An intelligent management system for meat storage

Abstract

The present invention relates to the field of warehouse management technology, specifically to an intelligent management system for meat warehouses, the system comprising an environmental control module, a quality monitoring module, a space optimization module, and a logistics coordination module. In the present invention, by automatically monitoring and adjusting the temperature and humidity inside the warehouse, it is ensured that the environmental conditions always remain in the most suitable state, thereby extending the shelf life of meat products and maintaining their quality, and the automated quality inspection and graded storage further improve the accuracy and efficiency of product sorting, ensuring that only products that meet the standards are stored, and at the same time, products of differentiated quality grades are stored separately, optimizing inventory management, and reconfiguring the space to optimize the warehouse layout, improve space utilization and operational efficiency, and logistics coordination through real-time data analysis, so that the warehouse process is faster and more efficient, reducing waiting and processing time, accelerating market response speed, improving operational efficiency, reducing costs, improving customer satisfaction, and effectively reducing food waste.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to an intelligent management system for meat warehouse. Background Art

[0002] The field of warehouse management technology involves various methods and systems for efficiently organizing, controlling and managing warehouse operations. In modern warehouse management, the application of technology ranges from basic cargo storage and retrieval systems to complex supply chain management and real-time data analysis. This field includes automated warehouse management systems (WMS), material handling systems, and smart devices integrated with the Internet of Things (IoT) to monitor environmental conditions and improve logistics efficiency. Key technologies include machine learning, artificial intelligence (AI), and big data analysis. The technology can optimize inventory levels, predict demand, reduce waste, and improve the ability to respond to market changes. Warehouse management technology also includes security and quality control measures to ensure the safety of stored goods and compliance with prescribed standards.

[0003] Among them, the meat storage intelligent management system is a technical system specially designed for handling and storing highly perishable items such as meat products. The main purpose of the system is to improve the storage efficiency and product quality control of meat products through advanced automation and data analysis technology. The system integrates temperature and humidity automatic control technology, real-time monitoring and data analysis functions, and machine learning algorithms to predict market demand and optimize inventory management. The intelligent warehousing system can also reduce the need for manual supervision and respond to rapidly changing market demands by automatically adjusting storage conditions, thereby ensuring the freshness and safety of meat products, reducing waste, and improving overall operational efficiency.

[0004] Common deficiencies of existing technologies when handling highly perishable items such as meat include a time lag in response to environmental control and non-personalized storage methods. Existing systems are unable to adjust environmental settings in real time to cope with rapidly changing external conditions, resulting in compromised quality of meat products and increased waste. The lack of refined quality grading and storage solutions leads to mixed storage of products of differentiated quality, affecting the overall sales of products and consumers' purchasing experience. Such operational deficiencies directly affect the economic benefits and market competitiveness of the company, increase operating costs and lead to customer loss. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent management system for meat storage.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: an intelligent management system for meat storage comprises:

[0007] The environmental control module uses temperature and humidity sensors to measure the temperature control equipment in the warehouse to adjust the air conditioning and ventilation facilities, generate environmental steady-state parameters, and based on the environmental steady-state parameters, maintain environmental stability, adjust the operating status of the equipment inside the warehouse, adjust the internal equipment settings, and generate equipment adjustment instructions;

[0008] The quality monitoring module checks the packaging of the meat products through a scanner according to the equipment adjustment instruction, and performs quality grading on the products entering the warehouse to generate quality grading results. Based on the quality grading results, the meat products are classified and stored to generate a graded storage plan;

[0009] The space optimization module reconfigures the shelves and temperature control areas according to the equipment adjustment instructions and the hierarchical storage plan, evaluates the quality and shelf life of the meat products, generates a space configuration plan, and optimizes the storage layout and space utilization by using the space configuration plan to generate an optimized layout plan;

[0010] Based on the optimized layout plan and real-time warehouse entry and exit data, the logistics coordination module dispatches the handling scheduling tools and personnel in the warehouse, obtains logistics efficiency data, adjusts the warehouse exit plan and personnel scheduling based on the logistics efficiency data, optimizes the warehouse exit process and adjusts the warehouse layout, and generates an optimized warehouse exit scheduling strategy.

[0011] As a further solution of the present invention, the step of obtaining the device adjustment instruction is specifically as follows:

[0012] The temperature and humidity sensors are used to measure the temperature control equipment in the warehouse to adjust the air conditioning and ventilation facilities, monitor the temperature and humidity in the warehouse in real time, record the current temperature and humidity, and generate environmental data records;

[0013] According to the environmental data records, the influence of temperature and humidity on the overall environmental steady state is balanced by the formula:

[0014] ;

[0015] Generate environmental steady-state parameters, where Represents the temperature value, Represents the humidity value, represents the environmental steady-state parameter;

[0016] The environmental steady-state parameters are used to adjust the settings of air conditioning and ventilation equipment, including adjusting temperature settings and ventilation switch states, and the equipment operation strategy is optimized according to the values ​​of the environmental steady-state parameters to generate equipment adjustment instructions.

[0017] As a further solution of the present invention, the steps of obtaining the quality grading results are specifically as follows:

[0018] Instruct the scanner to start working according to the signal of receiving the device adjustment instruction, and scan the meat product packaging entering the warehouse, including the packaging integrity, label information and visible defects, to obtain preliminary scanning data;

[0019] A quality assessment model is applied to the preliminary scan data, based on the weights of package integrity and label information, calculated by the formula:

[0020] ;

[0021] Generating a packaging quality score ,in, Represents the packaging integrity score, Represents the matching degree of label information, and are the weight coefficients of the two items respectively;

[0022] According to the packaging quality score , grade the product quality, use the quality threshold judgment logic to determine whether the product meets the warehouse standards, assign a grade to each product, and generate a quality grading result.

[0023] As a further solution of the present invention, the steps of obtaining the hierarchical storage solution are specifically as follows:

[0024] Based on the quality grading results, identifying matching storage areas and evaluating corresponding storage conditions according to the quality grade indication of each product, and generating classification and area matching records with reference to the characteristics of the product including temperature sensitivity and humidity requirements;

[0025] According to the classification and area matching records, the storage demand model is used to calculate the space allocation for the number of products of each quality level, using the formula:

[0026] ;

[0027] Calculate the total storage space required , generating the estimated storage requirements for the quality level, where Represents the number of products with different quality levels, Indicates the space occupancy factor of the corresponding level;

[0028] Based on the estimated storage demand of the quality grade and the real-time available warehouse space, space configuration is carried out, storage layout is adjusted, space utilization efficiency and product quality are optimized, products are stored under optimal conditions, and a hierarchical storage plan is generated.

[0029] As a further solution of the present invention, the step of obtaining the space configuration solution is specifically as follows:

[0030] Analyze the quality and shelf life requirements of meat products based on the data received from the equipment adjustment instructions and the graded storage plan, determine the storage priority of differentiated products, and generate a product classification and priority list;

[0031] Based on the product classification and priority list, an optimization algorithm is applied to reconfigure the shelves and temperature control zones using the formula:

[0032] ;

[0033] Generate preliminary shelf and temperature control configuration plans, including: Indicates products The priority of and Represent products Volume requirements and temperature control requirements, is a function adjusted according to storage conditions, Indicates the total number of products;

[0034] Combining the preliminary shelf and temperature control configuration plan with the real-time operating conditions of the warehouse, space configuration is performed, products are stored according to quality standards and shelf life, and a space configuration plan is generated.

[0035] As a further solution of the present invention, the step of obtaining the optimized layout solution is specifically as follows:

[0036] Analyze the space configuration plan, identify the space utilization areas in the current warehouse layout, determine the storage requirements and shelf life limits of each meat product through data analysis, and generate demand and utilization analysis results;

[0037] Based on the demand and utilization analysis results, the warehouse space layout is redesigned and adjusted using the formula:

[0038] ;

[0039] Generate a detailed draft warehouse layout, where: Indicates products Required storage area, For products The priority of Indicates the warehouse layout area for each product;

[0040] Implement the detailed warehouse layout draft, test the operational efficiency of the layout through dynamic simulation, optimize the storage conditions of product types, and generate an optimized layout plan.

[0041] As a further solution of the present invention, the steps for acquiring the logistics efficiency data are specifically as follows:

[0042] Based on the optimized layout plan, data collection is initialized, real-time in-and-out warehouse data is captured through real-time monitoring, the cargo flow frequency and timestamp of each area are recorded, and cargo mobility results are generated;

[0043] The cargo mobility results are analyzed and a statistical model is applied to predict the handling and scheduling efficiency of multiple regions using the formula:

[0044] ;

[0045] Evaluate and optimize logistics scheduling to generate data-driven logistics efficiency results ,in, Representative Processing time for the region, Indicates Frequency of use of the area, is the total number of scheduling events;

[0046] According to the data-driven logistics efficiency results, the warehouse's handling scheduling strategy is adjusted, including the handling tool and personnel allocation plan, to obtain logistics efficiency data.

[0047] As a further solution of the present invention, the steps for obtaining the optimized warehouse dispatching strategy are specifically as follows:

[0048] Based on the logistics efficiency data, real-time monitoring is used to capture data about the warehouse exit process, including warehouse exit time, frequency, and personnel efficiency, identify process bottlenecks and efficiency issues, and integrate the data to conduct preliminary trend analysis and pattern recognition to generate detailed results of warehouse exit performance;

[0049] Using the results of the warehouse performance refinement, determine the optimal resource allocation and time schedule, apply decision analysis tools to evaluate the potential impact of differentiated warehouse strategies, and use the formula:

[0050] ;

[0051] Calculate the expected exit rate of the generated strategy ,in, Indicates the average time of a single warehouse operation. represents the total number of shipments processed during the assessment period, represents the number of hours worked;

[0052] Based on the expected warehouse delivery rate of the strategy, redesign and adjust the warehouse delivery plan and personnel scheduling, implement new warehouse delivery process optimization measures, use simulation software to test the implementation effect of the new strategy, verify the real-time impact, apply the optimized strategy to the current operation, and continuously monitor the adjusted effect to generate the optimized warehouse delivery scheduling strategy.

[0053] Compared with the prior art, the advantages and positive effects of the present invention are:

[0054] In the present invention, the temperature and humidity inside the warehouse are automatically monitored and adjusted to ensure that the environmental conditions are always kept in the most suitable state, thereby extending the shelf life of meat products and maintaining their quality. Automated quality inspection and graded storage further improve the accuracy and efficiency of product sorting, ensuring that only products that meet the standards are stored. At the same time, products of differentiated quality grades are stored separately, optimizing inventory management. The reconfiguration of space optimizes the warehouse layout, improves space utilization and operational efficiency, and logistics coordination makes the warehouse delivery process faster and more efficient through real-time data analysis, reduces waiting and processing time, speeds up market response, improves operational efficiency, reduces costs, enhances customer satisfaction, and effectively reduces food waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a system flow chart of the present invention;

[0056] Figure 2 A flowchart of the device adjustment instructions in the present invention;

[0057] Figure 3 A flow chart of the quality grading results in the present invention;

[0058] Figure 4 A flowchart of the hierarchical storage solution of the present invention;

[0059] Figure 5 It is a flow chart of the space configuration scheme in the present invention;

[0060] Figure 6 It is a flow chart of the optimized layout scheme in the present invention;

[0061] Figure 7 It is a flow chart of logistics efficiency data in the present invention;

[0062] Figure 8 It is a flow chart of the optimized warehouse dispatching strategy in the present invention. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0064] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0065] See also Figure 1 , a meat storage intelligent management system includes:

[0066] The environmental control module uses temperature and humidity sensors to measure the temperature control equipment in the warehouse to adjust the air conditioning and ventilation facilities, generate environmental steady-state parameters, maintain environmental stability based on the environmental steady-state parameters, adjust the operating status of the equipment inside the warehouse, adjust the internal equipment settings, and generate equipment adjustment instructions;

[0067] The quality monitoring module checks the packaging of meat products through a scanner according to the equipment adjustment instructions, and grades the quality of the products entering the warehouse, generates quality grading results, and classifies and stores the meat products based on the quality grading results, and generates a graded storage plan;

[0068] The space optimization module reconfigures the shelves and temperature control areas according to the equipment adjustment instructions and the hierarchical storage plan, evaluates the quality and shelf life of meat products, generates a space configuration plan, uses the space configuration plan to optimize the storage layout, optimizes the space utilization, and generates an optimized layout plan;

[0069] The logistics coordination module dispatches the handling and dispatching tools and personnel in the warehouse based on the optimized layout plan and real-time warehouse entry and exit data, obtains logistics efficiency data, adjusts the warehouse exit plan and personnel scheduling based on the logistics efficiency data, optimizes the warehouse exit process and adjusts the warehouse layout, and generates an optimized warehouse exit dispatching strategy.

[0070] Environmental steady-state parameters include measured temperature, measured humidity, and ventilation efficiency indicators. Equipment adjustment instructions include air conditioning adjustment parameters, ventilation equipment settings, and equipment operation modes. Quality grading results include packaging integrity level, freshness level, and shelf life category. Graded storage plans include product type classification, shelf life zoning, and target temperature and humidity area settings. Space configuration plans include shelf re-layout, target product differentiation, and optimized channel configuration. The optimized layout plan includes improved space utilization efficiency, optimized shelf position, and optimized temperature control effect. Logistics efficiency data include average handling time, processing volume per unit time, and human resource utilization. The optimized warehouse scheduling strategy includes optimized warehouse schedule, personnel work shifts, and process simplification measures.

[0071] See also Figure 2 , the specific steps for obtaining the device adjustment instruction are as follows:

[0072] The temperature and humidity sensors are used to measure the temperature control equipment in the warehouse to adjust the air conditioning and ventilation facilities, monitor the temperature and humidity in the warehouse in real time, record the current temperature and humidity, and generate environmental data records;

[0073] By deploying multiple temperature and humidity sensors in the warehouse, environmental changes are monitored in real time. The sensors periodically send the collected data to the central processing unit, which records the temperature and humidity data at each moment. The data includes specific temperature and humidity values, as well as the specific timestamp of data collection. By collating and analyzing the data within a certain period of time, the fluctuation trend of temperature and humidity can be monitored, which helps to analyze environmental stability and the impact of the internal environment of the warehouse on stored items, thereby achieving precise environmental control and adjustment and generating environmental data records.

[0074] According to the environmental data records, the influence of temperature and humidity on the overall environmental steady state is balanced, through the formula:

[0075] ;

[0076] Generate environmental steady-state parameters, where Represents the temperature value, Represents the humidity value, represents the environmental steady-state parameter;

[0077] The benefit of the formula is that by squaring the temperature and humidity values ​​separately and taking a weighted average through the sum, it can more accurately reflect the combined impact of temperature and humidity on the environmental steady state, which is critical in complex or frequently changing environments. Suppose at a certain moment, the temperature in the warehouse is and humidity ;

[0078] Substitute into the formula and calculate:

[0079] ;

[0080] The result shows that, considering the current temperature and humidity, an environmental steady-state parameter of 49.80 is obtained. This parameter will be used to further adjust the settings of air conditioning and ventilation equipment to ensure environmental stability and maintain the optimal state of the warehouse environment.

[0081] Use environmental steady-state parameters to adjust the settings of air conditioning and ventilation equipment, including adjusting temperature settings and ventilation switch status, optimize equipment operation strategies based on the values ​​of environmental steady-state parameters, and generate equipment adjustment instructions.

[0082] After obtaining the environmental steady-state parameters, the air conditioning and ventilation equipment are fine-tuned. The steady-state parameters are input through the central control system. The system compares this parameter with the preset environmental target parameters and calculates the temperature setting and ventilation status that need to be adjusted. For example, if the steady-state parameters indicate that the current environment is hot, the temperature setting of the air conditioner is lowered and the operating frequency of the ventilation equipment is increased. The adjustment is driven by real-time data to ensure a quick and accurate response. Finally, according to the adjusted equipment operating status, equipment adjustment instructions are generated to ensure the suitability of the warehouse environment and the optimal operating status of the equipment.

[0083] See also Figure 3 , the specific steps for obtaining the quality grading results are:

[0084] Instruct the scanner to start working according to the signal of the adjustment instruction of the receiving device, and scan the meat product packaging entering the warehouse, including the packaging integrity, label information and visible defects, to obtain preliminary scanning data;

[0085] Receiving equipment adjustment instructions is the first step in the automated quality control system. The instructions are issued by the central management system, instructing the scanner to start checking the packaging of meat products, including scanning the sealing, material integrity and barcode or logo of the packaging. The scanning results will include preliminary data such as whether there is damage, leakage or information mismatch. The data is crucial for subsequent quality grading and will be stored in the database for further analysis to generate preliminary scanning data.

[0086] A quality assessment model is applied to the preliminary scan data, based on the weights of package integrity and label information, calculated using the formula:

[0087] ;

[0088] Generating a packaging quality score ,in, Represents the packaging integrity score, Represents the matching degree of label information, and are the weight coefficients of the two items respectively;

[0089] The benefit of the formula is that by adjusting the weight coefficient and , can flexibly adapt to the quality evaluation standards of differentiated products, so as to implement more precise quality control for differentiated categories of meat products;

[0090] Setting a Packaging Integrity Score for Meat Products The score is 85, and the label information matching degree is is 95%, the weight coefficient is 0.6, is 0.4, then insert the formula to calculate :

[0091] ;

[0092] The results show that after considering the packaging integrity and label information, the product's quality score is 89 points, which is a high-quality product level.

[0093] Rating based on packaging quality , grade the quality of the products, use the quality threshold judgment logic to determine whether the products meet the warehouse standards, assign grades to each product, and generate quality grading results;

[0094] Using the packaging quality score obtained from the second step, the decision-making process for quality grading includes comparing the score with the preset quality grade threshold, such as comparing the score with the grading standard to determine whether the product reaches grade A (such as above 90 points), grade B (80-89 points) or grade C (70-79 points). The process is automatically performed by specialized software to ensure that each product is accurately classified and the results are recorded in the product database for easy tracking and management. Finally, based on the classification results, the quality grading results are generated and provided to the warehouse management system for subsequent operations.

[0095] See also Figure 4 , the specific steps for obtaining the hierarchical storage solution are:

[0096] Based on the quality grading results, identify the matching storage area and evaluate the corresponding storage conditions according to the quality grade indication of each product, refer to the characteristics of the product including temperature sensitivity and humidity requirements, and generate classification and area matching records;

[0097] The system receives grading results from the quality control system, which details the quality grade of each meat product. Based on the information, the system identifies appropriate storage areas and evaluates storage conditions to ensure that sensitive products such as high-quality meat receive proper cold chain handling. This process involves using temperature and humidity data monitored by sensors to determine the suitability of each area and generate storage recommendations for products with differentiated quality grades.

[0098] According to the classification and area matching records, the storage demand model is used to calculate the space allocation for the number of products of each quality level using the formula:

[0099] ;

[0100] Calculate the total storage space required , generating the estimated storage requirements for the quality level, where Represents the number of products with different quality levels, Indicates the space occupancy factor of the corresponding level;

[0101] The formula is beneficial in that it dynamically adjusts the storage space factor , which can effectively adapt to the storage needs of products with differentiated quality levels, thereby maximizing the utilization efficiency of warehouse space and product freshness;

[0102] Set the quantity of Grade A products , number of B-grade products , number of C-grade products , storage space coefficient , substitute into the calculation and get:

[0103] ;

[0104] The results show that a total of 125 units of storage space are required to properly house all meat products and ensure storage conditions and access efficiency for all levels of products.

[0105] Combine the estimated storage demand of quality grade with the real-time available warehouse space to configure space, adjust storage layout, optimize space utilization efficiency and product quality, store products under the best conditions, and generate a hierarchical storage plan;

[0106] The calculated storage demand is matched with the actual warehouse space, specific areas are allocated to store differentiated grades of products, the storage layout is adjusted to accommodate high to low quality grading, the storage configuration is dynamically updated through the intelligent management system, the warehouse operation efficiency is optimized, and fast access to high-demand products is ensured. Ultimately, a complete set of hierarchical storage solutions is formed to guide daily warehouse management and operational decisions, and continuously track changes in product status and storage environment to maintain product quality.

[0107] See also Figure 5 , the steps for obtaining the space configuration plan are as follows:

[0108] Analyze the quality and shelf life requirements of meat products based on equipment adjustment instructions and data received from graded storage plans, determine storage priorities for differentiated products, and generate product classification and priority lists;

[0109] After receiving equipment adjustment instructions and hierarchical storage plans, various meat products are first subjected to detailed quality inspections and shelf life assessments. High-precision scanning and sensor technology are used to obtain product status data, which includes weight, volume, temperature sensitivity and potential shelf life. Through data analysis, the specific storage requirements and shelf space configuration of each product are determined. For example, meat with high shelf life requirements is placed in the low temperature area, and heavier products are placed on the bottom shelves. This process ensures that the storage environment and space utilization are dynamically optimized according to the actual product situation, providing a scientific basis for the adjustment of shelf configuration and temperature control areas.

[0110] Based on the product classification and priority list, an optimization algorithm is applied to reconfigure the shelves and temperature control zones using the formula:

[0111] ;

[0112] Generate preliminary shelf and temperature control configuration plans, including: Indicates products The priority of and Represent products Volume requirements and temperature control requirements, is a function adjusted according to storage conditions, Indicates the total number of products;

[0113] The benefit of the formula is that it allows the system to dynamically adjust the space configuration according to the specific needs and priorities of each product, optimizing the efficiency of the use of shelves and temperature-controlled areas;

[0114] There are five differentiated products, each with a priority They are 1, 2, 3, 4, and 5 respectively, and the volume requirements of each product 10, 20, 30, 40, 50 cubic meters respectively, temperature requirements They are 2, 3, 5, 7, and 9 degrees respectively, and the function Adjust the return value according to volume and temperature requirements , then the formula is calculated :

[0115] ;

[0116] This result shows that the system is able to handle diverse storage requirements and optimize space configuration.

[0117] Combine the preliminary shelf and temperature control configuration plan with the real-time operating conditions of the warehouse to configure the space, store the products according to the quality standards and shelf life, and generate a space configuration plan;

[0118] Based on the quality inspection results and shelf configuration data of the first two steps, the final space configuration plan is implemented. This plan is not only based on the physical and chemical stability requirements of the product, but also refers to the risk of cross-contamination and ease of operation. During the implementation process, the automation system is used to adjust the shelf position, optimize the storage path, reduce manual handling, and ensure that all kinds of meat products are stored in the optimal environment, thereby maximizing storage efficiency and product shelf life; the system also adjusts the temperature control settings through real-time monitoring to maintain suitable climatic conditions, thereby extending the market life of the product and reducing waste. The final output of the detailed space configuration plan makes warehouse management more refined, faster in response, and better able to meet the rapidly changing market needs.

[0119] See also Figure 6 , the steps to obtain the optimized layout plan are as follows:

[0120] Analyze space configuration plans, identify space utilization areas in the current warehouse layout, determine storage requirements and shelf life limitations of each meat product through data analysis, and generate demand and utilization analysis results;

[0121] Analyze the differentiated storage requirements and shelf life mentioned in the space configuration plan, determine the best storage method and location for meat products, and conduct a segmented assessment of the existing layout of the warehouse based on the weight, volume and sensitivity of the products. This analysis is achieved through data collection and model simulation to ensure that the storage environment for each product is optimal. Finally, a specific storage demand analysis report is obtained, which lists in detail the optimal storage conditions and recommended storage areas for each product.

[0122] Based on the demand and utilization analysis results, redesign and adjust the warehouse space layout using the formula:

[0123] ;

[0124] Generate a detailed draft warehouse layout, where: Indicates products Required storage area, For products The priority of Indicates the warehouse layout area for each product;

[0125] The formula effectively optimizes warehouse space layout by calculating the contribution of differentiated product types to space demand and combining product priorities to ensure that high-priority products are given priority in obtaining suitable storage conditions.

[0126] To determine the storage area required for a specific product type , analyzing the storage data and product turnover rate over the past year, among which, Weights are assigned based on product sales speed and sensitivity, expressed as a score of 1-5. The specific values ​​are obtained through market demand data. For example, for type A meat products, 20 square meters, is 4, calculated by the formula: square meters;

[0127] The results show that type A meat products require 80 square meters of priority storage space, which helps improve inventory management and increase space utilization efficiency.

[0128] Implement detailed warehouse layout draft, test the layout's operational efficiency through dynamic simulation, optimize storage conditions for product types, and generate optimized layout plans;

[0129] Implement the warehouse layout designed in the previous step, and verify the effectiveness of the new layout through actual layout adjustment and dynamic simulation testing. The simulation test includes the entry and exit efficiency test and emergency access response time evaluation of each product. The test ensures that all products can be quickly accessed in an emergency, thereby optimizing the inventory turnover speed. The final layout plan generated not only improves space utilization, but also improves the safety and efficiency of warehouse operations, ensuring that the storage area of ​​each product can respond quickly to changes in market demand.

[0130] See also Figure 7 ,The specific steps for obtaining logistics efficiency data are as follows:

[0131] Based on the optimized layout plan, data collection is initialized, real-time inbound and outbound data is captured through real-time monitoring, the cargo flow frequency and timestamp of each area are recorded, and cargo mobility results are generated;

[0132] Initialize data collection and collect the optimized warehouse layout plan and real-time in-and-out warehouse data through the real-time monitoring system. The data records the frequency and timestamp of cargo flow in each area in detail, generates a detailed cargo mobility report, and provides basic data. The system uses sensors and Internet of Things technology to monitor cargo activities in various parts of the warehouse to ensure that the collected data is accurate and updated in real time. The report generated by this data will reflect the real-time operation status of the warehouse, so that warehouse managers can have a comprehensive understanding of the cargo flow situation, so as to facilitate subsequent scheduling decision optimization.

[0133] Analyze the cargo mobility results and apply statistical models to predict the handling and scheduling efficiency of multiple regions using the formula:

[0134] ;

[0135] Evaluate and optimize logistics scheduling to generate data-driven logistics efficiency results ,in, Representative Processing time for the region, Indicates Frequency of use of the area, is the total number of scheduling events;

[0136] The benefit of the formula is that by quantifying the frequency of use and processing time of each area, it can effectively predict the efficiency of handling scheduling, help optimize the allocation of human and mechanical resources, thereby reducing waiting time and improving the overall speed of warehouse operations;

[0137] Set a specific time period. Event, a certain area Processing time Minutes, frequency of use , substitute into the formula to calculate , indicating the efficiency index of this area;

[0138] This result shows that by comparing the difference in Values, managers can identify areas with low efficiency and adjust resource allocation accordingly, which directly affects the improvement of logistics efficiency.

[0139] According to the data-driven logistics efficiency results, adjust the warehouse's handling and scheduling strategies, including the handling tools and personnel allocation plan, and obtain logistics efficiency data;

[0140] According to the logistics efficiency results obtained in the previous step, the warehouse handling scheduling strategy is adjusted, including specific handling tools and personnel allocation plans, as well as special measures to cope with peak periods, to generate logistics efficiency data. The strategy adjustment is based on data-driven analysis. By analyzing the data of differentiated time periods and regions, a more reasonable manpower and machinery scheduling plan is formulated, such as increasing manpower in high-demand areas or adjusting handling routes to reduce congestion. The data reflects the direct results of the scheduling strategy and provides a basis for further optimization. The ultimate goal is to verify the effectiveness and accuracy of the model through actual operations.

[0141] See also Figure 8 , the specific steps for obtaining the optimized outbound dispatching strategy are as follows:

[0142] Based on logistics efficiency data, real-time monitoring is used to capture data about the outbound process, including outbound time, frequency, and personnel efficiency, identify process bottlenecks and efficiency issues, and integrate data to conduct preliminary trend analysis and pattern recognition to generate detailed outbound performance results;

[0143] Data is collected through a real-time monitoring system that covers all aspects of the warehouse delivery process. Key performance indicators including warehouse delivery time, frequency, and personnel efficiency are collected, and data is analyzed to identify bottlenecks and efficiency issues in the process. This method ensures the accuracy and real-time nature of data analysis. By integrating data, preliminary trend analysis and pattern recognition are performed to provide support for further decision-making analysis. The generated detailed warehouse delivery performance report will provide data support and decision-making basis for the formulation of scheduling strategies.

[0144] Use the results of warehouse performance refinement to determine the optimal resource allocation and time schedule, apply decision analysis tools to evaluate the potential impact of differentiated warehouse strategies, and use the formula:

[0145] ;

[0146] Calculate the expected exit rate of the generated strategy ,in, Indicates the average time of a single warehouse operation. represents the total number of shipments processed during the assessment period, represents the number of hours worked;

[0147] The benefit of the formula is that by calculating the expected warehouse exit rate of each strategy, it can directly affect the optimization of resource allocation and time scheduling, thereby improving the overall warehouse exit efficiency;

[0148] Assume that there are 30 working days in a month and 8 working hours per day, then the total working hours hours, if 600 shipments are processed during this period and the average processing time for each shipment is 0.5 hours, then Hour, batch;

[0149] Substitute into the formula to calculate: Batch / hour;

[0150] The results show that the average efficiency of the current warehouse exit operation is 1.25 batches per hour. This data will be used to compare the effects of differentiated strategies to select the most optimized warehouse exit strategy.

[0151] Based on the expected warehouse delivery rate of the strategy, redesign and adjust the warehouse delivery plan and personnel scheduling, implement new warehouse delivery process optimization measures, use simulation software to test the implementation effect of the new strategy, verify the real-time impact, apply the optimized strategy to the current operation, and continuously monitor the adjusted effect to generate the optimized warehouse delivery scheduling strategy.

[0152] Based on the analysis results in the previous step, adjust the warehouse plan and personnel scheduling, and use simulation software to test the effectiveness of the new strategy. This step is a decision-making process driven by actual data. You can significantly see the specific impact of the differentiation strategy on the warehouse speed. The implementation of new warehouse process optimization measures, through testing in a controlled environment, ensure the effectiveness of the adjustment measures, and finally apply the adjustments to daily operations. Continue to monitor the adjusted warehouse efficiency and speed to ensure the continuous optimization and efficiency improvement of the warehouse process.

[0153] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An intelligent management system for meat storage, characterized in that: The system comprises: The environmental control module uses temperature and humidity sensors to measure the temperature control equipment in the warehouse to adjust the air conditioning and ventilation facilities, generate environmental steady-state parameters, and based on the environmental steady-state parameters, maintain environmental stability, adjust the operating status of the equipment inside the warehouse, adjust the internal equipment settings, and generate equipment adjustment instructions; The steps for generating the device adjustment instruction are specifically as follows: The temperature and humidity sensors are used to measure the temperature control equipment in the warehouse to adjust the air conditioning and ventilation facilities, monitor the temperature and humidity in the warehouse in real time, record the current temperature and humidity, and generate environmental data records; According to the environmental data records, the influence of temperature and humidity on the overall environmental steady state is balanced by the formula: ； Generate environmental steady-state parameters, where Represents the temperature value, Represents the humidity value, represents the environmental steady-state parameter; Using the environmental steady-state parameters, adjusting the settings of air conditioning and ventilation equipment, including adjusting temperature settings and ventilation switch states, optimizing equipment operation strategies according to the values ​​of the environmental steady-state parameters, and generating equipment adjustment instructions; The quality monitoring module checks the packaging of the meat products through a scanner according to the equipment adjustment instruction, and performs quality grading on the products entering the warehouse to generate quality grading results. Based on the quality grading results, the meat products are classified and stored to generate a graded storage plan; The steps for generating the quality grading result are specifically as follows: Instruct the scanner to start working according to the signal of receiving the device adjustment instruction, and scan the meat product packaging entering the warehouse, including the packaging integrity, label information and visible defects, to obtain preliminary scanning data; A quality assessment model is applied to the preliminary scan data, based on the weights of package integrity and label information, calculated by the formula: ； Generating a packaging quality score ,in, Represents the packaging integrity score, Represents the matching degree of label information, and are the weight coefficients of the two items respectively; According to the packaging quality score , grade the quality of the products, use the quality threshold judgment logic to determine whether the products meet the warehouse standards, assign grades to each product, and generate quality grading results; The steps for generating the hierarchical storage solution are specifically as follows: Based on the quality grading results, identifying matching storage areas and evaluating corresponding storage conditions according to the quality grade indication of each product, and generating classification and area matching records with reference to the characteristics of the product including temperature sensitivity and humidity requirements; According to the classification and area matching records, the storage demand model is used to calculate the space allocation for the number of products of each quality level, using the formula: ； Calculate the total storage space required , generating the estimated storage requirements for the quality level, where Represents the number of products with different quality levels, Indicates the space occupancy factor of the corresponding level; Combine the estimated storage demand of the quality grade with the real-time available warehouse space to configure the space, adjust the storage layout, optimize the space utilization efficiency and product quality, store the products under the best conditions, and generate a hierarchical storage plan; The space optimization module reconfigures the shelves and temperature control areas according to the equipment adjustment instructions and the hierarchical storage plan, evaluates the quality and shelf life of the meat products, generates a space configuration plan, and optimizes the storage layout and space utilization by using the space configuration plan to generate an optimized layout plan; Based on the optimized layout plan and real-time warehouse entry and exit data, the logistics coordination module dispatches the handling scheduling tools and personnel in the warehouse, obtains logistics efficiency data, adjusts the warehouse exit plan and personnel scheduling based on the logistics efficiency data, optimizes the warehouse exit process and adjusts the warehouse layout, and generates an optimized warehouse exit scheduling strategy.

2. The meat storage intelligent management system according to claim 1 is characterized in that: The steps for generating the space configuration scheme are specifically as follows: Analyze the quality and shelf life requirements of meat products based on the data received from the equipment adjustment instructions and the graded storage plan, determine the storage priority of differentiated products, and generate a product classification and priority list; Based on the product classification and priority list, an optimization algorithm is applied to reconfigure the shelves and temperature control zones using the formula: ； Generate preliminary shelf and temperature control configuration plans, including: Indicates products The priority of and Represent products Volume requirements and temperature control requirements, is a function adjusted according to storage conditions, Indicates the total number of products; Combining the preliminary shelf and temperature control configuration plan with the real-time operating conditions of the warehouse, space configuration is performed, products are stored according to quality standards and shelf life, and a space configuration plan is generated.

3. The intelligent management system for meat storage according to claim 2 is characterized in that: The steps for generating the optimized layout solution are specifically as follows: Analyze the space configuration plan, identify the space utilization areas in the current warehouse layout, determine the storage requirements and shelf life limits of each meat product through data analysis, and generate demand and utilization analysis results; Based on the demand and utilization analysis results, the warehouse space layout is redesigned and adjusted using the formula: ； Generate a detailed draft warehouse layout, where: Indicates products Required storage area, For products The priority of Indicates the warehouse layout area for each product; Implement the detailed warehouse layout draft, test the operational efficiency of the layout through dynamic simulation, optimize the storage conditions of product types, and generate an optimized layout plan.

4. The intelligent management system for meat storage according to claim 3 is characterized in that: The steps for obtaining the logistics efficiency data are specifically as follows: Based on the optimized layout plan, data collection is initialized, real-time in-and-out warehouse data is captured through real-time monitoring, the cargo flow frequency and timestamp of each area are recorded, and cargo mobility results are generated; The cargo mobility results are analyzed and a statistical model is applied to predict the handling and scheduling efficiency of multiple regions using the formula: ； Evaluate and optimize logistics scheduling to generate data-driven logistics efficiency results ,in, Representative Processing time for the region, Indicates Frequency of use of the area, is the total number of scheduling events; According to the data-driven logistics efficiency results, the warehouse's handling scheduling strategy is adjusted, including the handling tool and personnel allocation plan, to obtain logistics efficiency data.

5. The intelligent management system for meat storage according to claim 4 is characterized in that: The steps for generating the optimized outbound dispatching strategy are as follows: Based on the logistics efficiency data, real-time monitoring is used to capture data about the warehouse exit process, including warehouse exit time, frequency, and personnel efficiency, identify process bottlenecks and efficiency issues, and integrate the data to conduct preliminary trend analysis and pattern recognition to generate detailed results of warehouse exit performance; Using the results of the warehouse performance refinement, determine the optimal resource allocation and time schedule, apply decision analysis tools to evaluate the potential impact of differentiated warehouse strategies, and use the formula: ； Calculate the expected exit rate of the generated strategy ,in, Indicates the average time of a single warehouse operation. represents the total number of shipments processed during the assessment period, represents the number of hours worked; Based on the expected warehouse delivery rate of the strategy, redesign and adjust the warehouse delivery plan and personnel scheduling, implement new warehouse delivery process optimization measures, use simulation software to test the implementation effect of the new strategy, verify the real-time impact, apply the optimized strategy to the current operation, and continuously monitor the adjusted effect to generate the optimized warehouse delivery scheduling strategy.

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