Intelligent system and method for efficient mistake proofing and precise management and control of manufacturing industry production materials

Abstract

The invention discloses a manufacturing industry production material intelligent management system and method, and the system comprises a data collection module, an analysis module, an early warning module, a display module, an intelligent scheduling module, a tracing module and an interaction module, the data collection module collects material data through a sensor and a radio frequency identification device, the analysis module analyzes the data through a machine learning algorithm, and the early warning module carries out the sound-light alarm and message pushing. The display module displays material information, the intelligent scheduling module optimizes material distribution, the tracing module records full-life-cycle information, the interaction module facilitates user operation, all the modules cooperate, and efficient mistake proofing and accurate management and control are achieved. The material identification accuracy is improved, the materials are accurately analyzed and controlled, efficient early warning is achieved, visual display and convenient interaction are achieved, full-life-cycle tracing is achieved, material circulation is intelligently dispatched and optimized, the production efficiency is improved, the product quality is guaranteed, the management cost is reduced, and powerful guarantee is provided for material management in the manufacturing industry.

Description

Technical Field

[0001] The present invention relates to the technical field of material control systems in manufacturing industry, and in particular to an intelligent system and method for efficient error prevention and precise control of production materials in manufacturing industry. Background Art

[0002] In the manufacturing industry, the management of production materials has always been a key issue. With the continuous development of the manufacturing industry and the advancement of intelligentization, traditional material management methods have gradually revealed many disadvantages.

[0003] For example, the invention patent with publication number CN110276584A and publication date 2019.09.24 discloses a technical solution: This application relates to a material search system, method, device and storage medium. In the material search system, each feeder holds the corresponding material; the feeder search device is provided with a material information table, which contains the mapping relationship between the material identification information of each material and the first Bluetooth module of the feeder; the processing unit of the feeder search device matches the Bluetooth ID from the material information table according to the acquired material identification information of the material to be shipped out, and based on the Bluetooth ID, instructs the second Bluetooth module to send a wireless signal to the first Bluetooth module of the corresponding feeder; the first Bluetooth module triggers the prompt device to give a prompt according to the wireless signal.

[0004] The invention patent with publication number CN109359903A and publication date 2019.02.19 discloses a material distribution method and system for an air-conditioning workshop based on an MES system, including: real-time monitoring of the download and generation of production orders and ingredient lists through the MES system, reviewing the ingredient lists, and publishing ingredient list information; the material preparer receives the ingredient list information, verifies the material preparation information, and arranges the distribution according to the capacity of the line-side warehouse; the material preparer completes the material preparation and sends a distribution request; the distribution staff receives the distribution request and starts to distribute materials to the workstation line-side warehouse, and the workstation line-side warehouse sends a received information after receiving the materials; when the remaining material quantity of the workstation line-side warehouse is reduced to the warning value, and the total material distribution quantity is less than the order demand, the workstation line-side warehouse alarms and sends a material urging information, and the MES system pushes the material urging information to the material warehouse, and re-executes step A03 until the order is completed.

[0005] What the above two comparative documents do not solve is:

[0006] On the one hand, in the material identification process, it often relies on manual identification or simple equipment, which has low recognition accuracy, slow speed, and is prone to errors. This not only leads to low production efficiency, but also may cause the use of wrong materials due to misidentification, affecting product quality.

[0007] On the other hand, the data analysis and control of materials lacks accuracy and efficiency. It is impossible to accurately determine whether materials are used incorrectly in a timely manner, and it is difficult to accurately plan and schedule the use of materials. At the same time, in terms of material traceability, traditional methods are difficult to achieve effective traceability throughout the entire life cycle. Once quality problems occur, it is difficult to quickly locate the source of the problem.

[0008] In addition, in terms of material display and interaction, existing systems are often not intuitive and convenient enough, making it difficult for users to quickly obtain real-time status information of materials, and it is not convenient to set parameters and operate them.

[0009] To sum up, the manufacturing industry urgently needs an intelligent management system and method for production materials with efficient error prevention and precise control to improve production efficiency, ensure product quality and reduce management costs. Summary of the invention

[0010] The present invention proposes an intelligent system and method for efficient error prevention and precise control of manufacturing production materials to solve the problems mentioned in the above-mentioned prior art.

[0011] In order to achieve the above purpose, the present invention adopts the following technical solution: an intelligent system for efficient error prevention and precise control of production materials in the manufacturing industry, comprising:

[0012] The data collection module is used to collect relevant data of production materials in real time, including material type, quantity, and location information. The data collection accuracy evaluation index formula is: Among them A dataAcq Indicates the accuracy of data collection, N cda Represents the number of data actually collected correctly, N tdp represents the total number of data that should be collected theoretically, n is the number of parameter types of collected data, and W pi represents the weight of the parameter, and i represents the number of interference data. This formula takes into account the importance of different parameters and the impact of interference data on accuracy, and more comprehensively evaluates the accuracy of data collection.

[0013] The data analysis module is connected to the data acquisition module and can analyze and process the collected material data, determine whether there are errors in the materials, and accurately control the use of the materials. The analysis accuracy evaluation index formula is: Among them A dataAn Indicates the analysis accuracy, N ca Indicates the number of correct analyses, N ta Represents the total number of analyses, N ad Represents the number of abnormal data. This formula considers the number of correct analyses and the total number of analyses, minus the impact of abnormal data on analysis accuracy, and concisely evaluates the performance of the data analysis module.

[0014] The display module is used to display the real-time status information and analysis results of the material. The display clarity evaluation index formula is: Among them C display Indicates display clarity, N rp Indicates the number of clearly distinguishable pixels, N tp Indicates the total number of pixels, N tp Represents the number of blurred pixels. This formula intuitively reflects the clarity of the display module by subtracting the ratio of blurred pixels to total pixels from the ratio of clearly discernible pixels to total pixels.

[0015] The traceability module can trace the entire life cycle of materials, record the information of each link from procurement, warehousing, use to scrapping, and facilitate problem tracing and quality control. The traceability integrity evaluation index formula is: Among them I traceability Indicates traceability integrity, N rsd Indicates the number of links recorded in detail, N tse Indicates the total number of links in the expected material life cycle, N ms Represents the number of missing links. This formula simply evaluates the performance of the traceability module by subtracting the ratio of missing links to the total number of links from the ratio of the number of recorded links to the total number of links.

[0016] The early warning module sends out an early warning signal when the data analysis module detects material errors or abnormalities. The evaluation indicator formula for the early warning response time is: Where T warnResp Indicates the warning response time, N w Indicates the number of warnings, T ri Indicates the response time of the first warning.

[0017] The intelligent scheduling module intelligently schedules materials based on the results of the data analysis module and the production plan, optimizes the material distribution path and time, and improves the material flow efficiency. The scheduling efficiency improvement factor formula is: Among them, F scheduling represents the scheduling efficiency improvement factor, E a represents the efficiency after intelligent scheduling, E b Indicates the efficiency without using intelligent scheduling.

[0018] The interactive module provides an interactive interface between the user and the system. The user can query material information, receive warning notifications, and set system parameters through this module. The interactive friendliness evaluation index formula is: Among them, F interaction Indicates the interaction friendliness, N usp Indicates the number of points of user satisfaction, N tp Indicates the total number of evaluation points.

[0019] Preferably, the data acquisition module includes a sensor component and a radio frequency identification device, the sensor component is used to collect physical parameters of the material, and the radio frequency identification device is used to identify a unique identifier of the material.

[0020] Preferably, the data analysis module includes a data processing unit and an algorithm unit, and the algorithm unit uses a machine learning algorithm to analyze and predict the material data.

[0021] Preferably, the early warning module includes an audible and visual alarm device and a message push unit, which can send early warning information to relevant personnel in a timely manner.

[0022] Preferably, the display module includes a display screen and a data visualization unit, which can display the status information and analysis results of the material in an intuitive manner.

[0023] Preferably, the intelligent scheduling module includes a path planning unit and a scheduling algorithm unit, which can efficiently schedule materials according to real-time conditions.

[0024] Preferably, the traceability module includes a database and a query unit, which can conveniently query the full life cycle information of the material.

[0025] Preferably, the interaction module includes an input unit and an output unit, the user can operate through the input unit, and the system feeds back information to the user through the output unit.

[0026] A method for efficient error prevention and precise control of manufacturing production materials, comprising the following steps:

[0027] The data acquisition module collects relevant data of production materials in real time.

[0028] The data analysis module is used to analyze and process the collected material data to determine whether there are any errors in the materials and to accurately control the usage of the materials.

[0029] When material errors or abnormal conditions are detected, the early warning module sends out an early warning signal.

[0030] The real-time status information and analysis results of the material are displayed through the display module.

[0031] The intelligent scheduling module intelligently schedules materials based on the results of the data analysis module and the production plan.

[0032] The traceability module traces the entire life cycle of materials.

[0033] Users interact with the system through the interactive module.

[0034] Preferably, in the data collection step, a sensor component is used to collect the physical parameters of the material, and a radio frequency identification device is used to identify the unique identifier of the material. In the data analysis step, the material data is processed by the data processing unit and the algorithm unit, and the algorithm unit uses a machine learning algorithm to analyze and predict the material data. In the early warning step, early warning information is sent to relevant personnel through an audible and visual alarm device and a message push unit. In the display step, the status information and analysis results of the material are displayed through a display screen and a data visualization unit. In the intelligent scheduling step, the material is efficiently scheduled through a path planning unit and a scheduling algorithm unit. In the tracing step, the full life cycle information of the material is queried through a database and a query unit. In the interactive step, the user operates through the input unit, and the system feeds back information to the user through the output unit.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. Improve material recognition accuracy

[0037] Through advanced sensor technology and image recognition technology, combined with multi-sensor fusion and deep learning algorithms, the recognition accuracy of production materials has been greatly improved. It can quickly and accurately identify the type, quantity and location of materials, providing a reliable data basis for subsequent management and control.

[0038] 2. Accurate data analysis and control

[0039] The data analysis module uses machine learning algorithms to conduct in-depth analysis of the collected material data, accurately determine whether there are errors in the materials, and accurately control the use of materials. Problems can be discovered and measures can be taken in a timely manner to avoid the expansion of errors and improve production quality.

[0040] 3. Efficient early warning mechanism

[0041] When material errors or abnormal conditions are detected, the early warning module can quickly send out early warning signals. Through the sound and light alarm device and message push unit, it ensures that relevant personnel can receive notifications in time, respond quickly, and reduce losses.

[0042] 4. Intuitive display and convenient interaction

[0043] The display module can display the real-time status information and analysis results of materials in an intuitive way, allowing users to quickly understand the material situation. The interactive module provides a convenient user interface, allowing users to easily query material information, receive warning notifications, and set system parameters, improving the ease of use of the system.

[0044] 5. Full life cycle traceability

[0045] The traceability module can trace the entire life cycle of materials, recording information from procurement, warehousing, use to scrapping. It is convenient for problem tracing and quality control. Once a quality problem occurs, the source of the problem can be quickly located, improving the efficiency of problem solving.

[0046] 6. Intelligent scheduling optimizes material flow

[0047] The intelligent scheduling module intelligently schedules materials based on data analysis results and production plans, optimizing material distribution routes and time, improving material flow efficiency, reducing inventory costs, and ensuring production continuity. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a schematic block diagram of an intelligent system for efficient error prevention and precise control of manufacturing production materials proposed by the present invention;

[0049] Figure 2 This is a schematic diagram of an intelligent method for efficient error prevention and precise control of production materials in the manufacturing industry proposed by the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments 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.

[0051] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0052] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0053] Reference Figure 1-2 : An intelligent system for efficient error prevention and precise control of manufacturing production materials, including:

[0054] The data collection module is used to collect relevant data of production materials in real time, including material type, quantity, and location information. The data collection accuracy evaluation index formula is: Among them A dataAcq Indicates the accuracy of data collection, N cda Represents the number of data actually collected correctly, N tdp represents the total number of data that should be collected theoretically, n is the number of parameter types of collected data, and W pi represents the weight of the parameter, and i represents the number of interference data. This formula takes into account the importance of different parameters and the impact of interference data on accuracy, and more comprehensively evaluates the accuracy of data collection.

[0055] The data analysis module is connected to the data acquisition module and can analyze and process the collected material data, determine whether there are errors in the materials, and accurately control the use of the materials. The analysis accuracy evaluation index formula is: Among them A dataAn Indicates the analysis accuracy, N ca Indicates the number of correct analyses, N ta Represents the total number of analyses, N ad Represents the number of abnormal data. This formula considers the number of correct analyses and the total number of analyses, minus the impact of abnormal data on analysis accuracy, and concisely evaluates the performance of the data analysis module.

[0056] The display module is used to display the real-time status information and analysis results of the material. The display clarity evaluation index formula is: Among them C display Indicates display clarity, Nrp Indicates the number of clearly distinguishable pixels, N tp Indicates the total number of pixels, N tp Represents the number of blurred pixels. This formula intuitively reflects the clarity of the display module by subtracting the ratio of blurred pixels to total pixels from the ratio of clearly discernible pixels to total pixels.

[0057] The traceability module can trace the entire life cycle of materials, record the information of each link from procurement, warehousing, use to scrapping, and facilitate problem tracing and quality control. The traceability integrity evaluation index formula is: Among them I traceability Indicates traceability integrity, N rsd Indicates the number of links recorded in detail, N tse Indicates the total number of links in the expected material life cycle, N ms Represents the number of missing links. This formula simply evaluates the performance of the traceability module by subtracting the ratio of missing links to the total number of links from the ratio of the number of recorded links to the total number of links.

[0058] The early warning module sends out an early warning signal when the data analysis module detects material errors or abnormalities. The evaluation indicator formula for the early warning response time is: Where T warnResp Indicates the warning response time, N w Indicates the number of warnings, T ri Indicates the response time of the first warning.

[0059] The intelligent scheduling module intelligently schedules materials based on the results of the data analysis module and the production plan, optimizes the material distribution path and time, and improves the material flow efficiency. The scheduling efficiency improvement factor formula is: Among them, F scheduling represents the scheduling efficiency improvement factor, E a represents the efficiency after intelligent scheduling, E b Indicates the efficiency without using intelligent scheduling.

[0060] The interactive module provides an interactive interface between the user and the system. The user can query material information, receive warning notifications, and set system parameters through this module. The interactive friendliness evaluation index formula is: Among them, F interaction Indicates the interaction friendliness, N usp Indicates the number of points of user satisfaction, N tp Indicates the total number of evaluation points.

[0061] In the present invention, the data acquisition module includes a sensor component and a radio frequency identification device, the sensor component is used to collect physical parameters of the material, and the radio frequency identification device is used to identify the unique identification of the material.

[0062] In the present invention, the data processing unit undertakes the important task of preliminary sorting and processing the collected material data. After the data acquisition module collects the relevant data of the production materials, the data processing unit will first clean the data to remove the noise and outliers to ensure the accuracy and reliability of the data. Then, the data processing unit will classify and archive the data, and sort them according to different attributes such as material type, quantity, location, etc. for subsequent analysis and processing. In addition, the data processing unit will also convert the format and standardize the data so that it can be smoothly read and analyzed by the algorithm unit.

[0063] The algorithm unit is the key to the data analysis module. It uses advanced machine learning algorithms to conduct in-depth analysis and prediction of material data. Machine learning algorithms have strong self-learning and adaptive capabilities, and can dig out potential rules and patterns from a large amount of material data. For example, by learning from historical material usage data, the algorithm unit can predict the demand trend of different materials in the future, providing a scientific basis for material procurement and inventory management. At the same time, the algorithm unit can also analyze the material data collected in real time to determine whether the material is used incorrectly. For example, when it is detected that the usage of a certain material exceeds the normal range, or the combination with other materials does not meet the preset rules, the algorithm unit will immediately issue an alarm to remind relevant personnel to check and handle it.

[0064] In terms of specific algorithm selection, the algorithm unit can use a variety of machine learning algorithms, such as decision tree algorithm, support vector machine algorithm, neural network algorithm, etc. These algorithms have their own characteristics and can be selected and combined according to different data analysis tasks and data characteristics. For example, the decision tree algorithm is suitable for handling classification problems and can quickly determine the category and status of materials; the support vector machine algorithm performs well on small sample data and is suitable for accurate analysis of key materials; the neural network algorithm has a strong nonlinear fitting ability and can mine complex material data relationships.

[0065] In the present invention, the early warning module is an important component to ensure production safety and material management efficiency. The early warning module is mainly composed of an audible and visual alarm device and a message push unit.

[0066] The sound and light alarm device is an intuitive and eye-catching early warning method. It usually consists of a flashing indicator light and a loud siren. When the system detects a material error or abnormal situation, the indicator light will flash quickly and emit a strong light signal to attract the attention of people around. At the same time, the siren will emit a high-decibel sound, such as a sharp whistle or a rapid beep, to ensure that it can be quickly detected by relevant personnel in a noisy production environment. For example, when the material inventory is below the safety warning line, the sound and light alarm device will immediately start to remind the staff to replenish the materials in time; when the material is abnormally vibrated or the temperature is too high during transportation, the sound and light alarm device will also sound an alarm to indicate possible safety hazards.

[0067] The message push unit is a more flexible and convenient way to warn. It can send warning information to relevant personnel through multiple channels, including mobile phone text messages, emails, instant messaging software, etc. When the system detects a material problem, the message push unit will quickly send detailed warning information to the designated personnel. This information usually includes a specific description of the problem, the time and place of occurrence, possible impact, etc., so that relevant personnel can understand the situation in a timely manner and take appropriate measures. For example, when a key material has a quality problem, the message push unit will send a text message notification to the quality management personnel and an email to the person in charge of the production department to ensure that all parties can respond quickly and deal with the problem.

[0068] In order to ensure the timely delivery of warning information, the warning module usually sets multiple sending channels and priorities. In an emergency, the sound and light alarm device will be activated first to attract the attention of on-site personnel; at the same time, the message push unit will quickly send warning information to relevant personnel to ensure that personnel who are not on-site can also be informed of the situation in a timely manner. In addition, the warning module can also set different warning levels according to the severity of the problem. For major problems, multiple methods will be used to send warning information at the same time to improve response speed and processing efficiency.

[0069] In the present invention, the display module, as a key part of information presentation, plays a vital role in material management. The display module is mainly composed of a display screen and a data visualization unit.

[0070] The display screen is the main carrier of information display. It has high resolution and good color reproduction, and can clearly present the status information and analysis results of various materials. The size and layout of the display screen are carefully designed to adapt to different usage scenarios and user needs. Whether it is on the control console in the production workshop, the computer screen in the office, or on a mobile device, the display screen can display information in the best way, which is convenient for users to view at any time.

[0071] The data visualization unit is the key link to convert complex data into intuitive and easy-to-understand graphics and charts. It uses advanced data visualization technology to display the type, quantity, location and other status information of materials and various analysis results obtained by the data analysis module in a vivid way on the display screen. For example, for the inventory status of materials, the comparison of the inventory quantity of different materials can be intuitively displayed through a bar chart; for the usage trend of materials, the change of material usage over time can be displayed through a line chart. For the location information of materials in the factory, a map-like display method can be used to let users know the specific location of the materials at a glance.

[0072] When the status of a material changes, the display module can update the information in real time. For example, when a new material is put into storage, the display will immediately show the increase in inventory quantity; when the material is used, the corresponding quantity will dynamically decrease. At the same time, the data visualization unit will also update the graphics and charts in real time based on the new data, ensuring that users can always see the latest material status information and analysis results.

[0073] In addition, the display module also has interactive functions. Users can obtain more detailed material information by clicking on a specific area on the display screen. For example, by clicking on the icon of a material, you can view the detailed properties and historical usage records of the material. At the same time, users can also set the display module through the operation interface on the display screen, such as adjusting the size and color of the graphics, to meet personalized needs.

[0074] In short, the display module can display the material status information and analysis results in an intuitive way through the synergy of the display screen and the data visualization unit, providing users with clear and accurate material management information, greatly improving the efficiency of material management and the scientific nature of decision-making.

[0075] In the present invention, the intelligent scheduling module plays a vital role, and it is the core component for realizing efficient material flow. The intelligent scheduling module is mainly composed of a path planning unit and a scheduling algorithm unit.

[0076] The path planning unit is like a shrewd navigator. It can plan the most reasonable transportation route for materials based on the starting position, target position and various actual conditions of the materials. In terms of considerations, the path planning unit will comprehensively analyze factors such as the layout within the factory, traffic conditions in different areas, and the distribution of equipment. For example, for larger materials, the path planning unit will give priority to spacious and barrier-free passages to ensure that the materials can be transported smoothly; for urgent materials that need to be delivered quickly, it will choose the path with the shortest distance and shortest transportation time. At the same time, the path planning unit will also monitor the dynamic changes in the factory in real time, such as the movement of equipment, the appearance of temporary obstacles, etc., and adjust the path planning in time to ensure that the materials can always be transported along the optimal path.

[0077] The scheduling algorithm unit is like a wise commander. It uses advanced algorithms and strategies to efficiently schedule materials according to real-time conditions. The scheduling algorithm unit receives data from various modules in real time, including material demand information, inventory status, production progress, etc. Based on this data, it can accurately calculate the optimal scheduling time and sequence of materials. For example, when a certain production link urgently needs a certain material, the scheduling algorithm unit will give priority to the transportation of the material to ensure that production will not be interrupted due to material shortages. At the same time, the scheduling algorithm unit will also consider factors such as material priority and transportation costs to achieve the optimization of overall scheduling. It can dynamically adjust the scheduling strategy according to different situations to ensure that the flow of materials in the factory is always efficient and smooth.

[0078] Through the synergy of the path planning unit and the scheduling algorithm unit, the intelligent scheduling module can efficiently schedule materials according to real-time conditions, greatly improving the material circulation efficiency, reducing inventory costs, and providing strong guarantees for efficient production in the manufacturing industry.

[0079] In the present invention, the traceability module is a key component for realizing the full life cycle management of materials. The traceability module is mainly composed of a database and a query unit.

[0080] The database is like a huge information warehouse, which records in detail the information of each link of the material from the procurement stage to the storage, use and scrapping. In the procurement stage, the database will record the supplier information, purchase time, purchase quantity, quality standards and other data of the material. When the material is put into storage, the storage time, storage location, inspection results and other information will also be entered into the database one by one. During the use process, the database will continue to track the use department, use time, use amount and matching of the material with other materials. When the material is facing scrapping, the scrapping reason, scrapping time and other information will also be properly saved.

[0081] The query unit provides users with a convenient query method. Users can quickly retrieve the required material life cycle information from the database by entering specific query conditions, such as material name, batch number, production date, etc. The interface design of the query unit is simple and intuitive, and even non-professional technicians can easily operate it. Whether it is for quality traceability, cost accounting, or for making production plans and decisions, users can use the query unit to obtain accurate and detailed material life cycle information in a short time. This convenient and fast query function greatly improves the company's management efficiency and decision-making scientificity of production materials, and provides a strong guarantee for the efficient operation and quality control of the manufacturing industry.

[0082] In the present invention, the interaction module plays a vital role, and it builds a bridge for efficient communication between the user and the system. The interaction module is mainly composed of an input unit and an output unit.

[0083] The input unit provides users with a variety of operation methods. Users can convey instructions and information to the system through methods such as keyboards, touch screens, and voice input devices. For example, users can input requests for querying material information through the input unit, including detailed information such as the type, quantity, and location of a specific material. At the same time, users can also use the input unit to set parameters for the system and adjust key parameters such as the accuracy of material identification and the threshold of early warning according to actual production needs. In addition, when users find problems during the operation of the system or have suggestions for improvement, they can also provide feedback to the system through the input unit so that the system can be continuously optimized and improved.

[0084] The output unit is responsible for conveying the system's feedback information to the user. When the user issues a query request, the output unit will display the real-time status information and analysis results of the material in a clear and intuitive manner. This may include presenting data such as the material's inventory quantity, usage progress, quality inspection report, etc. on the display screen, or informing the user of key information through voice broadcast. When the system detects a material error or abnormality, the output unit will issue a warning notification in a timely manner, such as through a flashing indicator light, a pop-up dialog box, or sending a text message, to ensure that the user can be informed and take appropriate measures at the first time. In short, the output unit can ensure that the information exchange between the user and the system is smooth, timely, and accurate, greatly improving the system's ease of use and user experience.

[0085] A method for efficient error prevention and precise control of manufacturing production materials, comprising the following steps:

[0086] Collect relevant data of production materials in real time through data acquisition module;

[0087] Use the data analysis module to analyze and process the collected material data, determine whether there are any errors in the materials, and accurately control the use of materials;

[0088] When material errors or abnormal conditions are detected, the early warning module sends out an early warning signal;

[0089] Display the real-time status information and analysis results of materials through the display module;

[0090] The intelligent scheduling module intelligently schedules materials based on the results of the data analysis module and the production plan;

[0091] The traceability module traces the entire life cycle of materials;

[0092] Users interact with the system through the interactive module.

[0093] In the present invention, in the data collection step, the physical parameters of the material are collected by the sensor component, and the unique identifier of the material is identified by the radio frequency identification device. In the data analysis step, the material data is processed by the data processing unit and the algorithm unit, and the algorithm unit uses a machine learning algorithm to analyze and predict the material data. In the early warning step, the early warning information is sent to relevant personnel through the sound and light alarm device and the message push unit. In the display step, the status information and analysis results of the material are displayed through the display screen and the data visualization unit. In the intelligent scheduling step, the material is efficiently scheduled through the path planning unit and the scheduling algorithm unit. In the tracing step, the full life cycle information of the material is queried through the database and the query unit. In the interactive step, the user operates through the input unit, and the system feeds back information to the user through the output unit.

[0094] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent system for efficient error prevention and precise control of manufacturing production materials, characterized in that: include: The data collection module is used to collect relevant data of production materials in real time, including material type, quantity, and location information. The data collection accuracy evaluation index formula is: Among them A dataAcq Indicates the accuracy of data collection, N cda Represents the number of data actually collected correctly, N tdp represents the total number of data that should be collected theoretically, n is the number of parameter types of collected data, and W pi represents the weight of the parameter, i represents the number of interference data; The data analysis module is connected to the data acquisition module and can analyze and process the collected material data, determine whether there are errors in the materials, and accurately control the use of the materials. The analysis accuracy evaluation index formula is: Among them A dataAn Indicates the analysis accuracy, N ca Indicates the number of correct analyses, N ta Represents the total number of analyses, N ad Indicates the number of abnormal data; The display module is used to display the real-time status information and analysis results of the material. The display clarity evaluation index formula is: Among them C display Indicates display clarity, N rp Indicates the number of clearly distinguishable pixels, N tp Indicates the total number of pixels, N tp Indicates the number of blurred pixels; The traceability module can trace the entire life cycle of materials and record information on each link from procurement, warehousing, use to scrapping. The traceability integrity evaluation index formula is: Among them I traceability Indicates traceability integrity, N rsd Indicates the number of links recorded in detail, N tse Indicates the total number of links in the expected material life cycle, N ms Indicates the number of missing links; Early warning module: When the data analysis module detects material errors or abnormalities, it issues an early warning signal. The evaluation indicator formula for the early warning response time is: Where T warnResp Indicates the warning response time, N w Indicates the number of warnings, T ri Indicates the response time of the first warning; The intelligent scheduling module intelligently schedules materials based on the results of the data analysis module and the production plan, and optimizes the material distribution path and time. The scheduling efficiency improvement factor formula is: where F scheduling represents the scheduling efficiency improvement factor, E a represents the efficiency after intelligent scheduling, E b Indicates the efficiency without intelligent scheduling; The interactive module provides an interactive interface between the user and the system. The user can query material information, receive warning notifications, and set system parameters through this module. The evaluation index formula for its interactive friendliness is: where F interaction Indicates the interaction friendliness, N usp Indicates the number of points of user satisfaction, N tp Indicates the total number of evaluation points.

2. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The data acquisition module includes a sensor component and a radio frequency identification device. The sensor component is used to collect physical parameters of the material, and the radio frequency identification device is used to identify the unique identification of the material.

3. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The data analysis module includes a data processing unit and an algorithm unit. The algorithm unit uses a machine learning algorithm to analyze and predict material data.

4. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The early warning module includes an audible and visual alarm device and a message push unit, which can send early warning information to relevant personnel in a timely manner.

5. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The display module includes a display screen and a data visualization unit, which can display the status information and analysis results of the material in an intuitive manner.

6. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The intelligent scheduling module includes a path planning unit and a scheduling algorithm unit, which can efficiently schedule materials according to real-time conditions.

7. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The traceability module includes a database and a query unit, which can easily query the full life cycle information of the material.

8. The intelligent system for efficient error prevention and precise control of manufacturing production materials according to claim 1 is characterized in that: The interaction module includes an input unit and an output unit. The user can operate through the input unit, and the system feeds back information to the user through the output unit.

9. A method for applying the efficient error-proofing and precise control system for manufacturing production materials according to any one of claims 1 to 8, characterized in that: The method for efficient error prevention and precise control of manufacturing production materials comprises the following steps: S1. Collect relevant data of production materials in real time through the data acquisition module; S2. Use the data analysis module to analyze and process the collected material data, determine whether there are any errors in the materials, and accurately control the use of the materials; S3. When material errors or abnormalities are detected, the early warning module sends out an early warning signal; S4. Display the real-time status information and analysis results of the material through the display module; S5, the intelligent scheduling module intelligently schedules materials according to the results of the data analysis module and the production plan; S6, the traceability module traces the entire life cycle of materials; S7. The user interacts with the system through the interactive module.

10. The method for efficient error prevention and precise control of manufacturing production materials according to claim 9, characterized in that: In the data collection step, the sensor component is used to collect the physical parameters of the material, and the radio frequency identification device is used to identify the unique identification of the material; in the data analysis step, the material data is processed by the data processing unit and the algorithm unit, and the algorithm unit uses a machine learning algorithm to analyze and predict the material data; in the early warning step, the early warning information is sent to relevant personnel through the sound and light alarm device and the message push unit; in the display step, the status information and analysis results of the material are displayed through the display screen and the data visualization unit; in the intelligent scheduling step, the path planning unit and the scheduling algorithm unit are used to efficiently schedule the material; in the traceability step, the full life cycle information of the material is queried through the database and the query unit; in the interaction step, the user operates through the input unit, and the system feeds back information to the user through the output unit.

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