112 results about "Customer order" patented technology

The invention relates to the technical field of logistics information management, and discloses a cross-border logistics information management method and system based on a logistics management platform, and the method comprises the steps: carrying out the analysis of a received customer order in a domestic logistics system, and obtaining a labeling parameter set; querying equipment specification information of an overseas logistics system, and converting the labeling parameter set based on the equipment specification information to obtain an overseas execution instruction; the overseas execution instruction is transmitted to overseas warehouse labeling equipment of an overseas logistics system for automatic labeling operation, and labeling process data is obtained; state monitoring is conducted on the labeling process data, a labeling state report is obtained, the labeling state report is transmitted back to the domestic logistics system, and synchronous confirmation information is generated. According to the method, full-process automation and intelligentization of cross-border logistics labeling information coordination processing are realized.

The invention discloses a scheduling management method and system for an unmanned finished product warehouse area, and the method comprises the following steps: analyzing material attributes and order information when materials are warehoused, selecting a raw material area FIFO order scheduling strategy or a finished product area customer order clustering strategy according to the type of the warehouse area, candidate stack positions are generated in combination with a warehouse-area-row-column-layer-stack position five-level coding system, the optimal stack position is determined after stack safety verification, and a crown block operation instruction is generated; when the crown block works, acquiring starting and target coordinates, loading the digital twin model of the reservoir area to generate an initial path, and re-planning a high-risk path by adopting an improved path planning algorithm introducing a load coefficient and a congestion index through conflict risk assessment; and during multi-vehicle collaborative operation, task collaboration and path conflict avoidance are realized based on a distributed multi-agent architecture and a preset communication protocol.

The invention provides a wooden door customization order flexible splitting and plate utilization rate optimization method and system, and relates to the technical field of wooden product customization intelligent manufacturing, and the method comprises the steps: carrying out the standardization of customer order data, and generating an order vector and a door style assembly constraint; constructing point cloud data through three-dimensional scanning of the plate and reconstructing the point cloud data into a plate digital model; generating a mapping table based on constraint and order execution door style adaptation; the order data, the mapping table and the plate model are combined, the number of assemblies, splicing ports and the waste rate are optimized through flexible order splitting logic, and an order is decomposed into cuttable door assemblies and matched with specifications; and finally, a correction cutting scheme avoiding defects is generated, a production instruction containing the plate utilization rate is output, efficient resource utilization can be achieved, and material waste and production cost are reduced.

The invention discloses a multi-cavity vulcanization constraint-containing flexible same-machine parallel batch optimization scheduling method for a rubber tire production workshop, and the method specifically comprises the steps: obtaining basic data of the rubber tire production workshop, and building a multi-cavity vulcanization constraint-containing flexible job workshop scheduling model; analyzing the customer order set to generate order-task-batch data; constructing a scheduling data structure, decoding each candidate scheduling scheme under multiple constraint conditions, generating a corresponding feasible scheduling scheme, evaluating the feasible scheduling scheme, executing iterative optimization, generating a new candidate scheduling scheme, and evaluating the new candidate scheduling scheme; and when a preset termination condition is met, taking the scheduling scheme with the optimal value as the optimal scheduling scheme. The method has the beneficial effects that the maximum completion time of a rubber tire production workshop can be remarkably reduced under the multi-cavity vulcanization constraint, the equipment utilization rate and the order delivery rate on schedule are improved, and good robustness and adaptability are kept when the order structure, the batch demand and the equipment load change.

A system includes a plurality of stocked items arranged throughout a store for picking according to one or more electronic customer orders, a computing system configured to wirelessly transmit the electronic customer orders, and a mobile scanning device including a display. The mobile scanning device is configured to wirelessly receive an electronic customer order from the computing system. The electronic customer order includes a plurality of ordered items indicating which of the stocked items are to be picked. The mobile scanning device is configured to store an image-based map that indicates locations of the stocked items in the store and arrange at least one of the plurality of ordered items on the display based on the image-based map.

The invention relates to an intelligent distribution management optimization method for an agricultural product supply chain, and the method comprises the steps: collecting multi-source heterogeneous data of production, processing and transportation ends in real time through the Internet of Things, and uploading the data to a cloud end after dynamic grading desensitization and encryption to form a complete traceability record; automatically generating an initial transportation and profit scheme according to a customer order, and dynamically optimizing a route and assembly by using a loss model driven by real-time environment / road condition data; when the actual loss exceeds the threshold value, the transportation strategy is adjusted immediately, integration of data safety, path optimization and loss closed-loop control is achieved, the freshness of agricultural product supply is improved, meanwhile, the transportation cost is reduced, and the performance efficiency and the customer experience are improved.

The invention relates to the technical field of logistics management, and particularly discloses a modern medicine logistics management operation system. The method is used for solving the problems of high cost, low utilization rate and difficulty in achieving SLA caused by separation of a box and a path, imperceptible and non-quantifiable temperature control risk, slow border-crossing disposal, insufficient loading stability and difficulty in balancing cost and carbon emission in medicine cold chain distribution. Comprising a customer order management module, a vehicle-mounted monitoring module, a boxing path optimization module, an execution scheduling module, an accounting module and a tracing alarm module. According to the method, an encasement-path integrated optimization system is driven by an equivalent stability index generated by multi-source monitoring, path feasibility and loading feasibility are unified through early warning trigger constraint injection and local recalculation, dynamic rescheduling and linkage accounting, meanwhile, carbon emission, time window, stability and compliance event monetization are merged into a target function, and the load performance is improved. The cooperation of a temperature control early warning closed loop and an encasement path is realized, the cost and carbon emission are reduced, and the SLA achievement rate and the transportation efficiency are improved.

The invention relates to the technical field of production dynamic optimization, in particular to a coal mine production and sales decision-making method and system based on intelligent flexible production. Constructing a three-dimensional geologic model of the coal mine, and obtaining a production task generated based on a customer order; generating a production scheduling plan of the coal mine working face according to the three-dimensional geologic model and the production task; obtaining multi-source dynamic data in coal mine working face mining; constructing a coal mine anomaly recognition model to recognize the multi-source dynamic data and the three-dimensional geologic model to obtain a geologic anomaly type and a spatial position; quantifying the multi-dimensional influence of geological anomaly types and spatial positions on a production scheduling plan in combination with the operation state of coal mining equipment and mining historical data of a coal mine working face; and constructing a multi-objective optimization model, and planning the production quota, resource allocation and coal blending schemes of the coal mine working face by taking cost minimization and risk minimization as optimization objectives under the constraint of a production task to generate a dynamic balance production scheme.

The invention discloses a remote production control method based on an AI data center, and the method comprises the steps: importing a customer order from an ERP platform by the AI data center, determining a production task, and transmitting a production instruction to a laser cutting machine, a slitting machine and a welding machine according to the production task; the correction machine adjusts correction parameters within a correction range determined by a historical correction database according to the welded material detection data, the module value of the cutting adjustment vector, the module value of the splitting adjustment vector and the module value of the welding adjustment vector; and after each correction is completed, the AI data center updates the customer order and feeds back the customer order to the ERP platform and the remote client. According to the invention, through deep fusion of AI decision, equipment control and remote cooperation, efficient, accurate and adaptive intelligent manufacturing remote control is realized.

The invention discloses an unmanned aerial vehicle resource scheduling method and system based on unmanned aerial vehicle information and multi-modal data. The unmanned aerial vehicle resource scheduling method based on the unmanned aerial vehicle information and the multi-modal data comprises the steps of obtaining customer order information, a candidate pilot portrait and an unmanned aerial vehicle real-time state, then performing multi-modal analysis based on a large language model-visual language model, generating an order vector O, an unmanned aerial vehicle vector U and a pilot vector P, then performing reinforcement learning, and obtaining an unmanned aerial vehicle resource scheduling result; screening out an optimal combination of the pilot and the unmanned aerial vehicle, and generating a suggestion for completing the order; and the screened optimal pilot and unmanned aerial vehicle combination completes the customer order according to the order vector O and the suggestion for completing the order. The invention provides an unmanned aerial vehicle resource scheduling method and system based on unmanned aerial vehicle information and multi-modal data, which can realize efficient and accurate scheduling of unmanned aerial vehicle resources, improve order completion efficiency and quality, reduce scheduling cost, and better meet individual demands of customers.

The invention provides a medium-thickness plate assembly design method for stock plate blanks, and relates to the technical field of ferrous metallurgy and production scheduling. The method comprises the following steps that hierarchical classification of steel types, thicknesses, widths and lengths is carried out on contract orders through multi-level order grouping and an inventory plate blank management mechanism; a greedy strategy is adopted to construct an initial plate assembling scheme with the minimum plate blank use number; global excess material distribution is optimized through a pop-up chain network; and dynamically adjusting a plate assembling scheme in combination with a backtracking search technology so as to respond to the fluctuation of a production line, and generating the opposite punching loss of the non-delegation sub-plate. According to the method, on the premise that customer order requirements are met, the yield and the finished product rate of materials are remarkably improved, second-level dynamic response to production requirement changes is supported, the limitation of a traditional static model is broken through, the resource utilization efficiency and the production flexibility are remarkably improved, and efficient and reliable plate assembling decision support is provided for intelligent transformation of the steel industry.

An online concierge system trains a computer model to map receipt item labels to order item identifiers, enabling the online concierge system to identify discrepancies between receipt items and customer order items. The online concierge system identifies a training set of data comprising quantities of receipt item labels and corresponding orders having quantities of order item identifiers and trains the computer model to predict quantities of order item identifiers based on the set of training data. The online concierge system applies a one-hot encoding for a receipt item label to determine predicted order item identifiers and maps the receipt item label to order item identifiers based on the predictions.

An automated retail store system for providing automated storage of multiple items and scheduled handling of a customer order for said items at a single retail site, including: a store control system adapted to operate under the control of control signals generated based on order information for an order by a customer, said order information including information representing one or more items and a pickup time; a plurality of storage channels for storing different respective items; a retrieval system adapted to operate under the control of said store control system to: retrieve a plurality of said items in said order information from said channels, and place a plurality of said retrieved items into a delivery container; a conveyor system adapted to operate under the control of said store control system to: move said delivery container to either a storage rack or a locker compartment based on said pickup time, and move said delivery container from said storage rack to an available said locker compartment based on said pickup time; and a verification system adapted to operate under the control of said store control system to: verify an identity of said customer or a unique identifier for said order, and allow said customer to access said items in said locker compartment only when said identity or said identifier has been successfully verified.

The invention belongs to the technical field of automobile flexible manufacturing, and particularly discloses a method and system for analyzing and issuing technological parameters in real time in automobile flexible manufacturing, and the method comprises the following steps: a customer submits required configuration orders of appearance, interior decoration and functions through an Internet of Things customization platform; the Internet of Things customization platform converts the customer order information into a standardized data format and sends the data format to a manufacturing execution system MES; and the MES system presets process basic data required by each vehicle type and configuration rules of the corresponding vehicle type, analyzes production process information of the vehicle required by a client, issues the information to the production equipment through the IOT platform, and executes the steps of collecting the state and production data of the production equipment, judging whether the production equipment works normally or not and judging whether the product quality reaches the standard or not. By adopting the technical scheme, based on a two-way communication mechanism between the MES and the IOT platform, rapid customization, accurate issuing and real-time adjustment of the process data are realized, so that the efficient production requirement of flexible manufacturing of automobiles is met.

The invention provides an automobile foot mat multi-style mixed flow production scheduling method based on customer order data, and the method comprises the steps: carrying out the standardization and feature vector generation of order process parameters, combining with the real-time state collection of production equipment, building a static process similarity and dynamic equipment response cost evaluation model, and fusing multi-source data to analyze the dynamic switching cost. The method comprises the following steps: establishing a scheduling sequence, realizing scheduling sequence optimization by using an improved NSGA-II multi-target genetic algorithm, comprehensively considering switching cost, equipment utilization rate and production line rhythm, finally dynamically selecting an optimal scheduling scheme through a TOPSIS decision method and a workshop load rate, and continuously correcting and evaluating model parameters by using an online incremental learning algorithm, thereby realizing scheduling sequence optimization. According to the method, the production scheduling efficiency and the resource utilization rate are improved, the equipment switching loss is remarkably reduced, and flexible production self-adaptive optimization is realized.

The invention relates to the technical field of computers, in particular to an internet fresh agricultural product distribution management system which comprises an order management module, a logistics management module, an inventory management module and a data analysis module. The order management module is used for processing customer orders, including order receiving, processing, tracking and state updating, so as to ensure efficient processing of the orders; the logistics management module is used for monitoring the temperature and humidity of the fresh agricultural products in the transportation process and planning a distribution route so as to ensure that the fresh agricultural products are delivered to customers in the shortest time; the inventory management module is used for monitoring the inventory level of the fresh agricultural products so as to ensure that enough inventory meets the order requirements; and the data analysis module is used for optimizing a purchasing strategy through data analysis. According to the invention, optimization of the fresh agricultural product distribution process is facilitated.

The invention discloses a high-density storage system order batch optimization method and system under uncertain factors. The method comprises the steps of obtaining order data and performing preprocessing; inputting the preprocessed data into an order batch sorting model, and carrying out order task allocation according to an output result; and the order batching model is established by combining customer order returning tendency prediction, fusing a dynamic decision rule and a batching clustering algorithm with capacity limitation and taking minimization of all order sorting completion time as an objective function. According to the method, the order batch sorting model fusing the dynamic decision rule and the batch clustering algorithm with capacity limitation is provided, the orders can be batched in real time according to the real-time arrival state and number of the orders and the capacity of the workbench in the order arrival process, the defect of fixed time window batch is avoided, resource allocation can be flexibly adjusted, and the efficiency of batch sorting is improved. The equipment utilization rate is effectively improved; and in combination with customer order returning tendency prediction, the order batch sorting result is more accurate and efficient.

The invention provides a production order management method and system based on artificial intelligence, and relates to the technical field of production management. The method comprises the steps of obtaining predicted order information according to historical order information and industry trend information; according to the customer order information, the prediction order information and the product inventory information, generating supplementary library order information; according to the customer order information, the research and development order information and the replenishment order information, determining an order execution sequence and a production process sequence of the order; according to the order execution sequence, the production process sequence and the equipment capacity, a production equipment sequence and a production plan are determined; if the order insertion information is received, the order execution sequence, the production equipment sequence and the production plan are updated according to the information of the orders being executed, the order execution sequence and the order insertion information; if the production plan of the production equipment needs to be updated, the real-time capacity of the production equipment is determined, and the production equipment sequence and the production plan are updated. And the flexibility and response speed of production order management are improved.

An order fulfillment facility with a delivery system is disclosed having plurality of mobile robots with containers to bring customer orders and / or power supply device / s to UAV / s for final delivery. UAV leaves the discharged power supply devices that are received in empty container and transported to storage area for replenishment and diagnostic checks. Order fulfillment operations along with power supply device charging and monitoring is performed to achieve timely delivery of customer orders.

The invention relates to the technical field of lace fabric supply chain management. The invention relates to a lace fabric supply chain management method based on big data. The method comprises the following steps: S1, acquiring stock data and sales data of an enterprise, acquiring a lace type corresponding to lace fabric of the enterprise, and extracting a sales customer list from the sales data; according to the method, accurate prediction is realized through multi-dimensional data fusion, on one hand, accurate popularity information is extracted and fluctuation coefficients are calculated in combination with customer group portraits and network popularity trend data, and the influence degree of market popularity on customer orders is clarified, and on the other hand, reference time periods are screened in combination with historical order difference analysis; the maximum quantity difference value is used for limiting the prediction range, prediction data are prevented from deviating from actual demands, enterprises can grasp real demands of customers in advance, stock overstock caused by too high prediction is reduced, the problem of stockout caused by too low prediction is also avoided, and waste of supply chain resources is greatly reduced.

1. The name of the design product: user portrait display graphical user interface for electronic equipment. 2. The use of the design product: the design product is used for an electronic device. 3. The design points of the design product: the interface content of the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the graphical user interface is used for user portrait dimension display interface. 6. The human-computer interaction mode of the graphical user interface: the front view is the user portrait dimension display interface, which displays order index column chart, portrait score and rating, customer order total amount, order total tonnage, annual order trend and other information.

The embodiment of the invention provides an enterprise customer right presentation full-link tracking method and system based on order management, and belongs to the technical field of computers. The method comprises the following steps: acquiring original log data of an enterprise customer order; obtaining an order state evolution diagram set and an edge weight set according to the original log data; and inputting the order state evolution diagram set and the edge weight set into a preset diagram attention network to obtain an order context vector. And screening out a right trigger type from the order state evolution diagram according to a preset rule. And according to the order context vector and a preset multi-factor comprehensive scoring function, calculating a strategy score for issuing each preset right and interest category on each right and interest triggering type, and obtaining a right and interest issuing strategy set. And issuing a corresponding right category to the enterprise customer according to the right issuing strategy set when the right triggering type occurs. The problem of mismatching of rights and interests is solved, and the utilization rate of rights and interests and customer satisfaction are improved.

Storage and picking system (10) for picking individual items of a plurality of customer orders (34), wherein the orders (34) comprise at least one multi-line order (38) and a plurality of single-line orders (36), wherein each order line (40) of each of the orders (34) corresponds to an item type, each of which is stored in a source container (20), wherein the system (10) comprises: a storage facility (18) which is set up to store a large number of the source containers (20); a goods-to-person, WzP, station (12) with a number of buffer locations (14) for destination containers (16); a transport system (22) designed to transport the source containers (20) from the storage facility (18) to the WzP station (12), and vice versa; and a control device (24) which is set up to generate a source container sequence (44) which represents a sequence in which the source containers (20) are to be provided for the successive processing of the orders (34) at the WzP station (12) by means of the transport system (22); wherein the control device (24) is further configured to bundle the single-line orders (36) into a bundle order (48) which represents a further multi-line order (38) and which replaces the single-line orders (36) during the generation of the source container sequence (44).

The invention discloses a quotation management method and system based on a product cost guiding principle, and the method comprises the following steps: setting a plurality of product service options, presetting a corresponding income item and a corresponding cost item for each product service option, and building an income-cost architecture system; respectively calculating a non-supplier cost reference index and an operation cost reference index according to an apportionment rule; selecting a target cost item corresponding to the customer order business demand according to the target product service, and further generating a supplier quotation list; a target income item is selected according to the target product service, a target cost item in the supplier quotation is associated and matched with the target income item, and based on non-supplier and operation cost reference indexes, predicted self-operation transportation mileage and the like, various earnings are calculated, and a customer quotation is generated; and after the customer order business is completed, according to customer and supplier quotations and the like, respectively generating account receivable and account payable, submitting settlement auditing, and executing collection / payment after passing the auditing.

The invention discloses an outsourcing production and logistics combined scheduling method for an overseas manufacturing base. The method comprises the following steps: S1) acquiring data of a customer order, an outsourcing factory, an overseas manufacturing base workshop and a delivery ship; s2) establishing constraint conditions according to the factory, workshop and marine transportation data, wherein the constraint conditions comprise a processing workshop constraint, a parallel machine constraint and a task order time window constraint; s3) an outsourcing production and logistics combined scheduling model of the overseas manufacturing base is established according to the constraint conditions, and the target of the combined scheduling model is to minimize the maximum processing completion time and the total cost; and S4) designing a two-stage joint optimization strategy to combine with an improved decomposition multi-objective optimization algorithm of reinforcement learning to solve the production and logistics joint scheduling model in the distributed manufacturing environment, and obtaining an optimal scheme of production distribution scheduling. According to the constraint condition of the actual production workshop, the optimal joint scheduling scheme is solved, and the overall cost of the supply chain can be reduced.

Systems and methods are provided to provision a customer-specific identifier in cloud-based communications systems so that when a communication arrives at the network services provider, it is identified as being associated with the customer, even when the customer information would otherwise not be available. In examples, when a customer orders communication services from the network services provider (or associates the communication services with a third-party Internet telephony service), the network services provider provides the customer a unique identifier that is provisioned into that customer's instance of the third-party Internet telephony service. When the customer makes a call using the third-party Internet telephony service, the identifier is inserted into the communication (e.g., in a SIP header). The identifier is extracted when the communication is received at the network services provider and used to identify the customer so that appropriate services, service levels, etc. can be applied to the call.

The utility model relates to the technical field of paper meal boxes, and discloses a microwave paper meal box which comprises a first box body, the interior of the first box body is divided into three storage chambers by T-shaped partition plates, the left side of the first box body is fixedly connected with a second box body through a connecting plate, the first box body is fixedly connected with a first box cover, the second box body is fixedly connected with a second box cover, and the first box cover and the second box cover are fixedly connected through a connecting plate. The front end of the first box body and the front end of the second box body are both fixedly connected with inserting plates, the first box cover and the second box cover are both fixedly connected with clamping plates, and through holes are formed in the clamping plates. According to the utility model, diversified requirements of customers can be well met. When meals ordered by the customer contain cold dishes, the cold dishes can be placed in the second box body to be properly stored. When the hot dishes stored in the first box body need to be heated, the user can easily separate the first box body from the second box body, so that unnecessary heating of the cold dishes can be avoided, and the original taste and flavor of the cold dishes are kept. When the first box body and the second box body are connected together, the box is convenient to carry, and dishes are not prone to being mixed.

To improve convenience. [Solution] A sales data processing system in which a customer orders products and receives the ordered products at a store, comprising: a list display unit that displays the ordered products to a store employee in a list; an input unit that accepts input from the store employee for each of the ordered products displayed in the list as a picking operation; a declaration unit that declares the completion of the picking operation; and a generation unit that generates a message related to the picking operation when a declaration is made by the declaration unit, wherein the generation unit generates different messages depending on the input status from the input unit.

The invention relates to a moving service pricing method, system and device based on artificial intelligence and a medium. The method comprises the following steps: constructing a standardized article database containing article identifiers, basic unit prices and an attribute matrix, and defining dimension rules of floors, carrying distances and transportation distances; analyzing a customer order, extracting information of two places and an article identifier set, and calculating a corresponding coefficient; and inputting the basic unit price, the attribute matrix and the coefficient into a pricing model to generate comprehensive unit prices, and summing the comprehensive unit prices and performing global adjustment to obtain a final total price. According to the method, the standardization, transparency and accuracy of moving service pricing are improved by constructing the standardized article database and the quantitative dimension rule and combining the artificial intelligence pricing model, the problems of price randomness and consumption disputes caused by high subjectivity and non-transparent information in a traditional pricing mode are effectively solved, and the method is suitable for popularization and application. And meanwhile, the pricing efficiency and the user experience are improved.

The application discloses a kind of based on driving engine's semiconductor manufacturing business document automation management method and system, to solve the problem of low efficiency caused by order whole process manual dependence.The method obtains customer production demand by driving engine, and is automatically converted into customer order, service order and manufacturing order according to preset mapping rule and is issued to manufacturing execution system;Driving engine receives execution result and automatically updates service order and customer order state until closed loop.Driving engine uses exponential backoff retry strategy and task state machine to manage abnormal conditions, support topology dependence analysis of parallel / serial order.The application realizes order whole process automation promotion and real-time monitoring, reduces manual intervention, and improves production efficiency.