements of the quality assurance system of aerospace electronic components, the performance test data in the component production stage is used to mine the inherent quality hidden dangers of components, and provide a high-quality, low-cost, fast and accurate quality assurance capability.

The embodiment of the present invention also provides an intelligent detection and production management method for components, including:

Step 1: Test preparation stage, which is used for creating inspection tasks and assigning corresponding inventory locations.

According to an embodiment of the present invention, the specific method of step 1 is shown in Figure 2:

Step 101: The business department receives the sample box, and the bottom right corner of the sample box is attached with the manufacturer's QR code. The business personnel scan the QR code, enter the relevant information into the ERP system, and generate a management account;

Step 102: Replace the components from the manufacturer's material box to the standard material box of the three-dimensional warehouse;

Step 103: Print the task list with the two-dimensional code of the production task information through the ERP corresponding function module, and place the task list on the material box;

Step 104: The AGV trolley transports the material box to the three-dimensional warehouse;

Step 105: Move the material box from the AGV to the vertical warehouse conveying platform. The moving material box scans the QR code and RFID to obtain the component information and logistics information, and sets the relevant warehouse location information in the management software interface, and returns after confirmation. Send relevant information to the ERP system;

Step 106: The material box is moved to the stacker, the material box is placed on the stacker, the stacker starts to move the material box to the corresponding storage location, and the material box is stacked into the storage location.

Step 2: Detection phase, the detection phase is used for the assignment, execution, and delivery and storage of detection tasks, which can be implemented according to the following process: the appearance detection station receives the ERP task entrustment prompt, clicks accept, and clicks the AGV call system to receive the goods. The material and out-of-warehouse information is transmitted to the vertical warehouse, and the components to be inspected are sent to the corresponding inspection stations through the AGV; the initial inspection data is obtained through the automatic inspection device for appearance defects and comprehensive parameters and transmitted to the big data analysis platform; Management information and control information are communicated through ERP and Internet of Things platforms; after high temperature storage and temperature shock testing, they pass through the automatic detection device for appearance defects and comprehensive parameters to obtain post-screening detection data and transmit them to the big data analysis platform; big data The analysis platform performs quality analysis on batch detection targets.

According to an embodiment of the present invention, the specific method of step 2 is shown in Figure 3:

Step 201: The appearance inspection station receives the ERP task entrustment prompt, clicks accept, and clicks the AGV call system to transmit the goods picking and delivery information to the vertical warehouse, and the AGV moves to the vertical warehouse to wait for materials;

Step 202: Click to accept the ERP task entrustment (including component information, logistics information, etc.) in the warehouse, and the stacker automatically runs according to the information to get the relevant warehouse location material box, and removes the material box from the stacker to the warehouse conveyor platform. , The mobile material box scans the QR code and RFID through the scanner to record the relevant information and send it back to the ERP system. After scanning, move the material box to the AGV;

Step 203: After the material box is placed on the AGV, the AGV starts to move to the station;

Step 204: The AGV arrives at the station, moves the material box onto the workbench, scans the QR code to read the relevant information, and transmits it back to the ERP system;

Step 205: Unpack the components in the material box and put them into the vibrating plate. The vibrating plate operates to automatically feed the capacitors and transport them to the material plate of the appearance inspection machine;

Step 206: The automatic appearance inspection starts to run, the material tray rotates, the three high-speed cameras capture the appearance of the capacitors, the captured images are input into the industrial computer and the standard images are compared and analyzed. The detection data is sent to the big data analysis platform;

Step 207: After the appearance inspection is completed, put the good product into the material box, scan the QR code to upload the relevant information to the ERP, start the next process task, and send the task to the four-parameter inspection (capacity accuracy, loss, insulation resistance and dielectric withstand voltage) worker. bit. The scanned material box is placed on the AGV, and the AGV transports the material box to the four-parameter detection station;

Step 208: The four-parameter detection station receives the ERP task, removes the material box from the AGV and places it on the workbench, scans the QR code to read the relevant information, and transmits it back to the ERP system;

Step 209: Unpack the components in the material box and put them into the vibrating plate. The vibrating plate operates to automatically feed the capacitors and transport them to the four-parameter detection robotic arm. The robotic arm sucks the capacitors and moves them to the four-parameter detection tooling to execute the four-parameter detection tool. In the inspection procedure, the industrial computer displays the relevant measurement data and conducts comparative analysis. The OK ones are dialed into the good product box, and the NG ones are dialed into the defective product box, and the relevant inspection data are sent to the big data analysis platform;

Step 210: After the four-parameter detection is completed, the good product is loaded into the material box, the two-dimensional code is scanned to upload the relevant information to the ERP, the next process task is started, and the task is sent to the high temperature storage station. The scanned material box is placed on the AGV, and the AGV transports the material box to the high temperature storage station;

Step 211: After the four-parameter detection is completed, put the good products into the material box, scan the two-dimensional code to upload the relevant information to the ERP, start the next process task, and send the task to the high temperature storage station. The scanned material box is placed on the AGV, and the AGV transports the material box to the high temperature storage station;

Step 212: The high temperature storage station receives the ERP task, the AGV transports the material box to the station, and places the device in the high temperature storage box for high temperature storage (the display outside the box displays 120±2 degrees, the time displays 96 hours, and the data changes dynamically), The detection is completed and the task is transferred to the next station

Step 213: The temperature shock station receives the ERP task, the AGV transports the material box to the station, and places the device in the temperature shock box for temperature shock (the box display shows the temperature -55±3 degrees, 125±2 degrees; the time shows 30 minutes ; The times display 5; the data changes dynamically), the task is transferred to the next station after the detection is completed;

Step 214: The electric aging station receives the ERP task, the AGV transports the material box to the station, and the device is placed in the aging box for electric aging (the box display shows a temperature of 125±2 degrees, and a time display of 168 hours), and detects Complete and transfer the task to the next station;

Step 215: After screening, the final four-parameter detection station receives the ERP task, the AGV transports the material box to the station, unloads the material box from the AGV and places it on the workbench, scans the QR code to read the relevant information, and sends it back to the ERP system;

Step 216 : Unpack the components in the material box and put them into the vibrating plate. The vibrating plate operates to automatically feed the capacitors and transport them to the four-parameter detection robotic arm. The robotic arm sucks the capacitors and moves them to the four-parameter detection tooling to execute the four-parameter detection tool. In the inspection procedure, the industrial computer displays the relevant measurement data and conducts comparative analysis. The OK ones are dialed into the good product box, and the NG ones are dialed into the defective product box, and the relevant inspection data are sent to the big data analysis platform;

Step 217: After the four-parameter detection is completed, put the good products into the material box, scan the QR code to upload the relevant information to the ERP, start the next process task, and send the task to the post-screening appearance inspection station. The scanned material box is placed on the AGV, and the AGV transports the material box to the appearance inspection station after the screen;

Step 218: The post-screening appearance inspection station receives the ERP task, the AGV transports the material box to the station, unloads the material box from the AGV and places it on the workbench, scans the QR code to read the relevant information, and sends it back to the ERP system;

Step 219: Unpack the components in the material box and put them into the vibrating plate. The vibrating plate operates to automatically feed the capacitors and transport them to the material plate of the appearance inspection machine;

Step 220: The automatic appearance detection starts to run, the material tray rotates, the three high-speed cameras capture the appearance of the capacitors, and the captured images are input into the industrial computer for comparison and analysis with the standard images. The detection data is sent to the big data analysis platform;

Step 221: After the appearance inspection after sieving is completed, the good products are put into the material box, and the relevant information is uploaded to the ERP by scanning the two-dimensional code, and the good product storage procedure is carried out. The scanned material box is placed on the AGV, and the AGV transports the material box to the vertical warehouse;

Step 222: The warehouse receives the ERP good product warehousing task, the AGV transports the material box to the station, puts the material box on the conveying platform, moves through the scanning QR code and RFID, records the relevant information and sends it back to the ERP system;

Step 223: After scanning, move the material box to the stacker, and the stacker carries the material box to the designated storage position to put the material box into the warehouse.

Step 3: the user sampling stage, the user sampling stage is used for the closed loop of finished product delivery and inspection tasks.

According to an embodiment of the present invention, the specific method of step 3 is shown in Figure 4:

Step 301: The user submits an application for sample collection;

Step 302: query the ERP system according to the sampling conditions;

Step 303: If the checked sample has completed the aging screening and detection work, the ERP system and the three-dimensional warehouse update the warehouse task information;

Step 304: According to the sample receiving information, print the paper certificate uniformly, and seal it automatically;

Step 305: The warehouse receives the ERP finished product delivery information, and transports the finished product to the reception hall through the AGV;

Step 306: The user receives the sample, and the process is completed.

Obviously, those skilled in the art can make various changes and modifications to the invention without departing from the spirit and scope of the invention. Thus, provided that these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (10)

1. The utility model provides an intelligent production management system that detects of components and parts which characterized in that includes: the system comprises a command and dispatching system center, a scientific research and production management system, an Internet of things system platform, a detection and production unit and a data center; wherein:

the command scheduling system center is used for realizing command scheduling of each dimension intelligent detection demonstration line and graphical display and analysis of real-time data;

the scientific research production management system is used for realizing scheduling, production scheduling and execution control of component operation plans;

the Internet of things system platform is used for establishing a communication mechanism between equipment and a system, realizing intelligent interconnection of Internet of things equipment, heterogeneous system integration, data acquisition, transmission, storage, query and data analysis, dynamically monitoring the running state of the equipment and early warning abnormal conditions in real time;

the detection production unit comprises an intelligent logistics module and an automatic detection module; wherein,

the intelligent logistics module is used for realizing automatic guidance of an AGV running track, AGV running speed and direction control, AGV operation node automatic addressing RFID, AGV automatic stopping timing, AGV running state feedback, AGV running fault detection and alarm and AGV automatic collision avoidance and alarm functions through wireless communication management and information transmission and analysis;

the automatic detection module is used for carrying out preliminary detection before screening and final detection after screening of the components;

and the data center is used for processing the data of the scientific research production management system and the Internet of things system platform.

2. The system for intelligently detecting, producing and managing components according to claim 1, wherein each dimension comprises: the system comprises a first dimension and a second dimension, wherein the first dimension is a process dimension and is used for checking task execution processes, historical data analysis and statistical analysis information, and is mainly oriented to scheduling, screening group leader and common screening technicians; and the second dimension is a time dimension, the task execution data of each key time node is displayed through a time shaft, and the dimension mainly faces departments and the leaders of the supervisors.

3. The system for intelligently detecting, producing and managing components and parts as claimed in claim 1, wherein the automatic detection module comprises an appearance defect automatic detection sub-module and a comprehensive parameter automatic detection sub-module; the appearance defect detection and inspection submodule detects the appearance defects of the ceramic dielectric capacitor through a machine vision technology; the comprehensive parameter automatic detection submodule is used for automatically detecting the appearance, capacity precision, loss, insulation resistance, medium voltage resistance and other parameters of the components.

4. The system for intelligently detecting, producing and managing components and parts as claimed in claim 1, wherein the intelligent logistics system comprises an automatic storage module and an intelligent distribution module; the automatic storage module is in butt joint with task management, flow management, operation monitoring, operation execution and the scientific research and production management system issued by the Internet of things platform through an interface.

5. The system for intelligently detecting, producing and managing components according to claim 4, wherein the automated warehousing module comprises an automated vertical warehouse warehousing management module and an AGV task management module;

the automatic vertical warehouse storage management module is used for warehouse state management, warehouse entry and exit action execution management, warehouse entry management, warehouse exit management, billboard visual management, warehouse information query management and the like of components;

the AGV task management module is used for calling, task inquiry, state inquiry, task clearing, running path optimization planning and the like of the AGV.

6. The system for the intelligent detection, production and management of components and parts as claimed in claim 1, wherein the data center further comprises a Hadoop data platform; the Hadoop data platform is used for constructing a big data analysis platform of a production operation plan, storage information, test data and MES system historical data.

7. An intelligent detection production management method for components is characterized by comprising the following steps:

step 1: a detection preparation stage, wherein the detection preparation stage is used for creating a detection task and distributing a corresponding stock position;

step 2: the detection stage is used for detecting the distribution, execution, exit and entry of tasks;

and step 3: and a user sample receiving stage, wherein the user sample receiving stage is used for closed loop of ex-warehouse and detection tasks of finished products.

8. The intelligent component detection, production and management method according to claim 7, wherein the step 1 specifically comprises:

step 101: the business department receives the sample box, the manufacturer two-dimensional code is attached to the lower right corner of the sample box, business personnel scan the two-dimensional code, relevant information is input into the ERP system, and a management platform account is generated;

step 102: the components are changed into a standard material box of a stereoscopic warehouse from a manufacturer material box;

step 103: printing a task sheet with a production task information two-dimensional code through a corresponding functional module of the ERP, and placing the task sheet on a material box;

step 104: an AGV trolley conveys the material box to a three-dimensional warehouse;

step 105: moving the material box from the AGV to a vertical warehouse conveying platform, scanning the two-dimensional code and the RFID by a scanner to obtain component information and logistics information, setting related warehouse location information on a management software interface, and returning the related information to an ERP system after determining;

step 106: and moving the material boxes to a stacker, placing the material boxes on the stacker, starting the stacker to move the material boxes to a corresponding storage position, and stacking the material boxes into the storage position.

9. The intelligent component detection, production and management method according to claim 7, wherein the step 2 specifically comprises:

201. the appearance detection station receives an ERP task entrust prompt, clicks to accept, clicks an AGV calling system to send goods receiving and discharging information to the vertical warehouse, and sends the component to be detected to the corresponding detection station through the AGV;

202. acquiring initial measurement data and transmitting the initial measurement data to a big data analysis platform through an automatic appearance defect and comprehensive parameter detection device;

203. the management information and the control information generated in the detection process are subjected to data communication through the ERP and the Internet of things platform;

204. after high-temperature storage and temperature impact test, acquiring screened detection data and transmitting the screened detection data to a big data analysis platform by an automatic detection device for appearance defects and comprehensive parameters;

205. and the mass analysis platform performs mass analysis on the batch detection target.

10. The intelligent component detection, production and management method according to claim 7, wherein the step 3 specifically includes:

step 301: a user submits a sample receiving application;

step 302: inquiring an ERP system according to the sampling condition;

step 303: if the checked sample finishes the aging screening detection work, the ERP system and the stereoscopic warehouse update the warehouse task information;

step 304: uniformly printing paper certificates according to the sample information, and automatically stamping;

step 305: the vertical warehouse receives the ERP finished product ex-warehouse information and transports the finished product to a reception hall through an AGV;

step 306: and (5) the user receives the sample and the process is finished.