151 results about "Inventory control" patented technology

The invention provides a green agricultural product distribution path optimization and inventory control method, and the method comprises the steps: selecting a distribution path with the minimum agricultural product quality influence degree as an optimal path according to a prediction result of the agricultural product quality influence degree, and transmitting the optimized distribution path to a distribution vehicle terminal in real time; after the distribution vehicle terminal receives the optimal distribution route issued by the cloud, the distribution route is navigated in real time through a vehicle-mounted navigation system, a driver is guided to drive along the optimal route, and the distribution route is dynamically adjusted according to the real-time road condition information; meanwhile, according to the real-time position and the driving speed of the distribution vehicle, the arrival time of the agricultural products is dynamically estimated, and the estimated arrival time information is pushed to a destination customer to remind the customer to make preparation for receiving goods in advance.

An AI based inventory control system. A first moveable drawer, the first moveable drawer moveable from a first position to a second position. A first camera arranged to generate an image of an inventory item contained within the first moveable drawer. An image processor in operative communication with the first camera, the image processor configured to process the image generated by the first camera. An AI engine performing recognition on the processed image received from the image processor.

The invention relates to the technical field of enterprise cloud management, and discloses an ERP enterprise cloud management system, which comprises a system main body deployed based on a cloud computing architecture, the system main body is integrated with a financial management module, an inventory control module, a purchase management module, a sales management module, a production plan module, a human resource management module and a customer relationship management module, and data interaction interfaces and cooperative work mechanisms are arranged among the modules; data are stored by the cloud storage unit, and a data processing task is executed by the cloud operation unit. The ERP enterprise cloud management system breaks data barriers among departments of an enterprise, integrates core modules of financial management, inventory control, purchase management, sales management, production planning, human resource management, customer relationship management and the like, ensures the accuracy and consistency of data, and realizes the cloud management of the enterprise through a data sharing function. All the modules can obtain needed data and information in real time, and seamless transmission and cooperative work of the information are achieved.

The invention, which relates to the technical field of the warehousing system, discloses an intelligent warehousing system comprising a warehouse management information system and an equipment monitoring and scheduling system. The warehouse management information system comprises a goods management module, a warehouse management module, an order management module, an inventory management module, a warehouse-in and warehouse-out management module, an operation management and implementation module and an abnormity early warning module. According to the intelligent warehousing system, real-time tracking and data collection of articles are achieved through RFID, sensors, bar codes and the like, the data accuracy is improved, the warehouse management system integrates the functions of inventory control, order processing, cargo tracking and the like, automatic management of warehousing operation is achieved, inventory layout is optimized through data analysis and a machine learning algorithm, and the demand trend is predicted; and the decision-making efficiency is effectively improved.

The invention relates to the technical field of inventory control, and particularly discloses an order-returning inventory-returning control method, which specifically comprises the following steps: acquiring a sales order pushed down by a platform; transmitting the sales order to an inventory system for reservation, and determining that the reservation of the sales order is successful if the reservation inventory is sufficient; if the predeterminable inventory is not enough, determining that the sales order is failed in reservation, and determining the sales order which is failed in reservation as an out-of-stock order; acquiring a deficit order created by warehouse personnel; the inventory loss order is transmitted to an inventory system for reservation, and in response to the order cancelling operation of the sales order which is successfully reserved, the inventory system returns the previously occupied reservable inventory; and based on the priority of the out-of-stock order, determining the priority ownership of the occupied reservable stock. Therefore, the time and energy consumption of manual auditing are reduced, the auditing speed is increased, and the processing efficiency is improved. And the priority can be adjusted in real time, so that the timeliness and accuracy of inventory management are ensured.

The invention discloses a supply chain material data management method and a data management system, and particularly relates to the technical field of data management. Through collecting and centrally storing material data of each link of a supply chain, an inventory turnover rate and residence time are analyzed, a safe inventory level is evaluated, and a purchase plan and inventory control are optimized. In order to solve the possible problem that inventory data is not updated in time or input errors occur, interference of the inventory data on inventory turnover rate calculation is evaluated through real-time analysis and abnormal input monitoring, and the accuracy of the inventory data is ensured; according to the method, the accuracy of the inventory turnover rate calculation result is divided into high, medium and low accuracy levels, and corresponding processing is carried out, so that purchase, production and supply chain decisions of enterprises are optimized, strategic decision errors are reduced, and the overall efficiency and response capability of a supply chain are improved.

The invention discloses an optimization method and system for aviation equipment storage and a medium, and the method comprises the steps: collecting multi-dimensional dynamic data, carrying out the fusion cleaning and structural feature extraction, and generating a high-dimensional feature set; outputting a dynamic demand prediction value and uncertainty measurement by using a hybrid intelligent prediction model fusing time sequence prediction and ensemble learning; calculating an optimal inventory control parameter through a stochastic optimization model in combination with the aviation material key grade and the stockout loss cost; and generating an inventory operation instruction according to the optimal inventory control parameter and the real-time inventory state, and outputting a strategy report with confidence evaluation and key influence factor analysis. According to the method, multi-dimensional accurate prediction of the aerial material demand and dynamic optimization of the inventory strategy are realized, the inventory control precision and the resource utilization efficiency are remarkably improved, the stockout risk and the overstocked cost are effectively reduced, and the reliability and the economical efficiency of aviation equipment guarantee are enhanced.

The invention discloses a supply chain material inventory control method and system, and the method comprises the steps: carrying out the demand distortion analysis of the demand signal data of each node in a target supply chain, and obtaining the demand signal distortion amplitude of each node; if the demand signal distortion amplitude exceeds a preset distortion amplitude threshold, performing distortion degree classification prediction on the demand signal distortion amplitude to obtain a real-time demand prediction result of each node; performing sensitivity analysis on the real-time demand prediction result, and generating a safety inventory parameter of each node; generating a collaborative inventory distribution scheme of the target supply chain according to the safety inventory parameters and the information sharing evaluation indexes; and performing cooperative control on the material inventory of each node in the target supply chain according to the cooperative inventory distribution scheme. The flexibility and cooperation efficiency of the supply chain to adapt to the market change can be improved through the cooperation inventory distribution scheme, so that the risk resistance capability is enhanced, and the capability of the supply chain to cope with the market demand fluctuation complex scene is improved.

The invention discloses a building material inventory control and automatic replenishment system based on the Internet of Things, and the system comprises a data collection module which is used for collecting all kinds of building material information and environment data according to a plurality of sensors; the cloud server is used for storing, sorting and analyzing the real-time data and accurately calculating key indexes of each material; the pre-warning module is also used for judging whether replenishment is needed or not according to a preset inventory pre-warning threshold value; the replenishment module is used for automatically triggering a replenishment instruction when it is judged that replenishment is needed, and sending a replenishment order to the corresponding supplier through an information interaction platform with the supplier; a digital twin virtual module is arranged in the local terminal, and the local terminal is used for updating the stock information corresponding to the goods shelf, the goods allocation and the building materials in the digital twin virtual module according to the collected data information and visually displaying the stock information corresponding to the goods shelf, the goods allocation and the building materials. The invention further discloses a building material inventory control and automatic replenishment method based on the Internet of Things. According to the invention, the accuracy of building material inventory management is improved.

Methods and systems are provided for implementing an automated inventory control mechanism. In an embodiment, an operational workflow providing automated inventory control includes automated data collection and automated image data analysis. Automatic data collection includes capturing image data of a storage facility by a capturing device, such as an unmanned aerial vehicle system (UAS). Automated image data analysis includes functions of detecting objects (e.g., containers, trailers, slots, and / or other objects) appearing in the image data (e.g., using a machine learning (ML) model), identifying objects (e.g., objects in the image data, etc. In some embodiments, the method may include collecting image data (e.g., using an ML model), inspecting the object (e.g., including determining a condition and / or location of the object) based on the collected image data and metadata associated with and related to the image data (e.g., using analysis based on advanced mathematical rules), and / or generating results available for use by an inventory management system.

A computer system for vendor negotiation and analysis may be provided. The computer system may be programmed to (i) store a negotiation analysis model for analyzing and facilitating negotiations; (ii) receive a request for a product or service to be provided by a vendor; (iii) analyze a plurality of data for each of a plurality of vendors to determine a ranking of vendors for responding to the request; (iv) determine one or more vendors to contact based upon the ranking of vendors; (v) schedule a meeting with the one or more vendors; (vi) monitor each meeting with the one or more vendors; (vii) generate a recommendation for a vendor to respond to the request based upon the meeting and information about the vendor; and / or (viii) in response to receiving a decision to approve the vendor, generate one or more documents to transmit to the vendor.

The invention discloses a pet food intelligent production management and control system and a traceability code spraying device thereof, and relates to the technical field of pet food production, and the pet food intelligent production management and control system comprises a production planning unit, a raw material management unit, a production control unit, an intelligent mistake proofing unit and a quality traceability unit. The production planning unit optimizes a production plan and accurately allocates resources, the raw material management unit performs supplier qualification evaluation, raw material multi-level quality inspection and intelligent inventory regulation and control, quality is controlled from the source, the supply chain risk is reduced, the production control unit depends on the equipment real-time monitoring and fault early warning technology, the stability of production parameters is guaranteed, and the production efficiency is improved. The intelligent error-proofing unit integrates OCR verification, threshold detection and prediction model construction, rejects error detection data, prevents data missing, realizes real-time early warning and closed-loop processing of quality risks, and eliminates quality problems in the bud stage, and the quality tracing unit performs real-time early warning and closed-loop processing on the quality risks through full-link data acquisition and a unique tracing code. And accurate positioning and rapid recall of problem products are supported.

Embodiments of the present invention provide a trackable device system comprising a modular housing integrated with personal or enterprise assets. The system includes a chipset with wireless communication modules (e.g., BLE, UWB, GPS, or cellular), a processor, location modules, memory, and power management components. The processor supports proximity detection, geofencing, motion-triggered alerts, lost-mode activation, and SOS signaling to emergency contacts. Integration with mobile platforms enables real-time tracking, augmented reality overlays, and compatibility with networks like Apple Find My™ and Google Find My Device. Security features include encrypted memory, tamper detection, secure pairing, and a secure enclave for sensitive data. In enterprise settings, the system supports blockchain-based inventory logging, role-based access, and RFID / NFC inventory control. The device adapts to diverse form factors and deployment scenarios, ensuring reliable location tracking, anti-tamper protection, and secure asset management for consumer, industrial, and institutional applications.

The invention discloses an intelligent inventory control system based on a real-time data analysis and automation technology, and relates to the technical field of inventory control, and the system comprises an inventory tracking module which tracks the inventory in real time, updates the inventory data, and records the basic information of the inventory materials through the radio frequency identification technology and the bar code scanning technology; the inventory demand prediction module constructs and trains an inventory demand prediction model based on historical data of a certain type of people, uses the model to determine the material type of the current needed inventory, predicts the material inventory quantity based on customer demands, outputs a prediction result, dynamically adjusts the safety inventory level based on the prediction result, and formulates a replenishment plan. Abnormal detection and early warning are carried out; and the inventory decision optimization module is used for comprehensively analyzing historical data and real-time inventory data of a certain type of people, filtering and controlling the inventory data according to an analysis result, and optimizing inventory management. According to the invention, inventory management decisions can be optimized, and risks of inventory overstock and shortage can be reduced.

The invention provides a demand degree and inventory optimization-based medicine data dynamic management method and system, and relates to the technical field of medicine data management. The method comprises the following steps: firstly, acquiring consumption time series data, inventory time series data and environmental factor time series data of a target medicine set, and fusing the data to generate medicine dynamic collaboration data; secondly, calculating a corresponding real-time demand degree in a target medicine set based on the medicine dynamic collaboration data; according to the real-time demand degree, dynamically generating a dynamic safety inventory benchmark; the real-time demand degree is coupled with the real-time safety inventory benchmark of the corresponding target medicine, and a dynamic inventory control line is generated; and finally, updating and managing the inventory data of the target medicine set according to the dynamic inventory management and control line. According to the technical scheme provided by the invention, closed-loop intelligent inventory management from environment perception to automatic replenishment execution is realized.

The invention belongs to the technical field of intelligent logistics, and provides a construction method of an intelligent warehouse logistics data management platform. The method comprises the following steps: respectively constructing a distributed cloud layer, a software definition layer, an edge calculation layer and an Internet of Things layer for supply chain logistics; a block chain sharing network structure is constructed, so that a distributed cloud layer, a software definition layer, an edge computing layer and an Internet of Things layer realize network connection and data communication, when a user puts forward a service request, transaction records are executed based on a block chain, a path selection model preset in the cloud layer is adopted, and the service request is sent to the cloud layer. Selecting an optimal logistics distribution path from the candidate path set based on multi-standard decision analysis so as to carry out logistics distribution, and carrying out inventory demand prediction and periodic inventory control on each warehouse of a manufacturer or a supplier based on a preset inventory control model; according to the invention, the problem that a safe, credible and open supply chain logistics sharing management platform is lacked in the prior art can be solved.

The invention discloses a trade commodity dynamic inventory management and control system based on machine learning, and the system comprises the following modules: a structure state module which is used for obtaining the inventory structure state data of each commodity and generating a corresponding inventory structure state vector; the structure diagram module is used for constructing a structure connecting edge and generating a commodity dynamic diagram; the structure aggregation module is used for performing structure feature aggregation on the commodity adjacency relation to generate structure aggregation features; the demand prediction module is used for outputting a demand prediction result and demand plasticity parameters based on the improved iTransform; the inventory decision module is used for executing inventory decision calculation and generating an inventory adjustment track; and the execution feedback module is used for generating an inventory control instruction according to the inventory adjustment track, executing an inventory control operation and updating the inventory structure state data. According to the invention, through machine learning prediction of inventory structure perception, dynamic executable management of trade commodity demands and inventory regulation and control is realized.

The invention discloses an operation and maintenance method for an offshore wind plant, and the method comprises the steps: obtaining real-time operation data; determining degradation state parameters of a plurality of components of the wind power equipment based on the real-time operation data; respectively comparing the degradation state parameters of the plurality of components with a preset decision threshold, and determining real-time maintenance strategies respectively matched with the plurality of components; based on the determined real-time maintenance strategy, target spare parts matched with the real-time maintenance strategy are determined from a spare part library, the number of remaining spare parts in the spare part library is determined, and under the condition that the number of the remaining spare parts is smaller than a preset inventory threshold value, spare parts to be supplemented are determined; and according to the real-time maintenance strategy, the target spare parts perform maintenance operation on the multiple components of the wind power equipment, and replenishment processing is performed on the spare part library based on the spare parts to be replenished to obtain an operation and maintenance result. The problem that the offshore wind power plant is poor in long-term reliable operation and economical efficiency due to the lack of comprehensive consideration of maintenance strategies or inventory control in related technologies is solved.

This invention discloses a collaborative management method and system for the entire warehousing and logistics process, belonging to the field of warehousing and logistics information technology. Addressing the technical shortcomings of existing warehousing and logistics management, such as low inventory accuracy, poor scheduling efficiency, lagging information collaboration, and insufficient cost control, this invention integrates the entire process of inbound, storage, picking, outbound, transportation, and traceability, constructing a closed-loop management system of "data perception - algorithm decision-making - process collaboration - dynamic optimization." Through multi-dimensional data collection, optimized algorithm scheduling, cross-system data collaboration, and full-process traceability technology, this invention achieves precise inventory control, optimized logistics route planning, and efficient resource allocation, significantly improving warehousing and logistics operational efficiency, reducing overall costs, and enhancing management transparency. It is applicable to the digital management needs of warehousing and logistics in various industries, including manufacturing, retail, and e-commerce.

The application provides an intelligent inventory control management method and system based on a supply chain cooperation mechanism, applied to the technical field of supply chain management, preliminary demand prediction of a downstream partner is received, demand intention information containing customization component possibility weight and potential demand range is generated according to the prediction, after the upstream supplier receives the demand intention information, the influence of the demand intention information on future production resources is further evaluated, an evaluation result is obtained, finally, according to the evaluation result, the method performs flexible preparation in advance, including production window soft reservation, upstream material pre-communication and special mold preparation, effectively coping with the supply uncertainty of the customized components, avoiding the dilemma of standard component overstock and customized component shortage, realizing lean production and on-time delivery, and bringing significant economic benefits and competitive advantages to enterprises.

An inventory control system includes an object storage device, a display device, and one or more processors. The object storage device includes a plurality of compartments, where each compartment has a plurality of storage locations for storing objects. The display device is configured to display information about the object storage device. The one or more processors are configured to establish a database of descriptions for a plurality of objects configured for storage in the inventory control system. The one or more processors retrieve a plurality of object keywords corresponding to a plurality of objects stored at a plurality of storage locations within one of the plurality of compartments. The one or more processors also generate a text block based on the retrieved plurality of object keywords. On the display device, the one or more processors display a representation of the plurality of compartments of the object storage device with the text block applicable to the one of the plurality of compartments.

The application discloses a kind of inventory optimization methods of charging facility spare parts replacement cycle and failure rate analysis, and the core process of this method includes building data layer, multidimensional data is cleaned and optimized, to realize standardized storage;Based on the LSTM algorithm, a multidimensional linkage prediction model is built, the loss effect of design defects and environmental factors is quantified to optimize the model, and the accurate spare parts replacement cycle threshold and equipment failure rate are output;According to the flow properties of spare parts, a differentiated inventory management mode is designed, and the optimal management mode of slow-moving parts is selected;A full-cost quantification model is built to calculate the total cost and service level under each mode;Finally, with the goal of minimizing cost, an intelligent inventory control model is built, which dynamically outputs inventory warning thresholds, replenishment quantities and times;Through the algorithmization and parameter quantification of the whole process, the application realizes fine and intelligent management of inventory, significantly reduces operating costs and stockout risk, and improves the stability of charging facilities.

This invention discloses an automated inventory control method, system, and automated storage and retrieval system (AS / RS) for instant retail, relating to the field of warehouse automation control technology. The method includes: S1, acquiring the layout parameters of the AS / RS, constructing a topology map of the walking network based on the layout parameters, the topology map containing nodes and edges, nodes corresponding to work points, installing sensors on the stacker crane, and collecting motion state data of the stacker crane during task execution through the sensors; S2, associating and storing the motion state data with the path information of the stacker crane during task execution to form a motion state record; extracting the motion state data feature values ​​of each node interval from the historical motion state record, assigning weight adjustment values ​​to the corresponding edges based on the feature values, superimposing the weight adjustment values ​​onto the original weights to obtain updated weights, and recalculating the path based on the updated weights, so that the path planning result can reflect the actual traffic quality of the path segment.

The present invention relates to a dispensing system designed for dental applications, comprising an applicator with one or more reservoirs or cartridges containing dental material. The applicator integrates a dispensing mechanism and an outlet for controlled material delivery. It features a wireless communication device capable of receiving and transmitting information related to the reservoirs or cartridges to a remote device. The remote device, equipped with its own wireless communication and control unit, monitors the status and usage data of the reservoirs, and relays this information to a remote server. The system supports multiple communication protocols, such as RFID, NFC, Bluetooth, and Wi-Fi, facilitating seamless data exchange between the applicator, remote device, and server. Additionally, the system enables real-time monitoring of cartridge states— including fill level, identification, expiry date, and usage history— and stock management by updating inventory data upon delivery. This integrated network enhances traceability, inventory control, and operational efficiency in dental material dispensing.

The invention belongs to the technical field of cargo management, and particularly discloses an article warehouse-in and warehouse-out monitoring and inventory checking system and method, a terminal and a medium, when a person enters a goods taking channel, an entrance information acquisition module triggers a shooting unit to enter a tracking shooting mode, and position data in the length direction and the height direction are acquired in combination with a grating detection unit; when the person leaves, the position data and the video data are transmitted back to the background server for analysis, the article taking and placing position is marked, local shooting is carried out, historical data are compared, inventory increase and decrease information is generated, and the inventory is updated. The inventory checking control module carries out global shooting and comparison on all the goods shelves in a preset inventory checking time period, and inventory state batch updating is achieved. According to the invention, real-time monitoring and automatic inventory checking in the warehouse-in and warehouse-out process can be realized, and the accuracy and management efficiency of inventory data are improved.

A 3D printing system provides digital rights management protecting proprietary source code defining 3-D object data usable to print 3-D objects from uncompensated printing, and includes a central server, 3D printers, and corresponding single board computers (SBCs) each coupled to a respective printer. The central server stores the proprietary source code, permits displaying of an inventory of designs in an online store, and permits a user to securely purchase use of the source code to print one or more copies of a desired 3D object. The central server communicates across a network to incrementally stream the digital file containing the proprietary source code defining the desired 3D object to an SBC, and selectively controls each SBC / printer, to cause deletion of each incrementally streamed plurality of slices when the purchased use is completed. The SBC notifies the central server when the purchased use is completed.

The present disclosure proposes an inventory control method and device, which relates to the technical field of inventory control. The method includes: obtaining the historical purchase quantity sequence of the target product of the target object before the observation time sequence, processing the historical purchase quantity sequence to obtain the initial inventory of the target product for each unit observation time in the observation time sequence; determining the inventory impact factor of the target product at the current observation time, and determining the inventory of the target product at the current observation time according to the inventory impact factor of the target product at the current observation time and the initial inventory of the target product in the observation time sequence. Through the above method, the inventory of the target product of the target object can be accurately determined, and the efficiency of inventory control can be improved.

A pallet system having a plurality of like boxes which are sized and configured to a fit on a standardized air cargo pallet such as a U.S. Air Force 463L pallet. Each box has four sides and a hinged lid and is typically formed of a plastic material. The lid has a configuration that mates with the configuration of other like boxes such that boxes can be stacked on top of each other and be nested together without falling off. Each box also contains a first latch element which is mateable with a second latch element on an adjacent like box to fasten the boxes together in a horizontal direction on the pallet. A box may contain interior separators or compartments to suit size and content requirements. A box may be constructed to function for a particular purpose in addition to storage and shipping. Suitable labels and identifications can be applied to a box for each of identification in an inventory control system which may be implemented in an App for a mobile phone.

The present disclosure relates to systems and methods that are useful in control of one or more aspects of a power production plant. More particularly, the disclosure relates to power production plants and operation thereof utilizing a closed loop or semi-closed loop working fluid circuit. Inventory control through the working fluid circuit is provided through transfer of working fluid from a storage tank at one or positions between a plurality of compressors based upon at least one conditional input to a controller that is in a working arrangement with the working fluid circuit.