Automatic continuous feeding system for electroplated terminal coiled materials

Abstract

The invention relates to the technical field of electroplating production, and discloses an electroplating terminal coiled material automatic continuous feeding system which comprises an automatic feeding module used for automatically conveying an electroplating terminal coiled material from a storage position to an electroplating production line; the intelligent sensor and detection module is used for monitoring the supply condition of the electroplating terminal coiled material and parameters of tension and pressure in the feeding process in real time and sending out an alarm signal when an abnormal condition occurs; and the material control and monitoring module is used for managing the inventory of the coiled materials in real time and automatically dispatching the materials according to requirements in the production process. Through automatic feeding, intelligent sensor monitoring, accurate material scheduling and real-time data analysis, the automation degree and the production efficiency of the electroplating terminal production line are remarkably improved, the system can accurately control material supply, material waste is avoided, stable operation of the production line is achieved, manual intervention is reduced, resource use is optimized, and the production cost is reduced. And the overall production efficiency and economic benefits are improved.

Description

Technical Field

[0001] The invention relates to the technical field of electroplating production, in particular to an automatic continuous feeding system for electroplated terminal coils. Background Art

[0002] With the acceleration of the intelligentization process of the manufacturing industry, automation technology has been widely used in various production lines, especially in the fields of electroplating, stamping, etc. Most of the existing electroplating terminal production lines use manual or semi-automatic methods to supply coils to the production line on demand.

[0003] In the prior art, the supply of electroplated terminal coils relies on manual or simple conveying systems, and the coils are delivered to the production line by mechanical means. The system is unable to accurately schedule and monitor materials, and the material supply process is discontinuous and unstable, causing the production line to stagnate in some cases, or even interrupt production due to insufficient material supply. In addition, the traditional system lacks real-time monitoring functions and cannot respond to abnormalities in the production process in a timely manner, resulting in more manual intervention and the inability to guarantee the efficiency and stability of production. Due to the inaccurate material supply, there is often too much or too little material in the production process, which further leads to material waste or reduced production efficiency, affecting the overall economic benefits of production. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides an automatic continuous feeding system for electroplated terminal coils, which solves the problems of serious material waste, low production efficiency and excessive manual intervention in the prior art.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an automatic continuous feeding system for electroplated terminal coils, comprising: Automatic feeding module, used to automatically transport electroplated terminal coils from the storage location to the electroplating production line; Intelligent sensors and detection modules are used to monitor the supply of electroplated terminal coils, the tension and pressure parameters during the feeding process in real time, and send out alarm signals when abnormal conditions occur; The material control and monitoring module is used to manage the inventory of coils in real time and automatically dispatch materials according to demand during the production process; the production scheduling and control system is used to adjust the feeding strategy according to the production plan and monitor the production status in real time; The data management and analysis platform is used to collect, store and analyze various types of data in the production process to support real-time decision-making and production optimization.

[0006] Preferably, the automatic feeding module comprises: A conveyor belt device, driven by an electric motor, automatically conveys the electroplated terminal coils from the storage location to the production line; Robotic arms or intelligent fixtures are used to precisely dock the coils and ensure accurate positioning and delivery of the coils during the feeding process.

[0007] Preferably, the intelligent sensor and detection module include: Material monitoring sensors, used to monitor the location and status of coils in real time through RFID or infrared sensing technology; Tension and pressure sensors are used to monitor the tension and pressure of the coil in real time during the feeding process; Automatic alarm device, which automatically sends out an alarm signal when it detects feed interruption, material shortage or equipment failure.

[0008] Preferably, the material control and monitoring module includes: Automated warehousing system for storing and managing electroplated terminal coils and dispatching materials based on real-time demand; The inventory monitoring device uses IoT technology and sensors to monitor inventory status in real time and promptly reminds of material requirements during the production process.

[0009] Preferably, the production scheduling and control system includes: The artificial intelligence-based production scheduling algorithm is used to dynamically optimize the production task scheduling and adjust the feeding strategy according to the production plan; the production status monitoring system is used to track the operating status of the electroplating production line in real time.

[0010] Preferably, the data management and analysis platform includes: Big data platform, used to collect various data in the production process in real time, including feeding status, equipment operation status, and material consumption; Data analysis and visualization tools are used to analyze production data in real time and generate decision support reports to assist production scheduling and management decisions.

[0011] Preferably, the intelligent sensor and detection module further comprises: Infrared sensors are installed at key locations along the feeding path to accurately monitor the position of the coil during feeding; Machine vision system for automated inspection of electroplated terminal coils.

[0012] Preferably, the production scheduling and control system further comprises: Production task management module, used to manage production tasks according to production orders and scheduling plans; The abnormal monitoring and processing system is used to monitor abnormal situations in production in real time and automatically adjust production tasks and scheduling strategies.

[0013] Preferably, the data management and analysis platform further includes: Data storage module, which uses cloud computing platform to store production data and provides backup and recovery functions for historical data; The data mining module provides suggestions for optimizing production processes and scheduling strategies by mining and analyzing historical production data.

[0014] Preferably, the material control and monitoring module calculates the supply amount of the coil by the following formula: Among them, M(t) is the material demand at time t, R(τ) represents the current supply status of the material, λ(τ) is the failure rate, μ(τ) is the load status of the equipment, and θ is the preset minimum supply threshold to ensure the stability and accuracy of material supply.

[0015] The present invention provides an automatic continuous feeding system for electroplated terminal coils. It has the following beneficial effects: 1. The present invention realizes automatic and continuous feeding of electroplated terminal coils through the integration of automatic feeding, intelligent sensors and material scheduling systems, greatly improves production efficiency, continuously and stably provides materials for the production line, greatly shortens the production cycle, and improves overall production efficiency.

[0016] 2. Through the real-time monitoring system and intelligent scheduling algorithm, the present invention can accurately adjust the material supply according to production needs, avoiding excessive or insufficient material supply, thereby effectively reducing material waste, reducing resource waste in the production process, and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Example: Please refer to the attached Figure 1 The embodiment of the present invention provides an automatic continuous feeding system for electroplated terminal coils, comprising: Automatic feeding module, used to automatically transport electroplated terminal coils from the storage location to the electroplating production line; In this embodiment, the automatic feeding module is used to automatically transport the electroplated terminal coils from the storage location to the electroplating production line. This module is the core component of the automatic continuous feeding system for electroplated terminal coils. Its main function is to ensure that the materials can be stably and continuously supplied to the production line, reduce manual intervention, and improve production efficiency and accuracy. To achieve this goal, this module uses an electric motor-driven conveyor belt system and a precisely controlled robotic arm or intelligent fixture to ensure accurate conveying and positioning of the coils.

[0020] As an option, the conveyor belt device in the automatic feeding module includes a variable frequency controlled electric motor, which can dynamically adjust the speed of the conveyor belt according to the needs of the production line. Specifically, the conveyor belt driven by the electric motor can be controlled by a frequency converter to achieve flexible adjustment to meet the requirements of material supply and conveying rate in different production stages. Through this control method, the feeding speed can be adjusted in real time according to the actual load of the production line and the needs of the material, ensuring the stability of material supply and efficient operation of the production line.

[0021] In one possible implementation, the coil positioning and feeding device achieves precise docking of the coil through a robotic arm or intelligent fixture. Specifically, the robotic arm or fixture is controlled by a servo motor, which can achieve precise positioning and clamping to prevent the coil from being misplaced or slipped during the feeding process. This design can ensure that the coil is accurately fed into the production line, avoiding production stagnation caused by misplacement or falling off.

[0022] For example, the frequency conversion controller is combined with the robot positioning system to dynamically adjust the working state of the feeding system according to the length of the coil, production speed and material demand during the production process. For example, during the production process, the frequency conversion controller adjusts the speed of the conveyor belt according to the current production load to ensure that the feeding system can adapt to the different needs of the production line. At the same time, the robot positioning system can accurately position the coil through a visual sensor or a laser positioning device to avoid errors and ensure the continuity of production.

[0023] It should be noted that the dynamic adjustment mechanism in the automatic feeding module can realize intelligent feedback control in the material supply process through the coordinated work of the frequency converter and the robot arm. Through the real-time feedback system, the feeding device can automatically adjust the working speed according to the actual load of the production line to ensure the continuous supply of coils during the production process, avoiding low production efficiency or production line stagnation due to too much or too little material.

[0024] In this embodiment, in order to further improve the reliability and stability of the system, the automatic feeding module is also equipped with monitoring sensors, which can monitor the running status of the conveyor belt, the position and speed of the coil in real time. When the system detects that the conveyor belt deviates from the set path or the coil is misplaced, blocked or other abnormal conditions, the sensor will promptly send out an alarm signal and start the correction operation through the automatic scheduling system. Specifically, in the case of coil misplacement or conveyor belt abnormality, the control system can automatically adjust the position of the robot arm or the conveyor belt speed to restore the normal operation of the system.

[0025] It is understandable that in the automatic feeding module, the frequency converter, robotic arm, monitoring sensor and other equipment form a collaborative working mechanism to ensure the efficiency, stability and accuracy of material supply. Through this modular design, the system can adapt to different types of production lines and support fast and flexible production task scheduling.

[0026] In one possible implementation, the system can also be linked with other modules of the production line through the Internet of Things technology, and the production status and material demand data can be transmitted to the data management platform in real time to provide data support for production scheduling and quality control. Through the Internet of Things technology, the data transmission between the automatic feeding module and the production line is smoother, the production status can be monitored and adjusted in real time, and the automation level of the system is further improved.

[0027] In the present invention, the supply of materials is dynamically adjusted by the following formula: Among them, M(t) represents the material demand at time t, R(τ) is the current supply status of the material, reflecting the adequacy of the supply; λ(τ) is the failure rate, indicating the possible failure conditions in the system; μ(τ) is the load status of the equipment, indicating the current workload of the production line; θ is the preset minimum supply threshold, ensuring that the minimum material supply can be guaranteed even when the production load is high.

[0028] Through this formula, the system can intelligently adjust the material supply according to the real-time demand and load of the production line, thereby ensuring the accuracy and continuity of material supply during the production process. This mechanism effectively avoids the situation of excessive or insufficient materials, thereby improving production efficiency and reducing material waste during the production process.

[0029] In this embodiment, the design of the automatic feeding module fully considers the load fluctuation of the production line and the dynamic changes of material demand, ensuring that the entire system can respond in real time during the production process and make precise adjustments. This precise adjustment mechanism can effectively improve the automation level and production efficiency of the production line, and provide strong technical support for the realization of intelligent manufacturing.

[0030] Intelligent sensors and detection modules are used to monitor the supply of electroplated terminal coils, the tension and pressure parameters during the feeding process in real time, and send out alarm signals when abnormal conditions occur; In this embodiment, the intelligent sensor and detection module is used to monitor the supply of electroplated terminal coils in real time and accurately measure the tension, pressure, position and other key parameters of the coils during the feeding process. Through the application of this module, the accuracy and stability of the material supply process can be ensured, and the stagnation of the production line caused by material mismatch or equipment failure can be avoided, thereby improving the continuity and automation of production.

[0031] As an option, the material monitoring sensor uses RFID technology and infrared sensors to wirelessly monitor the electroplated terminal coils in real time. Specifically, the RFID tag is installed on the coil, and every time the coil passes the sensor, the sensor automatically reads the position information of the coil and transmits it to the central control system. This technology can effectively avoid the situation where the production line is stopped due to the misalignment or shortage of coils, and adjust the production process through system feedback information.

[0032] In one possible implementation, tension and pressure sensors are installed at key locations of the conveyor belt system to monitor the tension and pressure status of the coil during the feeding process in real time. Specifically, the tension sensor can detect changes in the tension of the coil to ensure that the tension of the coil is maintained within a predetermined range during the feeding process. The pressure sensor monitors the pressure of the coil on the conveyor belt to prevent the coil from breaking or slipping due to excessive tension or low pressure. When an abnormality is detected, the sensor will send an alarm signal to prompt the system or operator to make adjustments or repairs. Through this monitoring system, the working status of the machine can be adjusted in time when the material is abnormal to ensure the stable progress of the production process.

[0033] For example, the design of sensor feedback and adjustment mechanism allows the system to take automatic actions when an abnormality occurs. For example, when the system detects that the tension of the material exceeds the predetermined range, the sensor will immediately transmit data to the central control system, and the system will automatically adjust the speed of the conveyor belt or the position of the robot arm according to the set control algorithm to ensure that the tension of the coil returns to the normal range. In addition, when the pressure sensor detects too low pressure, it will trigger the automatic adjustment mechanism to increase the pressure of the coil on the conveyor belt to prevent the coil from slipping, thereby ensuring the accuracy of feeding.

[0034] It should be noted that the automatic alarm device is combined with the intelligent sensor. When a fault or abnormal situation occurs, it can not only sound an alarm, but also upload the data to the data management platform for remote monitoring and data analysis. The automatic alarm device can provide real-time feedback on problems such as interruptions in the coil supply process, material shortages or system failures, and provide operators with timely early warning information, thereby reducing human intervention and improving the safety and stability of the production line.

[0035] In this embodiment, the real-time data feedback of the intelligent sensor and the detection module enables the system to accurately monitor the entire material supply process and ensure the smooth execution of the production task. Through seamless integration with the automatic feeding module, material control and monitoring module and other systems, the intelligent sensor can not only provide real-time feedback on the status of the coil, but also provide accurate data support for the production scheduling system, so that the material supply and production plan can be dynamically adjusted, further optimizing the overall performance of the production line.

[0036] It is understandable that the implementation of this formula relies on the intelligent sensors to continuously provide accurate real-time data, including tension, pressure, speed, equipment status, etc. This data is fed back to the production scheduling system, and the system can dynamically adjust the material supply based on this information to ensure the precise match between supply and production tasks. This kind of feedback mechanism effectively avoids overfeeding or material shortage, reduces waste in the production process, and improves production efficiency.

[0037] In an extended implementation, the intelligent sensor and detection module can also be linked with other production line equipment to further optimize production scheduling. For example, when a certain part of the equipment is detected to be faulty, the sensor can notify the maintenance personnel through the system to carry out maintenance and adjust the production tasks to ensure the efficient and stable operation of the production line. This kind of cross-device collaboration and automatic adjustment mechanism greatly enhances the flexibility and intelligence level of the entire production system.

[0038] In summary, the intelligent sensor and detection module of the present invention not only ensures the stability of the supply of electroplated terminal coils through high-precision sensing technology, real-time monitoring and automatic adjustment functions, but also optimizes the overall efficiency of the production line through data feedback and dynamic adjustment, further improving the system's automation level and production quality.

[0039] Material control and monitoring module, used to manage coil inventory in real time and automatically dispatch materials according to demand during the production process; In this embodiment, the main function of the material control and monitoring module is to monitor and dispatch the inventory of electroplated terminal coils in real time, and automatically adjust the material supply according to production needs to ensure the accurate supply of materials during the production process. This module effectively realizes the precise management of materials by combining the automatic warehousing system, material dispatching system and sensor feedback mechanism, avoiding production stagnation or waste caused by material shortage or excess.

[0040] As an option, the automatic storage system consists of multiple storage units and automated transmission equipment that can automatically extract materials and deliver them to the production line according to demand. Specifically, the automatic storage system uses sensors and RFID technology to achieve inventory management. Whenever a coil is sent out, the system automatically records the outbound information through the RFID tag and updates the inventory status. The system can automatically initiate a replenishment request when the material inventory is insufficient to ensure that the production process is not interrupted.

[0041] In one possible implementation, the material scheduling system is closely integrated with the production scheduling system, using production tasks and production line load information to automatically calculate and allocate different types of coils to the production line. Specifically, the material scheduling system automatically allocates materials based on production progress and material requirements through intelligent scheduling algorithms. The system dynamically adjusts the order and quantity of material distribution based on the actual load of the production line and current inventory to ensure that the materials required for production are in place on time.

[0042] For example, the material control and monitoring module is also equipped with a real-time monitoring function. Through sensors installed in various links of the production line, the material status data is collected in real time, including the remaining amount of coils, current supply status, and equipment status. These data communicate with the central control system through the Internet of Things (IoT) technology to ensure that the inventory management system can obtain material information in real time. When the system detects insufficient materials or abnormal equipment, the system will trigger an alarm and start a backup plan to ensure the stability and continuity of production.

[0043] It should be noted that the material demand calculation formula dynamically adjusts the material supply through an accurate mathematical model to ensure that the material supply accurately matches the production demand. Specifically, the material supply calculation formula is as follows: Among them, M(t) represents the material demand at time t, D(t) is the production demand at that time, S(t) is the current inventory, and Q(t) is the unit material consumption. This formula is calculated based on the real-time inventory status and production demand, and can dynamically adjust the accuracy of material supply to ensure that the adequacy of material supply matches production demand.

[0044] It is understandable that this formula can adjust the material supply according to real-time data. Specifically, the real-time data collected by the sensor is fed back to the material scheduling system, which uses this data to dynamically adjust the material supply to avoid too much or too little material supply. The system will adjust the time, quantity and sequence of material delivery according to the real-time status and load conditions of the production line to ensure the accurate supply of materials during the production process.

[0045] In this embodiment, the combination of the automatic warehousing system and the material dispatching system ensures efficient management and accurate supply of materials. Through the integration of Internet of Things technology and the automated control system, the inventory and distribution status of materials can be monitored in real time, further reducing human errors and management costs. It should be noted that the system also has fault self-recovery capabilities. Once a transmission failure or sensor abnormality occurs, the system can automatically switch to the backup mode to ensure that the material supply is not affected and avoid production interruptions.

[0046] For example, the real-time inventory monitoring function allows operators to view real-time inventory status through the management platform and make flexible adjustments based on production needs. For example, when the order production demand changes, the material scheduling system can automatically calculate the optimal material allocation plan based on the adjusted production plan, and schedule materials in real time through IoT devices to ensure the efficient operation of the production line.

[0047] In an extended implementation, the material control and monitoring module can also be combined with a big data analysis platform to achieve in-depth analysis of historical data. By analyzing data such as material usage and inventory change trends during the production process, the system can predict future material demand and arrange material procurement and distribution in advance, thereby avoiding material surplus or shortage and further optimizing the utilization of production resources.

[0048] In addition, the optimal control of inventory management can achieve optimal inventory allocation through the following formula: Among them, Z is the optimization target of the material scheduling system, C i represents the unit cost of the i-th material, x i is the scheduling quantity of materials, S i is the available inventory of the material. This formula optimizes the inventory management and scheduling of materials by solving the minimum cost or maximum benefit, further reducing the phenomenon of excess inventory and material waste.

[0049] In summary, the material control and monitoring module of the present invention effectively improves the accuracy and stability of the supply of electroplated terminal coils through automated warehousing, precise material scheduling, real-time monitoring and data feedback mechanisms, reduces resource waste in production, and improves production efficiency. With the support of intelligent algorithms and real-time data, this module can dynamically adjust the material supply and work in conjunction with the production scheduling system to achieve efficient and stable operation of the production line.

[0050] Production scheduling and control system, used to adjust the feeding strategy according to the production plan and monitor the production status in real time; In this embodiment, the production scheduling and control system is one of the key modules of the automatic continuous feeding system for electroplated terminal coils. It is mainly used to dynamically adjust the production task scheduling and material supply according to production demand and equipment status to ensure the efficient operation of the production line. The system realizes comprehensive scheduling and optimization of the production process by integrating intelligent algorithms, real-time data feedback and production progress monitoring functions.

[0051] As an option, the production scheduling and control system adopts a scheduling algorithm based on artificial intelligence (AI). Specifically, the system automatically calculates and generates the optimal production scheduling plan by analyzing factors such as the priority of production tasks, the status of material supply, and the load of equipment. This scheduling plan can adapt to changes in the load of the production line in real time, intelligently adjust the production rhythm, and ensure the efficient operation of the production line. The AI ​​scheduling algorithm can monitor the status of equipment in real time during the production process, determine the availability of equipment, and adjust the schedule of production tasks according to real-time needs. For example, when an equipment fails, the system can automatically adjust the production task and prioritize other available equipment to avoid stagnation of the production line.

[0052] In one possible implementation, the production scheduling and control system shares data with the material control and monitoring module and the automatic feeding module. Specifically, the production scheduling system works together with the material scheduling system to update material requirements and adjust supply strategies in real time. Through this seamless integration, the production scheduling system can adjust material distribution routes and scheduling priorities based on real-time inventory data, production tasks, and production loads, thereby ensuring that materials are supplied to the production line on demand and accurately, avoiding material shortages or oversupply.

[0053] For example, the real-time monitoring and feedback mechanism in the production scheduling and control system collects key data of the production line (such as production progress, equipment status, material supply, etc.) through sensors and data acquisition devices. These data are transmitted to the central control system in real time as a basis for scheduling decisions. When the system detects production interruptions, equipment failures, or material shortages, the scheduling system will automatically adjust the production plan and take appropriate corrective measures. For example, if an equipment failure occurs in a certain production link, the scheduling system can adjust the task priority, postpone the tasks of the failed link, and prioritize scheduling other equipment for production to avoid a complete stagnation of production.

[0054] It should be noted that the production scheduling optimization formula is the core of intelligent scheduling. In order to ensure the optimal scheduling of production tasks, the system dynamically calculates the optimal scheduling plan through the following formula based on factors such as real-time production demand, equipment load and production task priority: Among them, Z represents the optimization goal of production scheduling, P i is the priority of the ith task, T i is the task completion time, C i is the cost of the production task, x i is the production volume of the task. The optimization goal of this formula is to minimize the weighted sum of the completion time and cost of the production task to ensure that the production task can be completed efficiently and economically.

[0055] It is understandable that the production scheduling system can dynamically calculate the priority, scheduling time and production cost of tasks by applying this optimization formula, and adjust the production plan based on real-time data. This mechanism can dynamically adjust the order and execution time of production tasks according to different production needs and equipment status, thereby improving production efficiency and reducing production costs.

[0056] In this embodiment, the production status monitoring module works closely with the production scheduling system to track every link on the production line in real time to ensure that the production task is carried out smoothly as planned. The monitoring module collects data such as equipment status, material consumption, and production progress in real time, and optimizes the production scheduling in real time based on these data. For example, if the load of a certain device is detected to be too large, the system will automatically adjust the load of other devices to ensure the smooth completion of the production task.

[0057] In an extended implementation, the production scheduling and control system can also be connected to the big data analysis platform. By analyzing historical production data, the system can predict future production needs and adjust the production plan based on these predictions. Specifically, the production scheduling system can predict production bottlenecks based on historical production data and take measures in advance to reduce the risk of production delays and equipment failures. For example, if the data analysis platform finds that bottlenecks often occur in certain production links, the system can adjust the production plan in advance and optimize the tasks of the bottleneck links to avoid production stagnation.

[0058] In summary, the production scheduling and control system of the present invention ensures the efficient operation of the electroplating terminal production line through intelligent scheduling algorithms, real-time monitoring and data feedback mechanisms, and production task optimization formulas. By working in collaboration with other modules, the production scheduling and control system can adjust production plans and material supplies in real time, avoid production line stagnation, and improve production efficiency and resource utilization. Through big data analysis and real-time feedback, the system not only optimizes production scheduling, but also provides strong support for future production task adjustments and decision-making, further improving the automation and intelligence level of the overall production line.

[0059] The data management and analysis platform is used to collect, store and analyze various types of data in the production process to support real-time decision-making and production optimization.

[0060] In this embodiment, the data management and analysis platform is the core component of the automatic continuous feeding system for electroplated terminal coils, and is mainly used to collect, store, analyze and visualize the data generated during the entire production process. The platform realizes the comprehensive management of production data and provides decision support for production scheduling, quality control and equipment maintenance through big data analysis technology, thereby effectively improving production efficiency and resource utilization.

[0061] As an option, the data management and analysis platform collects and interacts with various modules (such as automatic feeding module, intelligent sensor and detection module, material control and monitoring module, etc.) through the Internet of Things (IoT) technology. Specifically, the platform collects data from all links of the production line in real time, including material supply, production progress, equipment status, inventory status, sensor feedback, etc., and uploads this data to the cloud for storage. Through data aggregation, the platform can monitor every link in the production process in real time and provide comprehensive production data reports.

[0062] In one possible implementation, the big data analysis module is the core of the data management and analysis platform, responsible for processing and analyzing the collected production data. Specifically, this module uses data mining algorithms to conduct in-depth analysis of historical production data, identify production bottlenecks, resource waste points and potential problems, and provide data support for production optimization. For example, by analyzing historical production data, the system can predict the failure probability of a certain production link, so as to perform equipment maintenance in advance and avoid downtime failures.

[0063] For example, the data visualization function makes the data in the production process more intuitive. The data management and analysis platform presents real-time data through charts, dashboards, etc., helping operators and managers better understand the production status and operational efficiency. Through the visualization of key production indicators (such as production progress, equipment operation status, material consumption, etc.), operators can more quickly identify production anomalies and make timely adjustments, thereby improving the response speed and flexibility of production.

[0064] It should be noted that data storage and backup mechanisms are key components to ensure data security. The data management and analysis platform uses an efficient cloud storage solution to store production data in the cloud and perform regular backups to ensure data security and recoverability. By using distributed storage technology, the platform can store data synchronously on multiple servers, improving data storage reliability and reading speed.

[0065] In this embodiment, the data analysis and optimization algorithm can be dynamically adjusted according to the real-time collected production data. For example, when the sensor detects that the equipment is overloaded, the data management platform will analyze the historical operation data of the equipment and predict the possible failure time of the equipment through the optimization algorithm. The system will automatically adjust the production task scheduling or notify the maintenance personnel in advance to conduct equipment inspections, thereby reducing the impact of equipment failures on the production line.

[0066] It is understandable that the data management and analysis platform can provide optimization suggestions for the entire production process through powerful data analysis and intelligent decision-making capabilities. Specifically, the platform can automatically adjust the production plan and optimize the production process through real-time analysis of production line data combined with the decision-making logic of the intelligent scheduling system. Through this closed-loop feedback mechanism, each link of the production process can be adjusted according to real-time data, thereby improving production flexibility and responsiveness.

[0067] For example, the production forecasting module is an important part of the data management and analysis platform. This module uses machine learning algorithms to model historical production data and predict future production demand, equipment failures, and material consumption. Specifically, the production forecasting module can predict future production bottlenecks based on historical data, and adjust production scheduling based on the prediction results, prepare materials or perform equipment maintenance in advance, and avoid production delays and downtime.

[0068] In an extended implementation, artificial intelligence (AI) and deep learning algorithms can be further applied to data management and analysis platforms. Through deep learning technology, the platform can extract potential patterns from massive production data and perform more accurate production forecasts and resource optimization. Compared with traditional analysis methods, AI-based algorithms can provide more accurate production optimization suggestions in a shorter time, greatly improving the intelligence level of the system.

[0069] It should be noted that the security and privacy protection of production data are also key considerations for the data management and analysis platform. The platform uses multiple encryption technologies to protect sensitive data, such as equipment operating parameters and production scheduling data, to prevent data from being stolen or tampered with during transmission. At the same time, the platform also sets up a user rights management mechanism to ensure that only authorized users can access sensitive data.

[0070] In this embodiment, the data-driven decision support function provides production managers with a data-based decision basis. Specifically, the platform can generate regular reports based on data such as production progress, equipment status, and material supply to help managers understand the operating status of the production line and make adjustment decisions. For example, when the system detects a bottleneck in a certain link, the platform can provide real-time feedback and suggest managers to make corresponding production adjustments or equipment optimization.

[0071] In summary, the data management and analysis platform of the present invention greatly improves the transparency and control ability of the production process through comprehensive data collection, real-time analysis and intelligent decision-making functions. Through in-depth mining and intelligent analysis of historical data, the platform provides strong data support for production scheduling, equipment maintenance, quality control and other aspects, and improves the automation and intelligence level of the production line. Through integration with other modules, the data management and analysis platform can provide accurate optimization solutions for the production process and ensure efficient and stable operation of the entire production process.

[0072] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Automatic continuous feeding system for electroplated terminal coils, characterized by: include: Automatic feeding module, used to automatically transport electroplated terminal coils from the storage location to the electroplating production line; Intelligent sensors and detection modules are used to monitor the supply of electroplated terminal coils, the tension and pressure parameters during the feeding process in real time, and send out alarm signals when abnormal conditions occur; Material control and monitoring module, used to manage coil inventory in real time and automatically dispatch materials according to demand during the production process; Production scheduling and control system, used to adjust the feeding strategy according to the production plan and monitor the production status in real time; The data management and analysis platform is used to collect, store and analyze various types of data in the production process to support real-time decision-making and production optimization.

2. The automatic continuous feeding system for electroplated terminal coils according to claim 1 is characterized in that: The automatic feeding module comprises: A conveyor belt device, driven by an electric motor, automatically conveys the electroplated terminal coils from the storage location to the production line; Robotic arms or intelligent fixtures are used to precisely dock the coils and ensure accurate positioning and delivery of the coils during the feeding process.

3. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The intelligent sensor and detection module include: Material monitoring sensors, used to monitor the location and status of coils in real time through RFID or infrared sensing technology; Tension and pressure sensors are used to monitor the tension and pressure of the coil in real time during the feeding process; Automatic alarm device, which automatically sends out an alarm signal when it detects feed interruption, material shortage or equipment failure.

4. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The material control and monitoring module includes: Automated warehousing system for storing and managing electroplated terminal coils and dispatching materials based on real-time demand; The inventory monitoring device uses IoT technology and sensors to monitor inventory status in real time and promptly reminds of material requirements during the production process.

5. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The production scheduling and control system includes: The artificial intelligence-based production scheduling algorithm is used to dynamically optimize the production task scheduling and adjust the feeding strategy according to the production plan; the production status monitoring system is used to track the operating status of the electroplating production line in real time.

6. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The data management and analysis platform includes: Big data platform, used to collect various data in the production process in real time, including feeding status, equipment operation status, and material consumption; Data analysis and visualization tools are used to analyze production data in real time and generate decision support reports to assist production scheduling and management decisions.

7. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The intelligent sensor and detection module further comprises: Infrared sensors are installed at key locations along the feeding path to accurately monitor the position of the coil during feeding; Machine vision system for automated inspection of electroplated terminal coils.

8. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The production scheduling and control system further includes: Production task management module, used to manage production tasks according to production orders and scheduling plans; The abnormal monitoring and processing system is used to monitor abnormal situations in production in real time and automatically adjust production tasks and scheduling strategies.

9. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The data management and analysis platform also includes: Data storage module, which uses cloud computing platform to store production data and provides backup and recovery functions for historical data; The data mining module provides suggestions for optimizing production processes and scheduling strategies by mining and analyzing historical production data.

10. The automatic continuous feeding system for electroplated terminal coils according to claim 1, characterized in that: The material control and monitoring module calculates the supply of the coil by the following formula: Among them, M(t) is the material demand at time t, R(τ) represents the current supply status of the material, λ(τ) is the failure rate, μ(τ) is the load status of the equipment, and θ is the preset minimum supply threshold to ensure the stability and accuracy of material supply.

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