258results about How to "Reduce inventory costs" patented technology

The invention provides an inventory optimization method and system based on a deep learning model, and relates to the technical field of deep learning, and the method comprises the steps: obtaining the multi-dimensional data of a commodity, constructing a dynamic convolution kernel through employing a graph neural network, constructing a soft clustering distribution matrix in combination with a multi-layer perceptron, and obtaining a long-term dependence feature fusing a space dimension and a time dimension. And fusing the short-term and long-term features, inputting the fused short-term and long-term features into a bidirectional long-short-term memory network to generate a sales prediction sequence, and calculating a prediction confidence interval to obtain a final sales prediction result. And calculating a safe inventory level based on a sales prediction result, generating a replenishment decision by using a dynamic planning model based on deep reinforcement learning in combination with an inventory cost function, and finally sending the decision to a supply chain execution system. The sales volume is accurately predicted through the deep learning model, the inventory management is optimized, the storage cost, the stockout cost and the overstock cost are reduced, and the supply chain efficiency is effectively improved.

The invention relates to the technical field of material management, and discloses an infrastructure material cyclic application management and control system, which comprises the following modules: an intelligent material identification and real-time data acquisition module, which is used for carrying out automatic identification, classification and real-time data acquisition on infrastructure materials based on various sensor technologies (visual identification, RFID, laser scanning and NFC) and a deep learning algorithm, a digital material file is generated, and dynamic tracking and accurate positioning of materials are achieved; and the block chain-based full life cycle management module is used for carrying out data management and encrypted storage on the full life cycle (from purchasing, transportation, storage, use, maintenance, cyclic utilization to scrapping treatment) of the materials. Through close combination of a multi-mode sensor technology (visual identification, RFID, laser scanning and NFC) and a deep learning algorithm, all-directional and multi-dimensional identification and real-time data acquisition can be performed on capital construction materials in a complex and changeable environment.

The invention relates to the technical field of logistics informatization management, and discloses a warehousing method for logistics informatization management, and the method comprises the steps: 1, determining the target and demands of warehouse management, and reasonably planning a warehouse region according to the actual condition of a warehouse; 2, inputting detailed information of the goods into a warehouse management system, and inputting and managing customer information; 3, receiving purchased commodities, and carrying out inventory management and ex-warehouse management; 4, collecting various data in the warehousing operation process in real time, including the warehousing quantity, the ex-warehouse quantity, the stock quantity and the operation efficiency, and providing a decision support function according to a data analysis result; and 5, regularly maintaining and checking the warehouse management system to ensure the stable operation of the system and the safety of data. According to the warehousing system for reducing manual operation and paper file processing and logistics informatization management, automatic equipment, an information system and the Internet of Things technology are adopted, and the management efficiency and accuracy are greatly improved.

The invention discloses an electric power material supply management and control system and a method thereof. The electric power material supply management and control system comprises a master control center, a sub-control center, a material warehouse, a mobile control terminal and a data processing platform. The electric power material supply management and control method comprises the following steps: S1, material demand prediction; s2, intelligent scheduling; s3, performing real-time monitoring; s4, risk assessment and early warning; and S5, emergency response is carried out. The electric power material supply management and control system and the method thereof can improve the material supply efficiency, enhance the decision support capability, make the decision more accurate and efficient, help to optimize resource configuration, improve the overall operation efficiency, improve the transparency and visualization of a supply chain, enhance risk management, guarantee the safe and stable operation of a power grid, improve the emergency response speed, and improve the power supply efficiency. The resource allocation is optimized, the inventory cost is reduced, the fund utilization efficiency is improved, the optimal allocation of resources is realized, and the electric power material requirements of each region can be better met.

The invention relates to the field of allocation, and discloses a spare part allocation method for multiple warehouses, and the method comprises the steps: obtaining spare part inventory information and historical spare part delivery data of each warehouse in a plurality of warehouses; analyzing the stock quantity corresponding to each spare part model to obtain an out-of-stock spare part model of each warehouse, and determining the warehouse corresponding to the out-of-stock spare part model as a spare part receiving warehouse; according to the historical spare part ex-warehouse data and spare part inventory information of each warehouse, a spare part allocation list is determined; sending the spare part allocation list to a plurality of auditing terminal devices; after checking of the spare part allocation list is completed, allocation delivery information corresponding to the spare part allocation list is generated, and the allocation delivery information corresponding to the spare part allocation list is sent to a delivery terminal device corresponding to a target spare part delivery warehouse; and monitoring the allocation and transportation information, and if it is monitored that the allocation and transportation information is received, generating allocation and receiving information of the spare part allocation list. Therefore, multi-warehouse spare part allocation is realized.

The invention discloses an intelligent commodity management method, and relates to the technical field of commodity management. Through the design of the whole method, the efficiency can be improved, the intelligent system can automatically manage a plurality of goods management tasks such as inventory management, purchase decision making and demand prediction, manual intervention is reduced, the management efficiency is improved, inventory optimization is facilitated, the intelligent system can accurately predict demands through data analysis and prediction algorithms, and the management efficiency is improved. The inventory level is optimized according to the prediction result, the inventory overstock or stockout phenomenon is avoided, the inventory turnover rate is improved, the cost is reduced conveniently, the intelligent system can help enterprises to optimize purchasing strategies and reduce the inventory cost, the purchasing cost is reduced through price optimization and other modes, and therefore the overall cost of the enterprises is reduced, and the enterprise experience is improved. The customer satisfaction can be improved conveniently under the overall application, and the customer satisfaction can be improved and the customer loyalty can be enhanced by meeting customer requirements in time, accurately predicting the market trend and providing personalized services and intelligent commodity management.

The invention discloses a knowledge graph retrieval intelligent power storage system based on a feedforward neural network, and relates to the field of power equipment accessory management. The method comprises the following steps: constructing a power equipment resource classification model and a meteorological disaster risk periodic evaluation model in a coverage storage range; obtaining static data and dynamic data of different power devices; predicting the replacement demand level of the equipment through the feedforward neural network model; a model prediction evaluation result is used as a data source of the knowledge graph warehousing system, and terminal real-time fault prediction evaluation query, periodic equipment purchase guidance and backlog warning are realized. According to the invention, the storage demand can be intelligently predicted according to the actual state of the power equipment, the accuracy and response speed of storage management are improved, and an efficient spare part support scheme is provided for power network maintenance and equipment storage.

The invention discloses an intelligent order flexible processing production scheduling management method, and relates to the technical field of order management. The method comprises the steps of obtaining demand data from a baking order management system and performing priority classification on orders to ensure timely delivery of important orders and improve customer satisfaction. The future consumption of the baking raw materials is predicted through a time sequence prediction algorithm, the inventory cost is reduced, and the production continuity is guaranteed. And configuration of production equipment, workers and raw materials is optimized through mixed integer linear programming, reasonable utilization of resources is achieved, and the production efficiency is improved. The production progress and the variation of raw material consumption are controlled and monitored through the statistical process, abnormal conditions are recognized in time, and stable product quality is ensured. And flexible processing scheduling adjustment is carried out according to the production abnormity index, and the adaptability of the production system is enhanced. In conclusion, according to the method, the intelligent level of production management is effectively improved, the production process is optimized, and powerful support is provided for enterprises in the market with fierce competition.

The invention relates to the technical field of logistics, in particular to an intelligent stereoscopic warehouse and an operation method thereof. The method comprises the following steps: carrying out logistics tracking data acquisition on goods to be warehoused to obtain a current logistics tracking data set; according to the current logistics tracking data set, goods to be warehoused are classified, a goods classification list is obtained, and the goods classification list comprises a plurality of site fragile goods lists and a plurality of site non-fragile goods lists; according to the goods classification list, carrying out storage interval distribution on the to-be-warehoused goods to obtain a goods storage interval distribution list; according to the cargo storage interval distribution list, carrying out storage location distribution on the to-be-warehoused cargo to obtain a cargo storage location mapping table; and performing logistics updating on the current logistics tracking data set according to the cargo storage position mapping table to obtain an updated logistics tracking data set. The space utilization rate and the storage efficiency of the intelligent stereoscopic warehouse are improved, and the space pressure of a logistics center is effectively relieved.

The invention provides a medical consumable refined management method and system, and the method comprises the steps: a medical consumable database establishment step: carrying out the warehousing management of medical consumables, and establishing a database containing the information of various medical consumables; dynamic management of the medical consumables: in the use process of the medical consumables, obtaining ex-warehouse and use information of the medical consumables, linking with the database, and dynamically updating the database in real time; a first data analysis step: on the basis of the database information and the dynamic update information, using a big data model to predict the use cycles of various consumables, and realizing refinement of consumable management and control; and a purchase strategy output step: based on the period predicted by the big data model, setting the upper limit and the lower limit of the inventory of various consumables, and when a certain medical consumable exceeds the lower limit, outputting a purchase plan of the medical consumables to provide reference for the purchase behavior of purchasers. The inventory of the medical institution is reduced, and the inventory cost of the medical institution is effectively reduced.

The invention discloses a new tea drink sales volume prediction method and system based on a graph neural network, and the method comprises the steps: building an algorithm model trained based on spatial features and time sequence features through employing the graph neural network; according to the invention, store sales volume prediction can be carried out in different festivals and holidays, sales promotion activities, weather conditions, store business districts and consumer groups. By constructing a graph network topology structure based on stores, modeling is performed on store information data by adopting an undirected weighted graph, and the influence of surrounding stores on the current store is fully considered, so that the sales volume of each store is predicted; the problem that a conventional method is inaccurate in prediction due to the industry characteristics of short commodity life cycle, old product degradation, high commodity renewal speed and the like in the new tea beverage industry is solved, the number of stockout times and the inventory cost of the commodities are reduced, and therefore the store income is increased.

The invention relates to a digital factory production management method and system, and the method comprises the steps: predicting a future initial order demand based on a data analysis tool and historical sales data, and adjusting the initial order demand based on a current market trend and a current market strategy corresponding to a target peer, and obtaining a target order demand; obtaining the required production capacity and the equipment utilization rate corresponding to each piece of production equipment based on the target order demand; acquiring real-time operation data corresponding to each piece of production equipment, and predicting maintenance requirements corresponding to the real-time operation data, the required production capacity and the equipment utilization rate based on the trained deep learning model; and making a maintenance plan of each production device in advance based on the maintenance demand and the maintenance priority corresponding to each production device. The production equipment is subjected to preventive maintenance, the reliability and stability of the production equipment are improved, the use of maintenance resources is optimized, and the maintenance efficiency and quality are improved.

The invention relates to a garment customization system and method based on the Internet of Things, and belongs to the field of garment customization. The garment customization system based on the Internet of Things comprises a terminal, a size data generation module and a garment customization module. The terminal is used for collecting images and size data uploaded by a user; the size data generation module is used for carrying out feature extraction on the uploaded image and then reconstructing a human body image to generate size data of each part; the clothing customization module is used for matching the image output by the terminal to generate a virtual fitting picture, and the virtual fitting picture is used as a customization effect picture to be sent to the terminal after being subjected to aesthetic evaluation, secondary creation and aesthetic reevaluation; and the terminal combines the customization effect picture with the size data of each part of the human body to generate a garment customization order. According to the invention, based on the virtual fitting technology and the multi-dimensional aesthetic evaluation technology, the highly personalized customization service is provided for the user, and the accuracy of the online customization effect picture and the satisfaction degree of the user are effectively improved.

The utility model discloses a switch assembly, which comprises an isolating switch assembly and a circuit breaker assembly, a pole of the circuit breaker assembly is connected with a second voltage-sharing cover, the second voltage-sharing cover is internally provided with a cam assembly, and the cam assembly is connected with a second driving shaft; a vacuum bubble assembly is arranged in the pole, the vacuum bubble assembly comprises a vacuum static contact and a vacuum moving contact, the vacuum static contact is connected with the isolating switch assembly, and the vacuum moving contact is connected with the cam assembly; the vacuum moving contact is connected with a flexible connector, and the other end of the flexible connector is led out from the end portion, deviating from the isolation switch assembly, of the second voltage-sharing cover. According to the utility model, the flexible connection is led out from the end part of the second voltage-sharing cover to be connected with the bus, the overall appearance of the switch cabinet is tidy and elegant, the universality of accessories is high, most accessories are only required to be equipped with the same accessories for two isolation switch structural forms, the cost of the accessories is reduced, and the occupation of inventory and production resources is also reduced; and the inventory cost and the production cost are reduced.

The invention discloses a visual storage tracking management system based on steel structure production, and the system comprises an original data obtaining module which is used for obtaining a plurality of pieces of original material demand data at a current time point; the feature processing module is used for performing feature processing on the plurality of original material demand data at the current time point to obtain a material demand vector at the current time point; the vector input module is used for inputting the material demand vector at the current time point into a pre-trained ARIMA parent model; the demand output module is used for the ARIMA parent model to respectively remove long-term trend fluctuation and short-term random disturbance in the time sequence through an internal sub-model, and outputting an original material demand prediction value in a time window defined by a user based on a current time point; according to the method, the lag structure and the residual influence of the time sequence in the steel structure production raw material demand data can be accurate, and the prediction accuracy of the steel structure production raw material demand is remarkably improved in combination with the time window and the sliding calculation mode defined by the user.

The utility model belongs to the technical field of motor vehicles and air filters, and particularly relates to an air filter silencing exhaust pipe and an air filter. The exhaust pipe comprises a flexible pipe body and a rigid pipe body which are connected together; the rigid pipe body comprises an inner pipe body and an outer cover body covering the inner pipe body, a plurality of spacing plates arranged in the extending direction of the inner pipe body are arranged in a gap formed between the inner pipe body and the outer cover body, and a resonant cavity is formed between every two adjacent spacing plates; at least one opening corresponding to each resonant cavity is formed in the pipe wall of the inner pipe body, and the inner space of the inner pipe body is communicated with the resonant cavities. According to the air filter exhaust pipe, the sound wave interference principle is utilized, noise of different frequencies generated when airflow passes through is effectively reduced, the exhaust pipe is allowed to adapt to a complex installation path, and the air filter exhaust pipe can be conveniently installed in a narrow or irregular engine compartment. On the basis, the utility model further provides an air filter which has a good noise reduction effect, sealing performance and adaptation performance.

The invention discloses a configuration optimization method based on low-demand and non-low-demand ship spare parts, and belongs to the technical field of water surface JT equipment guarantee, and the method comprises the steps: solving a low-demand ship spare part configuration optimization model through employing improved gray Markov prediction; a TOPSIS-fused multi-target particle swarm optimization algorithm is adopted to solve the non-low-demand ship spare part configuration optimization model; and performing analogue simulation on an optimal spare part configuration list obtained by solving the multi-target particle swarm optimization model by adopting Monte Carlo, performing a simulation experiment by utilizing the configuration model, and verifying the multi-target particle swarm optimization model. According to the method, the low-demand spare part configuration optimization model and the non-low-demand spare part configuration optimization model are fused, and a better ship spare part configuration optimization method is realized by virtue of respective advantages, so that continuous, safe and reliable operation of a ship is ensured. And the configuration optimization efficiency and accuracy are improved.

The invention provides a data management method and system, electronic equipment and a storage medium, and belongs to the technical field of data management. The method comprises the following steps: preprocessing first data to obtain a time-space law of the first data; the first data is original data sent to the background management platform by the vending machine; determining a target data analysis model based on the time-space law of the first data; and inputting the second data into the target data analysis model to obtain a commodity adjustment strategy corresponding to the vending machine. The space-time law comprises time dimension features and space dimension features, and the target data analysis model comprises a time sequence analysis model and a space analysis model. According to the data management method and system, the electronic equipment and the storage medium provided by the invention, the data management efficiency can be effectively improved.

The invention relates to the field related to food safety, in particular to a food origin traceability system which comprises an information inquiry module and a user feedback module. The information inquiry module provides detailed information of food production places, production, processing, transportation and the like, and helps consumers and supervision departments to know food sources and safety. The user feedback module allows consumers to evaluate food quality and safety, and feedback information is stored and can be inquired by other consumers. Meanwhile, the food safety is improved, and it is ensured that problem food can be handled in time through transparent information and the rapid tracing ability; the consumer trust is enhanced, and the public traceability information and feedback evaluation improve the confidence of the consumer on the brand; the enterprise competitiveness is improved, and the enterprise can improve the product quality through feedback; market supervision is promoted, and real-time monitoring and food fraud prevention of supervision departments are facilitated; technical innovation and industrial upgrading are promoted, and standardization and informatization development of the food industry is promoted.

The invention relates to the technical field of material management, in particular to a T10 material management system and method based on an RFID reader. Comprising an RFID tag management module, an RFID reading management module, a material detection module, an inventory management module, a data storage module and a display module. According to the invention, the RFID tag management module writes data information of materials into RFID tags and establishes communication with an RFID reader in the RFID reading management module, and the inventory management module identifies the RFID tags by using the RFID reader and generates a log of the day, so that statistics of the number of products in a warehouse is realized; and a plurality of non-inductive sensors in the material detection module are used for detecting the temperature around the unfrozen product and changing the unfreezing time information in the RFID tag, so that the unfreezing time of the frozen product is adjusted in real time, the ex-warehouse speed of the product is increased, and the ex-warehouse quality of the product is ensured.

The invention discloses a fabric inventory optimization method and system, and the method comprises the steps: collecting market, sales and production data; predicting a fabric demand according to the collected data; planning fabric purchase and production plans according to the predicted demands, and making inventory space planning in advance; and monitoring the fabric inventory level in real time, and adjusting the purchase and production plan according to the inventory level. According to the invention, market demands and trends can be reflected in real time, fabric demands can be effectively predicted and planned, the inventory level can be dynamically adjusted, and optimal management of fabric inventory is realized.

The invention discloses a control and regulation system for hemostatic gauze production, which comprises a raw material supply control module, a production process monitoring module, an intelligent regulation execution module, a quality detection and feedback module and a human-computer interaction interface, and is characterized in that the raw material supply module is used for accurately controlling raw material supply and is provided with a material level sensor and a stirring device; the conveying speed is accurately regulated and controlled through a formula, the uniformity of raw materials is ensured, the production process monitoring module monitors key parameters in real time, the sensor wirelessly transmits data, and the intelligent adjusting module automatically adjusts equipment operation parameters. The quality detection module detects products and feeds back results, and a man-machine interaction interface is convenient to operate. Through cooperation of all the modules, raw material supply is accurately controlled, production parameters are monitored in real time, equipment operation is intelligently adjusted, product quality is strictly detected, convenient interaction is provided, the production quality and efficiency of hemostatic gauze are improved, cost is reduced, and high-quality and reliable hemostatic products are provided for the medical field.

The invention provides a digital center optimization method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining enterprise business process data, including order processing, inventory management, supply chain coordination and customer feedback, and carrying out the preprocessing of the enterprise business process data, so as to obtain a processed data pool; constructing a digital transformation center model according to the processed data pool; defining a fitness function to evaluate the performance of the current digital transformation hub model; and performing iterative optimization on the digital transformation center model through selection, crossover and mutation operations until a preset number of iterations is reached, so as to obtain an optimized digital transformation center model. According to the method, the digital transformation center model is constructed and optimized, so that the enterprise business process is effectively adjusted, the order processing, inventory management and supply chain coordination efficiency is improved, and the optimization of digital transformation is realized.

The utility model discloses a terminal block capable of being spliced, which comprises a plurality of plastic monomers, each plastic monomer is provided with a terminal piece and an elastic piece, the terminal piece is used for being connected with an external lead, and the elastic piece is used for clamping the external lead; and a plurality of plastic monomers can be spliced to form a combined terminal block. The splicable terminal block is simple in structure, and a plurality of plastic monomers can be spliced at will to form terminal blocks with different Pin numbers only by designing and manufacturing a mold for producing one plastic monomer, so that the production efficiency of the terminal block is improved, and the manufacturing cost of the terminal block, the manufacturing cost of the mold and the inventory cost are reduced.

The invention discloses a storage traceability method for teak cut raw materials, and belongs to the technical field of wood storage, and the method comprises the following steps: S11, generating a two-dimensional code: cutting teak logs to form teak raw materials; s12, warehousing operation is carried out, wherein the generated two-dimensional codes are printed and pasted to goods shelf bins, and the cut teak raw materials are stored to the corresponding goods shelf bins; s13, inventory management: carrying out inventory management on the raw material information recorded by the two-dimensional code through a warehouse management system; s21, warehouse-out application is carried out; s22, warehouse-out auditing: marking the goods shelf positions where the candidate raw materials are located, and forming a warehouse-out application form; s23, warehouse-out operation: according to the warehouse-out application form, taking out the candidate raw materials on the corresponding goods shelf positions, and carrying out matching operation; and S24, updating inventory data. The unique two-dimensional code is generated for each batch or each piece of cut teak raw material, and detailed raw material information is recorded, so that the transparency and traceability of storage information are greatly improved.

The invention discloses a radioactive waste graphite incineration treatment and tail gas purification and sealing treatment process, and relates to the field of radioactive waste treatment. Flue gas generated by incineration treatment is cooled and purified; according to the present invention, the carbon dioxide in the cooled and purified flue gas is concentrated and compressed, and the compressed carbon dioxide is subjected to geological storage so as to achieve the permanent fixation of the 14C, such that the problem that the existing radioactive waste graphite consumes the excessive stock can be solved, the generated secondary radioactive waste is less, and the emission problem of the 14C is avoided through the utilization of the new process.

The application provides a low-cost two-wire serial communication method for multi-device competition, which adopts two signal lines to realize bus arbitration and data transmission among multi-devices, wherein any signal line is used as a chip selection line, another signal line is used as a bidirectional data line, chip selection pins of all devices are configured as open-drain output, the chip selection line is connected to a positive electrode of a power supply through an external pull-up resistor, and a high level in a normal state represents a bus idle; when multiple devices share the same bus, distributed arbitration is realized through the following steps: a device continuously monitors a state of the chip selection line before sending data; if the state of the chip selection line is a high level, the device pulls down the chip selection line to attempt to obtain control right of the bus; if the state of the chip selection line is a low level, the device waits until the chip selection line is released; the device obtaining the sending permission sends data with a self-defined frame structure through the bidirectional data line; after the sending is completed, the device obtaining the sending permission releases the chip selection line.

The invention relates to the technical field of buildings, and discloses a recyclable universal back arris and a mounting method.The recyclable universal back arris comprises two back arris bodies and a connecting frame, each back arris body comprises two camber beams, a plurality of connecting plates are welded between the two camber beams, and the connecting frame is connected with the camber beams. The camber beams, the connecting plates and the connecting frames are all made of steel. The ends, close to each other, of the two back ridge bodies are slidably connected to the outer side of the connecting frame, and an adjusting mechanism is arranged in the connecting frame. The back arris is reasonable in design, the back arris is made of steel, the back arris has extremely high strength and bearing capacity, the back arris can be conveniently and rapidly installed through the installed installation mechanism, the installation mode is high in universality, and therefore the back arris can be suitable for different use scenes, cyclic utilization of the back arris is facilitated, and the concept of green construction is met; the length of the back ridges can be adjusted according to needs through the adjusting mechanism, and the flexibility and adaptability of construction are improved.

The utility model discloses a repair bar setting device, which comprises an MCU (Microprogrammed Control Unit) main control circuit used as a main processing center of equipment; the display circuit is used for displaying key information generated by man-machine interaction or interaction between equipment; the repair bar equipment interface circuit is used for communicating and connecting with external repair bar equipment; the data storage circuit is used for storing related setting parameter data; the key and buzzer circuit is used for realizing man-machine interaction operation and providing operation feedback; and the power management circuit is used for managing power supply and battery charging of the equipment. According to the repair bar setting device, by simulating a battery form and enhancing a setting interface, the operation convenience and practicability are remarkably improved, the maintenance cost of a mobile phone is reduced, man-machine interaction is optimized by integrating a display screen and functional keys, the setting efficiency is improved, the programmability of the MCU main control circuit provides flexibility for equipment customization, and the repair bar setting device is suitable for popularization and application. Therefore, the mobile phone maintenance tool is economical and efficient.

The invention discloses a park warehouse management system based on a sorting base, which relates to the technical field of warehouse management and comprises a data acquisition module, a sorting priority acquisition module, a warehouse sorting scheduling sequence table generation module, a distance acquisition module, a path point acquisition module and a cargo sorting scheduling path acquisition module. The technical problems that due to the fact that the real-time requirements of all sorting operations in a sorting base are different, processing of high-value goods is delayed, meanwhile, due to the fact that path planning is lacked, sorting equipment moves blindly in the operation process, the sorting equipment needs to frequently move back and forth between different operation areas, and energy consumption and time cost are increased are solved. The path points are sequenced and connected according to the warehouse sorting scheduling sequence table to obtain a cargo sorting scheduling path, a specific driving path is provided for sorting equipment, and it is ensured that all execution allocation tasks are efficiently completed; and the efficiency and the accuracy of logistics warehouse management are further improved.