90 results about "Order document" patented technology

The invention relates to the technical field of electronic shopping, in particular to a garment matching customization management system and method.The method comprises the steps that firstly, the body size, personal characteristics, social attributes, historical behaviors and target dressing occasion data of a user are collected, and real-time interaction feedback is fused to generate a dynamic multi-dimensional user portrait vector; inputting the design parameters into a pre-trained personalized matching generation model to generate a personalized matching scheme containing the design parameters; a virtual fitting effect picture is rendered through three-dimensional modeling, and a user is supported to adjust in real time and confirm a final scheme; and finally, analyzing the scheme to generate a customization demand list, distinguishing finished product items from customization items, intelligently matching a target supplier based on a supplier capability matrix, and issuing a purchase order or a customization production task list. And the system realizes full-process automation. According to the invention, matching precision and user experience are improved, supply and demand cooperation efficiency is optimized, personalized and standardized demands are adapted, and accurate, personalized and comfortable experience is provided for online clothes purchasing of the user.

The invention discloses a clothing supply chain transparent purchasing and collaborative management method and system based on the Internet of Things and a block chain. The method comprises the following steps: monitoring and collecting state data of raw materials in real time through Internet of Things equipment; when the state data meets a preset purchase triggering condition, a purchase demand transaction is automatically generated and broadcasted on the alliance block chain network; a purchase smart contract deployed on the alliance block chain network responds to the purchase demand, screens candidate suppliers, and quantitatively scores the candidate suppliers based on multi-dimensional historical performance data obtained from a distributed account book to automatically determine a target supplier; the purchase smart contract automatically generates a purchase order transaction and performs consensus evidence storage on the alliance block chain network; and continuously tracking order state update on the alliance block chain network, and automatically executing a settlement process when a preset payment condition is satisfied. According to the invention, the problems of opaque information, lagging purchasing decision, low process efficiency and difficulty in multi-party collaboration of the traditional clothing supply chain are solved.

The invention belongs to the technical field of purchase management and data processing of power transmission and transformation equipment manufacturing, and particularly relates to a power transmission and transformation equipment manufacturing-oriented purchase order full-process management and control method, equipment and a medium, and the method responds to a login request, and distributes permissions according to matching of a supplier unique identifier and an order manufacturer name. And creating an order containing specific parameters of power transmission and transformation, and transmitting the order to the cloud after verification. The edge end collects acceptance data, carries out edge processing, and transmits key data to the cloud end. The cloud integrates data and calculates indexes, qualified data block chains are stored according to project partitions, and hash chain type association cannot be tampered. And according to material category standard verification, three-level abnormity marking and graded feedback are carried out. And providing query, statistical evaluation and check report generation. According to the invention, edge processing is combined with cloud computing, so that the data processing efficiency and real-time performance are improved. A dynamic quality checking and grading early warning mechanism effectively recognizes and quickly responds to abnormity, and the quality risk is reduced. And the supply chain collaboration level and the overall management efficiency are improved.

The invention discloses a plastic trade scene-oriented cargo purchase-sales-stock data management system, which belongs to the technical field of cargo purchase-sales-stock management and specifically comprises a database, a purchase management module, a sales management module, a stock management and distribution module and an order tracking module. According to the method, a purchase order-inventory real-time binding mechanism is introduced, original inventory data is updated through in-transit inventory data, a traditional inventory is divided into new inventory concepts of available inventory and in-transit inventory, after sales order data is obtained, an inventory locking engine mechanism is called, a binding relation between a sales order and a new inventory is generated, and the new inventory is obtained. According to the method, the locked inventory is determined through matching and locking of the sales order and the inventory, the inventory data is updated again to cancel after verification of the locked inventory, dynamic monitoring and synchronous association of the inventory data, the purchasing data and the sales data are achieved, the inventory management efficiency and the order performance accuracy are effectively improved, and goods are effectively prevented from being oversold and mistakenly sold.

Systems and methods for handling supply chain certificates are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a processor and a memory coupled to the processor. The memory may store program instructions that, upon execution, cause the IHS to receive a message from a supplier identifying a device. The IHS may verify the device against a Purchase Order (PO) database of an Original Equipment Manufacturer (OEM) and may send encrypted material to the supplier. The supplier may generate a Certificate Signing Request (CSR) for the device comprising the encrypted material. The supplier may receive a digital certificate in response to the CSR and stores the certificate in the device. The system may ensure the authenticity and quality of components throughout the supply chain using cryptographic techniques.

The invention relates to a personalized commodity recommendation method, a personalized commodity recommendation device, personalized commodity recommendation equipment and a personalized commodity recommendation medium in the technical field of e-commerce. Determining user preference score distribution and re-purchase trend score distribution of a plurality of target categories accessed by the user in the independent stations; based on historical purchase orders and historical conversion paths of all users in the independent station, correspondingly determining co-purchase relation score distribution and conversion relation score distribution of the multiple target categories; the user preference score distribution, the re-purchase trend score distribution, the co-purchase relationship score distribution and the conversion relationship score distribution are weighted and fused into category interest score distribution; and determining recommended commodities pushed to the user based on the category interest score distribution. According to the invention, accurate personalized commodity recommendation is realized, and the user satisfaction is improved.

The application discloses a kind of intelligent material demand calculation method and electronic equipment, belong to intelligent manufacturing and supply chain management technical field, comprising: obtaining initial data, using multiple rule cleaning engine to the initial data is handled, obtains input data;Based on order delivery date, the processing cycle of each process of target product and corresponding yield, equipment capacity load factor determine the latest start date of each process;Based on the demand quantity of target product, the unit consumption of material and the cumulative yield from the first process to the current process, calculate the actual BOM demand of each process to material;Based on the actual BOM demand of each process to material is adjusted, obtains the purchase demand of each process to material;Determine total available inventory, the total available inventory is distributed to actual purchase demand;Determine the date of purchase order suggestion and carry out multi-objective optimization.The method significantly improves the planning accuracy, inventory efficiency and computing performance.

A computer-implemented method includes receiving, by a computer system, data indicating a user has acquired a cryptographic digital asset representing an article of footwear or apparel; responsive to receiving the data, granting the user authorization to produce up to a predetermined number of physical units of the article of footwear or apparel represented by the cryptographic digital asset; receiving, by the computer system via an electronic order portal, a purchase order from the user to produce a specified quantity, up to the predetermined number, of the physical units according to the authorization; and fulfilling, by the computer system, the purchase order to provide the specified quantity of physical units to the user.

The invention relates to a data analysis method based on a supply chain, in particular to the technical field of business management, and the method comprises the following steps: S1, collecting supply chain data from an internal system and an external source, the internal data comprising a production plan, a production schedule, an inventory level, a purchase order and a sales record, the external data comprises logistics transportation information, market demand indexes, consumer behavior characteristics, meteorological monitoring data, road traffic flow and policy and regulation change information; according to the invention, by establishing a multi-source data access channel, data of an ERP system, an MES system, a WMS system, an external data platform and an Internet of Things device are uniformly collected, and historical data and real-time data are combined to construct a multi-dimensional time sequence database, so that complete acquisition and structured storage of supply chain global information are realized; and the comprehensiveness and accuracy of data input are ensured.

The present disclosure relates to a computer-implemented method for managing purchase orders for building and real estate industries, comprising: identifying sensitive data in the purchase order; the sensitive data is encrypted; receiving a uniform content identifier (CID) for identifying the encrypted sensitive data; constructing metadata based on the CID, wherein the metadata comprises the CID and other data in the purchase order; receiving a purchase order non-homogeneous token PONFT generated based on the metadata; and transmitting the PONFT to each party involved in the purchase order. Compared with a comprehensive digital solution which needs to consume huge cost investment, the method has the advantage of low cost. Meanwhile, sensitive data in the purchase order in the building and real estate industries can be protected, the security of purchase order management is enhanced, and tampering of relevant information of the purchase order is prevented.

The invention provides an intelligent wisdom plan management method and system, and belongs to the technical field of industrial automation, the method is applied to intelligent plan management equipment, and the intelligent plan management equipment comprises an intelligent storage box, production equipment and a controller; the intelligent storage box is used for storing and providing consumables for the production equipment; the production equipment further comprises a dosage monitor; the controller performs data interaction with the intelligent storage box and the production equipment; the method is executed by a controller. The method comprises the following steps: acquiring consumable consumption of production equipment in real time based on a consumption monitor; when the consumption of the consumables reaches a preset scrapping threshold value, the consumables are recorded as scrapped consumables; replacement is carried out through the intelligent storage box based on the number of the scrapped consumables; the inventory state information of the consumables is obtained in real time through the intelligent storage box; and based on the inventory state information, a purchase order is automatically calculated and generated according to a preset purchase cycle threshold value for automatic purchase. According to the method, the situations of unplanned production halt, storage waste and the like can be reduced.

The invention provides an energy material supply allocation optimization method and system based on machine learning, and relates to the technical field of material management.The method comprises the steps that purchase order data, supplier performance data, inventory state data and demand order data are obtained, the purchase order data and the supplier performance data are integrated, and the purchase order data and the supplier performance data are integrated; forming a comprehensive state set; processing the comprehensive state set to generate multi-dimensional feature information, and inputting the multi-dimensional feature information into a multi-channel convolutional neural network for cross-modal feature fusion to obtain a rating vector; and combining the rating vector with inventory state data and demand order data to construct a supply and demand associated feature set, inputting the supply and demand associated feature set into a graph neural network, updating node feature representation through multiple rounds of inter-node message transmission, and finally generating an allocation path planning and material distribution strategy based on the updated node feature representation. According to the invention, the accuracy and overall efficiency of energy material scheduling are improved.

The invention relates to the technical field of financial block chains, and the method comprises the steps: carrying out the format recognition of a heterogeneous bill file according to the heterogeneous bill file submitted by a first participant, and generating a to-be-verified standardized bill data set; uploading a key verification field in the standardized bill data set to a main chain node of a block chain network, generating a corresponding first data hash value through a consensus mechanism, and storing the first data hash value; uploading the service data packet to a side chain storage node associated with the main chain node, and generating a corresponding second data hash value; and based on a purchase order database provided by the second participant, matching the standardized bill data set with the purchase order database in real time. According to the invention, an automatic and credible intelligent reconciliation system is constructed by fusing optical character recognition and block chain evidence storage technologies, and a business closed loop is formed. According to the overall scheme, full-link intelligence and credibility from data acquisition, processing and verification to dispute solution are realized, and the financial cooperation cost and risk of the supply chain are greatly reduced.

1. The name of the design product: the viewing purchase list graphical user interface of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the interface content and interface layout of the graphical user interface. 4. The picture or photo that best indicates the design points: interface change state diagram. 5. The use of the graphical user interface: the interface is the purchase list display interface of the inventory dynamic monitoring and early warning system software, the main view is the entrance interface of the purchase list, and the interface change state diagram is entered by clicking "purchase list" in the main view. This interface shows the information of the purchase order in different dimensions, and corresponding operations can be performed according to different needs.

Embodiments of the present disclosure provide a product warehousing method, medium, device and computing device. The product warehousing method comprises: determining first inventory quantities of a target product in each target sales channel according to total inventory quantities of the target product in all warehouses and purchase order data; for each target sales channel, determining second inventory quantities of the target product in each warehouse in the target sales channel according to the first inventory quantity corresponding to the target sales channel and a warehousing ratio of each warehouse in the target sales channel; for each warehouse, determining an initial warehousing quantity of the target product in the warehouse according to a total reserve quantity, the second inventory quantity of each target sales channel in the warehouse and an existing inventory quantity of the warehouse; and determining a target warehousing quantity of the target product in each target sales channel in each warehouse according to the initial warehousing quantity corresponding to each warehouse and a reserve ratio of each target sales channel. The present disclosure can improve the accuracy of warehousing processing.

The invention captures multimodal biometric, clinical, and IoT-logistics data inside a privacy-preserving enclave, builds a hybrid digital twin that unites mechanistic metabolism with machine-learning and taste-genomics embeddings, and—every time physiology, medication, or stock conditions change—computes a drug-safe, nutrient-balanced, culturally palatable meal. It then auto-mints a non-fungible smart-contract purchase order, selects the lowest-carbon, highest-reliability vendor via a self-retraining Deep-Q network, tracks temperature, humidity, and shock in minute-level cold-chain telemetry, and reroutes or reorders within ten seconds of any excursion, all events anchoring to a blockchain ledger that passes quarterly zero-knowledge audits. Post-delivery metrics feed back to the graph, triggering on-the-fly model retraining and instant reformulation on new HL7-FHIR medication events, so clinical efficacy and ingredient integrity are maintained end-to-end without human intervention.

This invention discloses a pre-set and then linked method for collaborative pricing and production of printed materials, belonging to the field of information management technology in the printing industry. It includes acquiring historical production order data from target customers, extracting specifications, process routes, and material information for each order, constructing a dedicated product template library for that customer, responding to receiving current production requirement parameters, synchronously and in parallel executing and responding to the review and confirmation instruction for the optimal production plan, and automatically generating a production work order associated with that production plan. This invention, through an atomic decomposition mechanism, automatically generates a production work order after reviewing and confirming the optimal production plan, and then decomposes it in parallel into three types of atomic documents: material purchase orders, production task orders, and process outsourcing orders. These three documents are associated through the same work order identifier, achieving end-to-end data connectivity from quotation to production, eliminating information silos, making quotation-to-production possible, and significantly shortening the order response cycle.

To strengthen control over revenue recognition for contracts and purchase orders with minimal workload. [Solution] The order form / contract checking device includes: a contract information input means that registers contract information including project number, contract number, contract period, order date, planned sales date, line, product, and contract amount in response to operator operations on the contract input screen; an order form registration means that registers order form information including contract number, storage location, order form presence / absence classification specifying whether or not an order form is attached, line, receipt date, actual construction period, and order form amount in response to operator operations on the order form registration screen; and a sales input means that, in response to operator operations on the sales input screen, when recording sales for the target project number and contract number, refers to the registered contract information and the order form information to check whether the contract amount and the order form amount match and whether the contract period is within the actual construction period, and enables sales recording if the conditions are met.

This invention discloses a refined cost accounting method for cross-border multi-entity e-commerce, including: receiving original documents and parsing key information fields; determining whether the original documents belong to inter-company transactions; determining whether the original documents match the transaction link segment rules; generating derivative documents when they match; performing inbound cost calculation for internal purchase orders and inbound purchase orders: breaking down the inbound cost into multiple cost items, calculating the amount of each cost item in parallel under the transaction currency, local currency, and purchase currency, and determining the inbound cost for this transaction; performing outbound cost calculation for internal sales orders and sales outbound orders: locking the outbound cost based on the weighted average unit price of the inventory, and synchronously transferring the amount in different currencies for each cost item; updating the cost balance of the inventory in real time; and generating a transaction log for the detailed status before and after each inventory change. This invention decomposes cost accounting into the processing of each document, achieving real-time and accurate cost calculation.

The invention provides a material management method and system based on an intelligent balance benefit library. The method comprises the steps of obtaining a material demand list of a target engineering project; executing cross-project balance benefit library calculation, expanding a benefit library range to an associated spare part project inventory, and generating a structured benefit library result; if allocation from spare parts is needed, a project material conversion list is automatically generated, other warehouse-out lists and warehouse-in lists are generated in a linkage mode, and financial vouchers are driven to be automatically generated; if yes, generating a purchase request list; when a purchase order is created, performing rigid control according to a pre-configured inventory amount upper limit rule; and meanwhile, direct material picking and warehouse-out aiming at spare part projects are intercepted. According to the invention, automatic cooperation and business and financial linkage of multi-project inventory resources are realized through technical means, the technical problems of data islands, business and financial disjoint and out-of-control inventory cost are solved, and the effects of improving the inventory utilization rate, enhancing the risk control capability and ensuring the data accuracy are achieved.

The application provides a production scheduling and dispatching method, which comprises the following steps: obtaining purchase order information, the purchase order information comprising at least two purchase order numbers and product types, product quantities and delivery dates corresponding to the purchase order numbers; obtaining sales order information based on the purchase order information, and splitting and issuing the sales order information, the sales order information comprising a plurality of sales orders, each sales order comprising a sales order number, a product quantity and a delivery date corresponding to each product type; obtaining inventory quantities corresponding to product types corresponding to each sales order, and determining whether the inventory quantities corresponding to the sales orders are less than the product quantities; collecting the sales orders with the inventory quantities less than the product quantities, and obtaining production cycle information corresponding to the product types corresponding to the sales orders; determining priorities of the sales orders based on the inventory quantities, the sales orders and the production cycle information; and scheduling and dispatching based on the priorities of the sales orders.

This invention discloses a BIM-based engineering data management method and system, relating to the technical field of engineering management. The label and voucher module and the data information collection module enable real-time recording and monitoring of building materials entering and leaving the warehouse, their placement status, and damage conditions. This helps managers understand the quantity and status of building materials in a timely manner, and reduces damage by monitoring the placement and damage status of materials. The verification module checks the remaining quantity Sv and the damage quantity Pz of building materials to generate the usage quantity Ss, and analyzes the usage quantity Ss to determine whether a purchase order needs to be issued, avoiding overstocking or shortages and improving inventory management efficiency. The engineering warehouse analysis module uses feature extraction and machine learning calculations to obtain the stacking stability factor Djyz, the disorder coefficient Hx, and the damage status coefficient Pzxs, and calculates the rectification evaluation index Zgzs, which can optimize the stacking and path planning of building materials.

The invention discloses a cross-border e-commerce service system based on artificial intelligence, and the system comprises a supplier management module which comprises a contract management unit, a supplier information management unit and a commodity information management unit, and achieves the comprehensive management of the contract of a supplier, basic information and provided commodity information; the purchase management module predicts commodity demands according to sales data and inventory conditions by using an artificial intelligence algorithm, automatically generates a purchase order, and tracks the execution process of the purchase order; the system has the beneficial effects that integrated supplier purchase, sales and stock management functions including contract management, supplier management, commodity management and the like are provided, so that the supplier management efficiency and accuracy are improved, and a long-term stable cooperation relationship between merchants and suppliers is favorably established; the operations of order and list declaration, logistics waybill pushing, order pushing and the like are efficiently carried out, and the requirements of different business modes are met.

The disclosed end-to-end product customization systems and methods receive custom orders from customers or consumers, evaluate them, and generate production-ready custom orders that are able to be used by decorator to create the custom products. The system receives a customization option and an order file type in the custom order. The system or a third party evaluates that customization option to identify a change order that is required and also determines a conversion recommendation to convert the order file type or a production-ready file type. The production-ready custom order is generated based on the change order and the conversion recommendation.

Embodiments of a supply chain management system (SCMS) are disclosed that enable the generation of synthetic supply chain activity data for developing machine learning models, such as models for predicting vendor lead times (VLTs) of purchase orders fulfilled by a supply chain network. In embodiments, the generation process is performed over successive time periods to simulate dynamically changing variables of the supply chain network, including inventory levels, product demand, and stock manager decisions. The generation process may also be used to generate synthetic data to simulate elements within the supply chain network, such as simulated warehouses, vendors, or products. The disclosed SCMS is able to generate highly realistic training data that simulates the operations within the supply chain network, which can be used to improve the performance of machine learning models.

The present application relates to the technical field of data analysis, and particularly relates to a data-based unpacking and packing operation method and system, which comprises an order decomposition unit, based on the commodity composition in a purchase order and in combination with the contents of different warehouses, the purchase order is decomposed into multiple sub-pickup orders, and a pickup database corresponding to each warehouse is constructed; a warehouse analysis unit, each warehouse is independently analyzed, and pickup arrays in the pickup database located in a to-be-determined time interval range are divided into a to-be-determined array set; a to-be-determined array set is extracted, a packing combination constructed by multiple pickup arrays is simulated for three-dimensional placement and transportation route simulation, a space recommendation value and a route recommendation value of each packing combination are analyzed, and a pickup packing combination is screened out; a model simulation unit, a three-dimensional model is constructed and sequentially placed and simulated, and the placement simulation is used to eliminate part of the packing combinations that cannot be placed; and a packing pickup unit, the pickup packing combination is cycled for pickup and sorting.

The invention discloses a material management method, a computing device and a computer readable storage medium, and the method comprises the steps: determining a first material demand according to a target production plan, and carrying out the neat analysis of the first material demand on a production level according to an existing inventory; determining a second material demand according to an analysis result of the neat set analysis, the second material demand being a material demand corresponding to the first material demand which cannot be satisfied by the existing inventory; acquiring at least one purchase order in a purchase state, and matching the second material demand based on material information in the purchase order; and managing the first material demand according to an analysis result of the registration analysis and a matching result of the purchase order. Therefore, the material requirement of the current production plan is met in time on the basis of the existing inventory and the purchase order through the method of neat set analysis and purchase order matching, the risk of production interruption is reduced, the inventory is optimized, and the inventory cost is reduced.

The invention discloses a single engineering accounting method and system, and relates to the technical field of engineering management, and the method comprises the steps: creating a single engineering project of a WBS architecture, obtaining a project budget, and building an incidence relation between the project budget and a WBS node. Acquiring a purchase demand, and generating a purchase application hooked to the WBS node based on the purchase demand; creating a purchase order based on the purchase application, executing a receiving or service confirmation operation on the purchase order according to the actual progress of the project to generate a material information ledger, collecting the cost to a WBS node based on the material information ledger, and executing an invoice verification and payment process associated with the purchase order; and after the project is completed, inputting completion information, and displaying the completion information according to the preset management hierarchy by using the visual billboard. According to the invention, through the creation of the WBS architecture, the work content and budget distribution of each stage of the project can be clearly divided, fine management is realized, and the management efficiency is improved.

The invention discloses a sorting method and system for realizing cross-platform order priority generation, and the method comprises the steps: obtaining order data flows of a plurality of order platforms, determining order purchase types based on the order data flows, and extracting order text information; determining a basic priority based on a corresponding relationship between a preset order purchase type and the basic priority; inputting the order text information into a pre-trained order emergency degree classification model, and judging an emergency degree grade; and performing quantification processing on the basic priority and the emergency level to obtain a basic priority score and an emergency level score, performing weighted calculation to obtain an order priority score, and sorting the orders according to the order priority score. According to the method, the order priority is dynamically adjusted by combining the order purchase type and the emergency degree level, so that the equipment maintenance leasing order and the industrial product purchase order which have great influence on power business can be preferentially processed, the waiting time of key business is shortened, and the overall efficiency is improved.

This specification discloses an emergency sourcing method, device, and medium for the biopharmaceutical supply chain, relating to the field of supply chain technology. The method includes: receiving a quality deviation emergency request containing a deviation batch identifier and deviation type; based on the quality deviation emergency request, determining the deviation batch and the corresponding set of affected batches in a pre-constructed dynamic supply chain knowledge graph; acquiring corresponding production-related data and logistics-related data; inputting the production-related data and logistics-related data into a pre-trained causal risk assessment model; determining the risk transmission path information from the deviation batch to the affected batches in the set of affected batches; calculating the risk index for each affected batch to determine the batch disposal decision tree for the corresponding disposal instruction; and based on the batch disposal decision tree and a pre-stored supplier profile database, determining the corresponding supplier selection scheme and material allocation scheme to generate an emergency purchase order, thereby achieving emergency sourcing.