Intelligent production line material inventory detection method and system

Abstract

The invention relates to the technical field of warehouse management, in particular to an intelligent production line material inventory detection method and system, which can improve the production efficiency and reduce the production cost. The method comprises the following steps: dividing an intelligent production line into at least two material management subsystems according to a preset division strategy; for each material management subsystem, performing real-time data acquisition according to a preset time node to obtain real-time inventory state data information; obtaining rated inventory state data information of each material management subsystem based on a production plan condition corresponding to the intelligent production line; and considering the real-time inventory state data information and the rated inventory state data information of all the material management subsystems to obtain an intelligent production line material inventory detection result.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to a material inventory detection method and system for an intelligent production line. Background Art

[0002] In today's highly automated and intelligent modern industrial development process, intelligent production lines have become the core elements for many manufacturing companies to improve production efficiency and enhance market competitiveness with their efficient and precise production capabilities; material inventory management, as a key link in the normal operation of intelligent production lines, is directly related to production continuity, cost control and timeliness of product delivery; on the one hand, sufficient supply of raw materials is the basis for ensuring that the production line does not stop. If the inventory is insufficient, it will lead to production interruptions, delay order delivery, and increase additional production costs; on the other hand, the reasonable storage and allocation of finished products affects whether the products can be delivered to customers in a timely manner, which is related to the company's market reputation and customer satisfaction.

[0003] However, existing material inventory detection methods have many limitations. Some traditional detection methods can only simply record the quantity of materials, and cannot fully obtain key information such as the storage location and storage time of the materials, making it difficult to meet the complex and changing production plan requirements. Moreover, many methods lack adaptability to dynamic changes in production plans and cannot adjust inventory detection strategies in a timely manner according to real-time production conditions, resulting in inventory backlogs or out-of-stock phenomena from time to time, which not only wastes resources, but also reduces the overall operating efficiency of the production line.

[0004] Therefore, there is an urgent need for an intelligent production line material inventory detection method that can comprehensively consider production planning conditions and fully detect material inventory status to solve the current dilemma. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a material inventory detection method and system for an intelligent production line, which can improve production efficiency and reduce production costs.

[0006] In a first aspect, the present invention provides a method for detecting material inventory of an intelligent production line, the method comprising: According to the preset division strategy, the intelligent production line is divided into at least two material management subsystems; For each of the material management subsystems, real-time data collection is performed according to preset time nodes to obtain real-time inventory status data information; Based on the production plan conditions corresponding to the intelligent production line, obtaining the rated inventory status data information of each material management subsystem; Taking into account the real-time inventory status data information and the rated inventory status data information of all the material management subsystems, the material inventory detection result of the intelligent production line is obtained.

[0007] Further, considering the real-time inventory status data information and the rated inventory status data information of all the material management subsystems, obtaining the intelligent production line material inventory detection result includes: Perform deviation analysis on various data between the real-time inventory status data information and the rated inventory status data information to obtain a real-time inventory status deviation vector; the real-time inventory status deviation vector includes a quantity deviation, a position deviation, and a warehousing time deviation; Inputting the real-time inventory status deviation vector into an inventory status anomaly assessment model to obtain an anomaly assessment index; Considering the impact of each material management subsystem on the operation of the intelligent production line, determining the impact weight corresponding to each material management subsystem; Based on the impact weight, weight evaluation is performed on the abnormality evaluation indexes corresponding to all the material management subsystems to obtain the material inventory abnormality index of the intelligent production line; The material inventory abnormality index is compared with a preset threshold value, and a detection result of the material inventory of the intelligent production line is generated according to the comparison result.

[0008] Furthermore, at least two of the material management subsystems include at least one raw material storage subsystem and at least one finished product storage subsystem.

[0009] Furthermore, the method for acquiring the real-time inventory status data information includes: Deploy sensors and counters in the raw material storage subsystem and finished product storage subsystem; Through sensors and counters, the material in and out status is recorded, and the real-time quantity of the current material is calculated; Perform image recognition on the raw material storage subsystem and finished product storage subsystem to track the storage location of materials in real time; Use the data acquisition module to collect the signals output by the sensor and convert them into different formats; When materials enter the warehouse, the data collection module records the material entry time and associates it with the material identification; Integrate data from different sensors, counters and data acquisition modules to form real-time inventory status data information.

[0010] Furthermore, the real-time inventory status data information includes the real-time quantity, real-time storage location and real-time warehousing time of the current material at a preset time node.

[0011] Furthermore, the method for acquiring the rated inventory status data information includes: Collect production plan information, combine historical sales data and market demand trends, and predict future order demand; Analyze the consumption rate of different materials in the production process based on historical production data; Based on production plan information and material consumption rate, calculate the material requirements of each material management subsystem at different time nodes; Determine the inventory parameters of each material management subsystem based on material requirements; Use inventory parameters to build a dynamic inventory model; The inventory model is solved to calculate the optimal inventory status of each material management subsystem at a preset time node, that is, the rated inventory status data information; the rated inventory status data information includes the optimal quantity, the optimal storage location and the optimal warehousing time.

[0012] Furthermore, the rated inventory status data information includes the optimal quantity, optimal storage location and optimal warehousing time of the corresponding material of each material management subsystem at a preset time node calculated according to the production plan.

[0013] On the other hand, the present application also provides an intelligent production line material inventory detection system, the system comprising: The material management subsystem division module divides the intelligent production line into at least two material management subsystems according to a preset division strategy; A real-time data collection module collects real-time data for each of the material management subsystems according to preset time nodes to obtain real-time inventory status data information; A rated inventory status data acquisition module, which acquires the rated inventory status data information of each material management subsystem based on the production plan conditions corresponding to the intelligent production line; The inventory detection result generation module considers the real-time inventory status data information and the rated inventory status data information of all the material management subsystems to obtain the intelligent production line material inventory detection result.

[0014] In a third aspect, the present application provides an electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and the computer program, when executed by the processor, implements the steps of any one of the above methods.

[0015] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps in any one of the above-mentioned methods when executed by a processor.

[0016] Compared with the prior art, the present invention has the following beneficial effects: the method not only records the quantity of materials, but also obtains key information such as the storage location and storage time of the materials; this comprehensive data collection method ensures a deeper understanding of the material status, which helps to improve the accuracy and efficiency of production planning; By dynamically adjusting the rated inventory status data information of each material management subsystem based on production plan conditions, this method can respond to changes in production demand in real time; this improves the system's ability to adapt to changes in production plans and reduces inventory backlogs or stockouts caused by plan changes; Combining real-time inventory status data information with rated inventory status data information to generate material inventory detection results, enabling enterprises to better allocate resources, reduce inventory holding costs, and ensure sufficient supply of raw materials to maintain production continuity; Accurate inventory management and timely material allocation can effectively avoid production interruptions, reduce the risk of delayed order delivery, and reduce the additional production costs caused by this; ensure the smooth operation of production and improve overall production efficiency; help improve customer satisfaction, thereby enhancing the company's market competitiveness and credibility; In summary, this intelligent production line material inventory detection method can not only improve production efficiency and reduce production costs, but also enhance the company's market competitiveness and customer satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of the present invention; Figure 2 It is a flow chart for obtaining the material inventory detection results of the intelligent production line; Figure 3 It is a structural diagram of a material inventory detection method and system for an intelligent production line. DETAILED DESCRIPTION

[0018] In the description of this application, those skilled in the art should know that this application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, this application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), a combination of hardware and software. In addition, in some embodiments, this application can also be implemented in the form of a computer program product in one or more computer-readable storage media, and the computer-readable storage medium contains computer program code.

[0019] The above-mentioned computer-readable storage medium may adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, optical disc read-only memories, optical storage devices, magnetic storage devices, or any combination of the above. In the present application, computer-readable storage media can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device.

[0020] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws.

[0021] The present application describes the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0022] It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine, and these computer-readable program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified by the boxes in the flowchart and / or block diagram.

[0023] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product including functions / operations specified in the blocks in the flowchart and / or block diagram.

[0024] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0025] The present application is described below in conjunction with the drawings in the present application.

[0026] Embodiment 1: Figure 1 to Figure 2 As shown, a material inventory detection method for an intelligent production line of the present invention specifically includes the following steps: S1. Divide the intelligent production line into at least two material management subsystems according to the preset division strategy; The preset division strategy is set based on the material inventory management structure and production planning conditions of the intelligent production line; at least two of the material management subsystems include at least one raw material storage subsystem and at least one finished product storage subsystem; Based on the material inventory management structure, it is necessary to have an in-depth understanding of the material inventory management structure of the intelligent production line, including the types of materials, storage methods, flow paths, etc. This helps to determine the management requirements and characteristics of different materials and provide a basis for dividing the material management subsystems; Combined with the production planning conditions, the production planning conditions of the intelligent production line are considered, such as production batches, production cycles, material requirement planning, etc. These factors will directly affect the management and scheduling of materials, so they need to be fully considered when dividing the material management subsystem; Clearly distinguish between raw materials and finished products based on the nature of the materials; raw materials are inputs into the production process, while finished products are outputs of the production process; these two types of materials have different requirements for storage, management, and allocation; analyze the physical and chemical properties of various materials, such as flammability, explosiveness, corrosion, size, weight, etc.; these properties will affect storage conditions, management methods, and safety requirements; According to the production plan and material consumption rate, evaluate the storage requirements of various materials, including storage volume, storage cycle, etc.; plan storage space according to storage requirements to ensure safe and efficient storage of materials; plan storage space including shelf layout, aisle width and safety distance; Design reasonable logistics flow lines to ensure efficient flow of materials from warehousing, storage to outbound delivery; designing logistics flow lines includes planning material handling paths, loading and unloading operation areas and automation equipment configuration; Ensure that each material management subsystem is seamlessly integrated with other management systems of the intelligent production line; establish a unified data interaction standard to achieve real-time data exchange and sharing between subsystems; including the collection and transmission of key information such as material quantity, storage location, and storage time; For the storage of dangerous goods, special safety protection measures need to be established; The raw material storage subsystem is used to store various raw materials required for the production line. Raw materials are classified and stored according to their types, specifications, properties, etc. to ensure the accuracy and traceability of raw materials. This subsystem needs to have strong material identification and management capabilities to quickly and accurately locate the required raw materials. The finished product storage subsystem is used to store finished products produced by the production line, waiting for delivery. Finished products are classified and stored according to their type, model, batch, etc. to ensure the accuracy and traceability of the finished products. This subsystem needs to have strong inventory management and delivery capabilities in order to quickly respond to customer order needs.

[0027] In this step, by dividing the intelligent production line into at least two material management subsystems according to the preset division strategy, refined management of materials is achieved; it helps to carry out targeted management according to the nature of materials, storage requirements and logistics efficiency, and improves the efficiency and accuracy of material management; the raw material storage subsystem can ensure that all kinds of raw materials required for the production line are supplied in a timely and accurate manner, avoiding production interruptions caused by shortages or errors of raw materials; at the same time, the finished product storage subsystem can quickly respond to customer order requirements and realize efficient delivery of finished products, thereby improving overall production efficiency; by classifying and storing raw materials and finished products, and strengthening material identification and management capabilities, the accuracy and traceability of materials are ensured; this helps to quickly locate the cause when a problem occurs, and take corresponding corrective measures, reducing production risks and costs; designing reasonable logistics routes and automation equipment configurations, This makes the process of material entry, storage and outbound delivery more efficient and smoother; this not only reduces the error rate of manual operations, but also increases the material turnover speed, further improving production efficiency; ensures that each material management subsystem is seamlessly integrated with other management systems of the intelligent production line, and establishes a unified data interaction standard; helps to achieve real-time data exchange and sharing between subsystems, improves the transparency and traceability of information, and provides more accurate and timely data support for decision-making; for the storage of hazardous materials, special safety protection measures are established to ensure the safety of material storage; this helps to reduce the risk of safety accidents and protect the safety of personnel and property; in summary, this step can effectively divide the intelligent production line into multiple material management subsystems, each subsystem focuses on a specific type of material management task, thereby achieving more refined inventory control and higher operational efficiency.

[0028] S2. For each of the material management subsystems, real-time data collection is performed according to preset time nodes to obtain real-time inventory status data information; The real-time inventory status data information includes the real-time quantity, real-time storage location and real-time warehousing time of the current material at a preset time node; A unique identification, including barcode and QR code, is affixed to each material package or carrier. The scanning operation is performed by scanning equipment during material entry, storage location change, and exit, to obtain the basic identification information of the material, so as to accurately link the real-time quantity, storage location, and entry time of the material. When the raw materials are entered into the warehouse, the QR code on the raw material packaging is scanned by a scanning terminal, and the system automatically records the entry time of the batch of raw materials, and updates its real-time storage location in the warehouse according to the location information of the entry operation; RFID tags are used for materials with high value, frequent circulation or extremely high real-time requirements; RFID readers are arranged at key locations in the warehouse; when materials with RFID tags pass through the reader's recognition range, the reader automatically reads the tag information, without the need for manual alignment and scanning like barcodes; in the finished product storage subsystem, when the finished product passes through the channel equipped with an RFID reader, the system instantly obtains the quantity, batch and other information of the finished product, quickly updates the real-time inventory status data, and improves the efficiency and accuracy of data collection; Deploy a wired network in the warehouse and connect various data collection devices to the warehouse management system server through network cables. The wired network has stable and fast data transmission speed, which can meet the needs of real-time transmission of large amounts of data and ensure that the collected real-time inventory status data information is quickly and accurately transmitted to the system for processing and storage; For areas where wiring is inconvenient or handheld devices are used, wireless network technologies such as Wi-Fi and Bluetooth are used; handheld scanning terminals interact with the warehouse management system through Wi-Fi and upload the collected data to the server in a timely manner; at the same time, cellular network technologies such as 4G / 5G can also be used to achieve remote data transmission and monitoring, making it easier for enterprise managers to obtain inventory status information anytime and anywhere; The method for acquiring real-time inventory status data information includes: Deploy various sensors and counters in the raw material storage subsystem and finished product storage subsystem, including temperature sensors, pressure sensors, displacement sensors, etc., to monitor the storage environment of materials; for specific materials, such as flammable, explosive, corrosive and other dangerous goods, special sensors need to be deployed to monitor their safety status; Use the data acquisition module to collect the signals output by the sensor and convert them into a data format that can be processed later; the data acquisition module has high-precision and high-frequency data acquisition capabilities to ensure the accuracy and real-time nature of the data; Sensors and counters deployed in the storage area can record the material in and out status in real time and calculate the real-time quantity of the current materials. For bulk materials, weight measuring equipment is used to check the weight to obtain the real-time weight information of the materials. Through image recognition technology, the storage location of materials can be tracked in real time; When materials enter the warehouse, the data collection module records the material entry time and associates it with the material's unique identification; the material entry time information is updated in real time to facilitate subsequent inventory analysis and optimization; Integrate data from different sensors and data acquisition modules to form unified real-time inventory status data information.

[0029] In this step, through real-time data collection at preset time nodes, combined with the use of barcodes, QR codes and RFID tags, the real-time quantity, storage location, warehousing time and other information of materials can be quickly and accurately obtained; not only the efficiency of data collection is improved, but also the real-time and accuracy of inventory data is ensured; the use of RFID tags and related reader-writer equipment realizes the automatic identification and tracking of materials in the warehouse, reduces the tedious process of manual scanning, and improves the level of automation; at the same time, by deploying sensors and counters, and using image recognition technology, the intelligence of warehouse management is further improved; the combination of wired network and wireless network technology ensures Real-time inventory status data information can be quickly and accurately transmitted to the warehouse management system for processing and storage; it not only improves the stability and speed of data transmission, but also enables enterprise managers to obtain inventory status information anytime and anywhere, thereby managing inventory more efficiently; for specific materials, such as dangerous goods, deploying special sensors to monitor their safety status helps to promptly discover and deal with potential safety hazards and ensure the safe operation of the warehouse; the acquisition and processing of real-time inventory status data information provides enterprises with rich data resources; through the analysis and mining of these data, enterprises can better understand inventory status, optimize inventory strategies, improve inventory turnover, and reduce inventory costs.

[0030] S3. Based on the production plan conditions corresponding to the intelligent production line, obtain the rated inventory status data information of each material management subsystem; The rated inventory status data information includes the optimal quantity, optimal storage location and optimal warehousing time of the corresponding materials of each material management subsystem at a preset time node calculated according to the production plan; The method for obtaining the rated inventory status data information includes: Collect production plan information and obtain production plans for a period of time in the future from the production plan management system, including product type, production quantity, production cycle, etc.; combine historical sales data and market demand trends to predict future order demand; Analyze the consumption rate and rules of different materials in the production process based on historical production data; Based on the production plan and material consumption rate, calculate the material requirements of each material management subsystem at different time nodes; Determine the inventory parameters of each material management subsystem based on material demand, procurement cycle, and safety stock level factors; Using inventory parameters, a dynamic inventory model is constructed, which can simulate the changes of material inventory under different production conditions; Use optimization algorithms to solve the inventory model and find the optimal inventory status of each material management subsystem at a preset time node; Output the calculation results in the form of rated inventory status data information, including the optimal quantity, optimal storage location and optimal warehousing time; By simulating the production environment, the calculated rated inventory status data information is verified to ensure its feasibility and accuracy in actual production; According to the actual production situation and changes in market demand, the rated inventory status data information is dynamically adjusted and optimized.

[0031] In this step, by collecting production plan information and combining it with historical sales data and market demand trends for forecasting, the material demand in the future can be determined more accurately; it helps the intelligent production line to prepare in advance and reduce production interruptions caused by material shortages or surpluses, thereby improving production efficiency; at the same time, based on the analysis of material consumption rates and patterns, the production process can be further optimized to ensure the accuracy of material use; by building a dynamic inventory model and using the optimization algorithm to solve it, the optimal inventory status of each material management subsystem at the preset time node can be found, which helps to achieve refined inventory management; optimizing inventory management can not only reduce inventory backlogs and funds It can not only improve inventory occupancy, but also increase inventory turnover and reduce inventory costs; the inventory model and optimization algorithm in this step can be dynamically adjusted according to different production conditions and market demands; the intelligent production line can quickly adapt to market changes and flexibly adjust production plans; by outputting rated inventory status data information, it provides powerful decision-making support for production management personnel; it can help managers understand the inventory status more intuitively, formulate reasonable procurement plans and production plans, thereby optimizing resource allocation and improving overall operational efficiency; this step realizes the refinement, dynamicization and intelligence of material management of intelligent production lines through the comprehensive use of production plan management, data analysis, optimization algorithms and simulation verification.

[0032] S4. Considering the real-time inventory status data information and the rated inventory status data information of all the material management subsystems, obtaining the material inventory detection result of the intelligent production line; Compare the real-time quantity of materials in each material management subsystem with the rated quantity to obtain the quantity deviation; the quantity deviation refers to the difference or ratio between the real-time quantity and the rated quantity, reflecting the sufficiency or excess of the material quantity; analyze the difference between the real-time storage location and the rated storage location of the material to obtain the position deviation; the position deviation can be obtained by calculating the physical distance or logical difference between the two locations, which reflects the rationality of the material storage location; compare the real-time storage time of the material with the rated storage time to obtain the storage time deviation; the storage time deviation refers to the time difference between the real-time storage time and the rated storage time, which reflects the timeliness and accuracy of the material storage time; combine the quantity deviation, location deviation and storage time deviation to obtain the real-time inventory status deviation vector, which comprehensively reflects the deviation of the material in terms of quantity, location and storage time; The real-time inventory status deviation vector is used as input to the inventory status abnormality assessment model. The inventory status abnormality assessment model can automatically calculate the abnormality assessment index based on the input deviation vector. The abnormality assessment index is a comprehensive indicator that reflects the abnormality of the material inventory status. The higher the index, the greater the deviation between the inventory status and the rated status. Consider the impact of each material management subsystem on the operation of the intelligent production line, including factors such as the importance of the material, the degree of direct impact on the production line, and the possible consequences of out-of-stock or backlogs. Based on the results of the impact analysis, determine an impact weight for each material management subsystem. The larger the weight, the greater the impact of the subsystem on the operation of the production line, so more attention should be paid to it in subsequent evaluations. Multiply the abnormal evaluation index of all material management subsystems by their corresponding impact weights to obtain the weighted abnormal evaluation index; summarize all weighted abnormal evaluation indexes to obtain the material inventory abnormal index of the intelligent production line. The material inventory abnormal index reflects the abnormal degree of the material inventory of the entire production line; According to the actual situation and needs of the enterprise, a preset threshold value of the material inventory abnormality index is set. The threshold value is used to determine whether the material inventory status is abnormal; the calculated material inventory abnormality index is compared with the preset threshold value; if the abnormality index exceeds the threshold value, the material inventory status is considered to be abnormal and corresponding measures need to be taken to adjust it; if the abnormality index is below the threshold value, the material inventory status is considered to be normal and the current management strategy can continue to be maintained.

[0033] In this step, by comprehensively considering the deviation of the real-time quantity, storage location and warehousing time of the materials from the rated state, this step can fully and accurately reflect the actual state of the material inventory; it helps to discover potential problems so that corrective measures can be taken in time; the introduction of the inventory status abnormality assessment model can automatically calculate the abnormality assessment index based on the input real-time inventory status deviation vector; it not only improves the accuracy and efficiency of the assessment, but also reduces the interference of human factors, making inventory management more objective and scientific; this step can determine different impact weights for each subsystem according to the degree of influence of different material management subsystems on the operation of the intelligent production line; this flexible processing method enables the inventory management strategy to be more in line with the actual situation of the enterprise The situation and needs of the company are improved, which improves the pertinence and effectiveness of the strategy. By setting a preset threshold for the material inventory abnormality index and comparing the calculated abnormality index with the threshold, this step can issue an early warning before the material inventory status becomes abnormal, providing managers with sufficient time to take measures to make adjustments. This preventive and forward-looking management method helps avoid problems such as inventory backlogs or out-of-stocks, thereby ensuring the continuity and stability of production. By promptly discovering and resolving abnormal problems in the material inventory status, this step helps optimize the configuration and utilization of materials and reduce the waste of resources. At the same time, it can also improve the operating efficiency of the production line and ensure that products can be delivered to customers in a timely manner, thereby enhancing the company's market competitiveness and customer satisfaction.

[0034] Embodiment 2: Figure 3 As shown, an intelligent production line material inventory detection system of the present invention specifically includes the following modules; The material management subsystem division module divides the intelligent production line into at least two material management subsystems according to a preset division strategy; A real-time data collection module collects real-time data for each of the material management subsystems according to preset time nodes to obtain real-time inventory status data information; A rated inventory status data acquisition module, which acquires the rated inventory status data information of each material management subsystem based on the production plan conditions corresponding to the intelligent production line; The inventory detection result generation module considers the real-time inventory status data information and the rated inventory status data information of all the material management subsystems to obtain the intelligent production line material inventory detection result.

[0035] Through the real-time data acquisition module, the system can obtain key information such as the real-time quantity, storage location and storage time of materials, rather than just simple quantity records; it provides more comprehensive data support for production planning and helps improve the accuracy of decision-making; The rated inventory status data acquisition module dynamically adjusts the optimal inventory status of each material management subsystem based on production plan conditions, so that the inventory management strategy can be flexibly adjusted according to the real-time production situation; this dynamic adaptability can effectively avoid inventory backlogs or stockouts caused by changes in production plans; By accurately grasping the difference between the actual inventory status of materials and the ideal inventory status, the inventory detection result generation module can help enterprises allocate resources more effectively, reduce unnecessary inventory backlogs, reduce inventory holding costs, and ensure sufficient supply of raw materials to prevent additional costs caused by production interruptions; The material management subsystem division module divides the intelligent production line into different material management subsystems, which facilitates targeted management of different types of materials, ensures the continuous supply of raw materials and the reasonable allocation of finished products, thereby ensuring the continuity of production and improving the overall operating efficiency of the production line; through precise management and timely allocation of finished products, the system helps to ensure that products can be delivered to customers on time, improve customer satisfaction, and thus enhance the market competitiveness and credibility of the enterprise; In summary, this intelligent production line material inventory detection system not only overcomes the limitations of traditional methods, but also provides comprehensive information support, enhances adaptability and flexibility, optimizes resource allocation and cost control, promotes production continuity and efficiency, and improves customer satisfaction and market reputation.

[0036] The various variations and specific embodiments of the intelligent production line material inventory detection method in the aforementioned embodiment 1 are also applicable to the intelligent production line material inventory detection system of this embodiment. Through the aforementioned detailed description of the intelligent production line material inventory detection method, those skilled in the art can clearly know the implementation method of the intelligent production line material inventory detection system in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0037] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned method for controlling output data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0038] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for detecting material inventory of an intelligent production line, characterized in that: The method comprises: According to the preset division strategy, the intelligent production line is divided into at least two material management subsystems; For each of the material management subsystems, real-time data collection is performed according to preset time nodes to obtain real-time inventory status data information; Based on the production plan conditions corresponding to the intelligent production line, obtaining the rated inventory status data information of each material management subsystem; Taking into account the real-time inventory status data information and the rated inventory status data information of all the material management subsystems, the material inventory detection result of the intelligent production line is obtained.

2. The intelligent production line material inventory detection method according to claim 1, characterized in that: Taking into account the real-time inventory status data information and the rated inventory status data information of all the material management subsystems, obtaining the intelligent production line material inventory detection result includes: Perform deviation analysis on various data between the real-time inventory status data information and the rated inventory status data information to obtain a real-time inventory status deviation vector; the real-time inventory status deviation vector includes a quantity deviation, a position deviation, and a warehousing time deviation; Inputting the real-time inventory status deviation vector into an inventory status anomaly assessment model to obtain an anomaly assessment index; Considering the impact of each material management subsystem on the operation of the intelligent production line, determining the impact weight corresponding to each material management subsystem; Based on the impact weight, weight evaluation is performed on the abnormal evaluation indexes corresponding to all the material management subsystems to obtain the material inventory abnormality index of the intelligent production line; The material inventory abnormality index is compared with a preset threshold value, and a detection result of the material inventory of the intelligent production line is generated according to the comparison result.

3. The intelligent production line material inventory detection method according to claim 1, characterized in that: At least two of the material management subsystems include at least one raw material storage subsystem and at least one finished product storage subsystem.

4. The intelligent production line material inventory detection method according to claim 1, characterized in that: The method for acquiring real-time inventory status data information includes: Deploy sensors and counters in the raw material storage subsystem and finished product storage subsystem; Through sensors and counters, the material in and out status is recorded, and the real-time quantity of the current material is calculated; Perform image recognition on the raw material storage subsystem and finished product storage subsystem to track the storage location of materials in real time; Use the data acquisition module to collect the signals output by the sensor and convert them into different formats; When materials enter the warehouse, the material entry time is recorded through the data collection module and associated with the material identification; Integrate data from different sensors, counters and data acquisition modules to form real-time inventory status data information.

5. The intelligent production line material inventory detection method according to claim 4, characterized in that: The real-time inventory status data information includes the real-time quantity, real-time storage location and real-time warehousing time of the current material at a preset time node.

6. The intelligent production line material inventory detection method according to claim 1, characterized in that: The method for obtaining the rated inventory status data information includes: Collect production plan information, combine historical sales data and market demand trends, and predict future order demand; Analyze the consumption rate of different materials in the production process based on historical production data; Based on production plan information and material consumption rate, calculate the material requirements of each material management subsystem at different time nodes; Determine the inventory parameters of each material management subsystem based on material requirements; Use inventory parameters to build a dynamic inventory model; The inventory model is solved to calculate the optimal inventory status of each material management subsystem at a preset time node, that is, the rated inventory status data information; the rated inventory status data information includes the optimal quantity, the optimal storage location and the optimal warehousing time.

7. The intelligent production line material inventory detection method according to claim 6, characterized in that: The rated inventory status data information includes the optimal quantity, optimal storage location and optimal warehousing time of the corresponding materials of each material management subsystem at a preset time node calculated according to the production plan.

8. An intelligent production line material inventory detection system, characterized in that: The system comprises: The material management subsystem division module divides the intelligent production line into at least two material management subsystems according to a preset division strategy; A real-time data collection module collects real-time data for each of the material management subsystems according to preset time nodes to obtain real-time inventory status data information; A rated inventory status data acquisition module, which acquires the rated inventory status data information of each material management subsystem based on the production plan conditions corresponding to the intelligent production line; The inventory detection result generation module considers the real-time inventory status data information and the rated inventory status data information of all the material management subsystems to obtain the intelligent production line material inventory detection result.

9. An electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, wherein: When the computer program is executed by the processor, the steps in the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

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