91 results about "Production logistics" patented technology

The invention discloses a smart warehouse material sorting two-stage scheduling method based on an embedded neighborhood search strategy genetic algorithm, relates to the field of smart logistics scheduling, and is used for solving the problem of warehouse material sorting scheduling in enterprise production logistics links. The method comprises the following steps: under the condition of considering the heterogeneity characteristics of a production line, establishing an order task batching and batching path optimization two-stage optimization model taking the minimum total cost of order picking order delay as a target function, calling a channel type storage picking path strategy, and providing four neighborhood search strategies, and a traditional genetic algorithm is improved by embedding a neighborhood search strategy to solve problems. According to the method, to-be-sorted order batching and batch grouping path planning automation is realized, so that the total order sorting delay cost is minimized, and the problem of'order batching-path planning 'two-stage scheduling of storage sorting in the production material supply process of an enterprise can be solved, so that the comprehensive benefits of production logistics are improved, and the purposes of reducing cost and improving efficiency are achieved.

According to the tray cycle scheduling system and the application method, historical data and a production plan are fused, an improved algorithm is adopted to predict tray requirements, and an attention mechanism is introduced to improve precision; the method comprises the following steps: acquiring multi-dimensional state information of a tray through a multi-modal sensor, eliminating noise by using a data fusion algorithm, and constructing a digital twin model to realize state synchronization; a double-layer optimization architecture is constructed, an upper layer solves a global scheme by combining an improved particle swarm and a simulated annealing algorithm, and a lower layer dynamically adjusts a path through reinforcement learning; an instruction is generated based on a digital twin model, an event triggering mechanism is adopted to reduce communication load, and virtual-real interaction closed-loop control is realized; a real-time evaluation index system is established, a meta-learning algorithm is utilized to quickly adapt to a new environment, and system parameters are continuously optimized. Multi-module collaborative innovation is achieved, the tray scheduling efficiency and the intelligent level are remarkably improved, production logistics whole-process collaborative optimization is achieved, and core support is provided for cost reduction and efficiency improvement of enterprises.

The invention discloses a whole-process collaborative production logistics management optimization system and method. The core of the system is intelligent inquiry and blockchain cost management. The inquiry module fuses a dynamic weight algorithm and a machine learning model, intelligently screens goods opportunities, pushes an AES encrypted inquiry sheet, and optimizes a quotation scheme in a multi-objective manner. And the delivery module is in butt joint with the ERP through the OData API, automatically analyzes the order, generates a delivery order, integrates weighing data for fee calculation, and carries out early warning on an abnormal order. And the customs declaration module identifies invoice information through OCR, automatically extracts customs declaration fields, verifies compliance through API, and generates a standardized customs declaration. The in-transit tracking module integrates a multi-platform API, pulls a logistics state in real time, pushes the logistics state to a client through WebSocket, and transparentizes an order state. The cost management module constructs a distributed account book based on a PBFT consensus mechanism block chain, ensures that cost information is safe and credible, and supports multi-currency settlement and dispute arbitration. The system comprehensively optimizes the production logistics link, realizes full-process collaboration, improves the efficiency, reduces the cost, and enhances the enterprise competitiveness.

The invention relates to the technical field of production logistics scheduling management, and discloses a digital twin workshop production logistics real-time scheduling management method and system, and the method comprises the steps: 1, building a unified state data and standard parameter baseline, calculating a consistency deviation value, and setting a two-stage deviation judgment threshold; 2, receiving a field event, and determining a scheduling time window; 3, determining task priorities, and generating a production to-be-executed list; 4, generating a carrying task set according to the production to-be-executed list, and determining carrying equipment and task allocation under constraint; step 5, performing channel conflict-free path planning, and generating a space-time occupation table; step 6, performing cross consistency check, and executing issuing or local recalculation according to a threshold; and step 7, executing field operation and updating unified state data, and executing consistency recovery when the deviation exceeds the limit. According to the invention, real-time collaborative scheduling and high-reliability operation of workshop production and logistics tasks are realized.

The invention relates to the technical field of cloud manufacturing, in particular to a real-time order receiving and scheduling method and system for a flexible job shop. Comprising the following steps: extracting related data from a production site, and constructing a flexible job shop environment model according to the related data; an agent decision model is constructed, a corresponding DQN algorithm model is constructed, and the DQN algorithm model comprises an order acceptance DQN and a scheduling DQN; on the basis of interaction with the intelligent agent, training an order acceptance DQN algorithm model and a scheduling DQN algorithm model, the training of the order acceptance DQN being completed on the basis of the scheduling DQN having a good effect; and deploying the trained order acceptance DQN and the scheduling DQN to make a decision. According to the method, comprehensive fine consideration of the external production capacity and the expected available production capacity of the actual production workshop is added, a high-customization order-oriented order acceptance decision and production logistics collaborative scheduling real-time comprehensive scheduling model is established, the deviation of real-time acceptance decision is reduced, and more efficient and scientific management and control of the production process are realized.

The invention discloses a twinning workshop production-logistics resource real-time collaborative scheduling method, which belongs to the technical field of workshop scheduling and comprises the following steps: S1, in a digital twinning environment, establishing a twinning workshop production-logistics resource real-time collaborative scheduling model; s2, when a task triggers a scheduling mechanism, obtaining production information of a physical workshop in real time, completing simulation and prediction in a virtual space, and optimizing a scheduling method according to a prediction result; s3, evaluating the service capability of the production-logistics resource group according to the optimized scheduling method, and selecting an optimal resource service group for the task; and S4, feeding back the task allocation scheme to the physical workshop, and waiting for the next task to trigger the scheduling mechanism. According to the twinning workshop production-logistics resource real-time collaborative scheduling method, production-logistics resources are distributed for tasks in real time, and production scheduling of workshops in a high-disturbance environment is achieved.

The invention relates to the technical field of computers, and discloses an agricultural and sideline food whole-process information tracing method and system, and the method comprises the steps: deploying sensing and collection equipment in all links of production, logistics, storage and sales, and generating a standardized event record with a time-space stamp and a digital signature; executing data cleaning, event modeling and map construction through a centralized platform to form a multi-dimensional tracing network with commodities as nodes and operation events as edges; and in response to user query, dynamically generating a visual tracing path according to time, geography, responsibility subject or environmental parameter dimensions. The system comprises a production end acquisition subsystem, a logistics end acquisition subsystem, a storage end acquisition subsystem, a sales end acquisition subsystem and a central data fusion platform, and a permission control and credibility scoring mechanism is arranged in the platform. According to the method, through event-driven atlas and multi-source data fusion, full-chain information reversible restoration, multi-condition filtering query and compliance automatic judgment are realized, and the authenticity, integrity and decision support capability of tracing are remarkably improved.

The invention provides a supply chain cost anomaly AI positioning system based on multi-mode depth tracing, and relates to the technical field of cost anomaly tracing. According to the supply chain cost anomaly AI positioning system based on multi-modal depth tracing, a three-layer architecture is adopted, a dynamic threshold algorithm and a multi-level association map are combined, real-time detection and root positioning of cost anomaly are achieved, and the three-layer structure is data acquisition, dynamic modeling and visual tracing. The system has the advantages that dynamic adaptability is improved, reasonable fluctuation and abnormal risks are accurately distinguished, the system breaks through the rigid limitation of a traditional static rule, the judgment threshold value is dynamically adjusted by fusing market dynamics (such as bulk commodity prices and policy adjustment) and real-time service data, and a supplier-production-logistics-storage association graph is constructed, so that the risk of abnormal risks is accurately distinguished. And the conduction path of the cost abnormity in each link of the supply chain is visually displayed.

The invention relates to the technical field of industrial information processing of production logistics scheduling, in particular to an intelligent material scheduling decision-making method and system based on a large language model, and the method comprises the steps: obtaining historical scheduling data, a production plan text, real-time material state information, production rhythm information and production main data; constructing a time statistical model and analyzing the plan text to obtain a scheduling constraint set; generating a candidate transfer time window after consistency verification, and determining a target time window; and generating a timestamp sequence, aligning and correcting according to rhythms, and outputting a scheduling instruction sequence. Constraint conflicts and non-executable instructions can be reduced, and delivery and beat stability is improved.

The invention provides a product tracing method based on a flow code, and the method comprises the steps: generating a unique sub-flow code on a production transmission belt in a production link, scanning the code, recording a production date and a flow line position, and storing the production date and the flow line position in a central database; thirdly, classifying according to the sub-assembly codes, generating a mother assembly code for external packaging, scanning the code to record the delivery time of the packaged product and the position of the storage warehouse, and updating the storage information of the database; and before the product is delivered, scanning the code again to record the delivery time and the delivery destination, and updating the logistics information. And during sales in the retail store, scanning the product flow code, recording sales time and place information and transmitting the information to the central database. And finally, a consumer or an enterprise inputs a flow code for query through a specific platform, and the platform retrieves production, logistics and sales information and displays a result. According to the method, accurate recording and efficient tracing of the whole process information of the product from production to sales are realized, the logistics efficiency is improved, the production management and control are optimized, and the product quality is guaranteed.

The invention provides an intelligent logistics system predictive scheduling optimization method and system, and the method specifically comprises the steps: collecting the operation state data of equipment in an intelligent logistics system in real time, carrying out the preprocessing of the operation state data, and dividing the operation state data into a training set and a test set; time domain analysis is carried out on the preprocessed operation state data, key fault features are extracted from the operation state data, and health state evaluation is carried out on the equipment; a predictive scheduling model is established, scheduling strategy switching is carried out based on the obtained health state evaluation result, and multi-objective optimization is carried out on a production logistics scheduling scheme; a three-dimensional modeling technology is adopted to carry out visual management, and virtual simulation is combined to carry out scheduling optimization verification. The method provided by the invention can effectively deal with the problems of equipment failure and the like in a dynamic logistics environment, optimize the logistics scheduling performance, reduce the distribution delay, improve the overall efficiency and resource utilization rate of a logistics system, and realize high-intelligence and high-efficiency production logistics scheduling.

The present application relates to a configuration method and storage medium for production logistics distribution resources, the method comprising: determining revised configuration information according to received distribution demand change information; when it is determined that the distribution carrier configuration mode in the revised configuration information is the target configuration mode, based on material target information and alternative cloud vehicle supply information, performing gene coding and population initialization to generate multiple initial structure codes; using a swarm intelligence global optimization algorithm, performing swarm optimization operations on the multiple initial structure codes to generate multiple first structure codes, and based on the distribution cost fitness of the distribution configuration scheme corresponding to the first structure code and the swarm intelligence global optimization algorithm, performing population update optimization on the multiple first structure codes to generate multiple candidate structure codes; among the multiple candidate structure codes, detecting the target structure code, and providing the distribution configuration scheme corresponding to the target structure as the configuration result of the production logistics distribution resources.

The utility model relates to the technical field of automatic logistics equipment, and provides a filter stick box group warehousing shaping device and filter stick production logistics equipment, the device comprises a connecting frame, a controller and at least two clamping mechanisms, each clamping mechanism comprises a driving assembly and a clamping part, the clamping part comprises two clamping pieces which are arranged on the connecting frame in a relative sliding mode, and the driving assembly is connected with the controller. The clamping pieces are provided with material detection sensors, and the driving assembly is arranged on the connecting frame and connected with the two clamping pieces. And the controller is used for sending a starting signal to the corresponding driving assembly when the material detection sensor detects the filter stick box group. The space between the two clamping pieces of the clamping component is detected through the material detection sensor, when the material detection sensor detects the filter stick box set, the driving assembly drives the two clamping pieces to be close to each other, the whole support filter stick box set is clamped and tidied, the filter stick box set which deflects is tidied again, and the filter stick box set is tidied in order. The situation that when the stacker takes goods, appearance detection alarm is triggered due to deviation of the filter stick box set is avoided, and therefore operation efficiency is improved.

The invention relates to the technical field of environmental information and industrial carbon emission, in particular to a cloud analysis and scheduling method for cement telegraph pole carbon footprint calculation, which comprises the following steps: constructing a cloud unified data access layer, and collecting raw material, energy and production logistics full-link data in real time; on the basis of life cycle evaluation, eight process stages are divided, and a high-precision carbon footprint accounting model is established; performing multi-dimensional sensitivity analysis on the key process parameters through Monte Carlo simulation to generate a carbon emission scene probability map; outputting a low-carbon scheduling instruction according to the optimal scene, and driving an advanced plan scheduling system to execute emission reduction and production scheduling; and a long-short-term memory neural network is introduced to realize model self-learning. According to the invention, real-time monitoring, accounting and active optimization of carbon emission in the whole life cycle of the cement telegraph pole are realized.

The application relates to the technical field of electromagnetic wire spool storage, and provides an electromagnetic wire spool grabbing mechanism, which realizes accurate grabbing and intelligent tray splicing of electromagnetic wire spools through the synergistic effect of three-axis servo driving, an adjustable pneumatic clamping jaw and an industrial vision system. The mechanism is deeply integrated with an MES / WMS system, significantly improves tray utilization and tray splicing efficiency, reduces manual intervention, and is suitable for transformer production logistics automation scenes.

The invention discloses a molten iron transport locomotive control method and system based on an application terminal, and belongs to the field of intelligent monitoring and management of locomotives of iron and steel enterprises, and the method comprises the steps: obtaining state data, shunting operation data and geographic information data of a transport locomotive; on the basis of the state data and shunting operation data of the transport locomotive, the train set length of the transport locomotive is obtained through double-algorithm calculation; based on the state data, shunting operation data and geographic information data of the transport locomotive and the train length of the transport locomotive, fault judgment and early warning are carried out by adopting a fault judgment algorithm; based on the result of fault judgment and early warning, a control instruction is issued to the transport locomotive through the application program end, and control over the transport locomotive is achieved. According to the method, the transport locomotive train length is calculated through the speed integral and the shunting operation plan algorithm, correction is carried out through error compensation, control over the molten iron transport locomotive through the application program end is achieved, the transport efficiency is improved, and the production logistics cost is remarkably reduced.

The invention provides an information integration system of a matrix workshop production logistics collaborative scheduling system. The information integration system comprises a UI interaction layer, a service gateway layer, a service collaboration layer and a data layer. The UI interaction layer, the service gateway layer, the service collaboration layer and the data layer realize efficient communication through a uniform interface; an ERP system, a WMS system, an MOM system, a logistics scheduling system and an AGV system information flow are integrated in the service collaboration layer; in the service collaboration layer, information flows of the ERP system, the WMS system, the MOM system, the logistics scheduling system and the AGV system adopt a vertical integrated architecture, a unified software interface specification and a message transmission mechanism. According to the invention, overall efficient collaboration and integrated management of the production logistics collaborative scheduling system are realized, the problem of information islands is effectively solved, clear division and collaboration among the layers ensure that the system has good maintainability, expandability and response capability, and the requirements of complex business scenes are met.

The invention belongs to the technical field of building construction, and particularly relates to a large-diameter overhead pipeline replacement construction auxiliary device and a construction method of the large-diameter overhead pipeline replacement construction auxiliary device. A horizontal guide rail formed by cutting an old pipeline is adopted as a guide rail of a conveying table, so that the conveying table is driven by a winch to do axial reciprocating motion in a conveying through groove of the horizontal guide rail, and long-distance conveying of a hoisting pipe section on a roof is achieved; when a new pipeline is replaced and hoisted by adopting the device and the method, the hoisting equipment only needs to be arranged at one end of the horizontal guide rail and does not need to move along with the change of the final mounting position of the hoisting pipe section, so that the construction site area occupied by the hoisting operation of the hoisting equipment is reduced, and the influence of pipeline replacement construction on bottom surface production logistics is reduced. The method is particularly suitable for the situation that construction sites are insufficient. In addition, the horizontal guide rail is manufactured by axially cutting an old pipeline, so that the old pipeline is reused, and materials and construction cost are saved.

The invention discloses a two-stage assembly flow shop scheduling method oriented to mechanical arm performance degradation, and aims at minimizing the maximum completion time and the total energy consumption as optimization targets for the production-logistics collaborative scheduling problem in a two-stage assembly flow shop. First, the problem is converted into a novel mathematical model. In order to solve the problem, an accurate method and an approximation method are adopted at the same time. For an accurate method, a double-target model is converted into a single-target model through a constraint method, and then a GUROBI solver is called to complete solution; for an approximation method, a heuristic algorithm oriented to the problem is designed, and the algorithm can also generate a specified number of Pareto optimal solutions for a decision maker. According to the invention, a high-quality scheduling scheme can be obtained, and production-logistics collaborative scheduling is realized.

The invention discloses an integrated storage container capable of synchronously and rapidly sorting multiple material boxes, and belongs to the technical field of industrial automatic storage. The device comprises a top frame, the bottom of the top frame is fixedly connected with a plurality of stand columns, the stand columns are evenly arrayed in a rectangular shape, the surfaces of the stand columns are fixedly connected with material box layer plates, the surfaces of the stand columns are fixedly connected with transverse supports, and the bottoms of the stand columns are fixedly connected with the same bottom frame. A gear and rack lifting platform is fixedly connected between the top frame and the bottom frame, and a plurality of sets of high-speed gear and rack material box extracting mechanism assemblies are installed on the lifting platform. By controlling the independent operation of the multiple groups of high-speed gear rack material box forks, arranging the high-speed lifting platform of the multiple groups of material box forks and combining with a control software optimization algorithm, the aim of synchronously and quickly putting in and out of a warehouse at a time of multiple material boxes is really achieved, so that the efficiency bottleneck among production, logistics, storage and taking and warehousing can be broken through, and the production efficiency is improved. And effective cost reduction and benefit increase of enterprises are realized.

1. The name of the product of this design: Mouse production logistics line. 2. Purpose of this design product: used for assembly of mouse and storage and warehousing. 3. The design key point of this appearance design product lies in the shape of the product. 4. The picture or photo that best illustrates the design points: Stereoscopic diagram 1. 5. This product is a large production line. The bottom view is not easy to see when in use, so the bottom view is omitted.

This invention discloses a composite navigation explosion-proof logistics robot and its operating method, belonging to the field of logistics equipment technology. It can be used for the transfer of hazardous chemicals in flammable and explosive production environments, achieving high-precision and high-reliability autonomous operation through laser SLAM and barcode scanner sensors. It features a dedicated quick-change explosion-proof battery box with a sliding push-in and lateral locking mechanical interface. Battery replacement is simple: just pull out the quick-release pin, remove the pressure block, and pull out the battery box—the entire process takes only a few minutes. This eliminates the need for prolonged charging stops, allowing the robot to perform transfer tasks almost continuously and uninterruptedly, significantly improving the overall utilization rate of equipment in high-intensity, continuous production logistics scenarios.

The invention relates to the technical field of automation, in particular to electronic component shell assembling and glue filling equipment which comprises a feeding mechanism, a shell feeding mechanism, a coding mechanism, a pre-assembling mechanism, a transferring mechanism, a press-fitting mechanism, a wobble plate mechanism and a glue filling system, and the pre-assembling mechanism comprises a pre-assembling rotating module, a rotating base plate and two pre-assembling clamping modules. The rotating base plate is arranged on the preassembly rotating module, the two preassembly clamping modules are oppositely arranged on the two sides of the rotating base plate, the shell feeding mechanism is used for feeding shells towards the preassembly clamping modules, and the preassembly rotating module is used for driving the rotating base plate to drive the preassembly clamping modules to rotate. The feeding mechanism is used for feeding electronic elements and feeding the electronic elements into the shell on the preassembling clamping module. When the device is applied to reactor production, excellent technical effects are shown in the aspects of assembly precision, quality control, glue pouring effect, production logistics and the like.

The present application relates to a method for optimizing the configuration of distributed blockchain production logistics resources based on an improved teaching and learning algorithm, including: selecting a candidate BCPLR node set corresponding to each blockchain resource set from the production logistics resource BCPLR nodes corresponding to a plurality of preset blockchain resource sets; performing population individual coding and population initialization based on the plurality of candidate BCPLR node sets and the production logistics task volume to generate a plurality of first individual codes; using the improved teaching and learning algorithm TLBO, performing population search iterations on the plurality of first individual codes to generate a plurality of second individual codes, and based on the fitness of the resource configuration method corresponding to the second individual code and the improved TLBO, performing population update iterations on the plurality of second individual codes, and determining the target individual code from the generated plurality of candidate individual codes to obtain an optimized configuration result, wherein the improved TLBO is a TIBO that uses the teaching strategy of multi-teacher grouping and the cross-learning strategy combining randomness and directionality as the teaching strategy and learning strategy of TLBO respectively.

The invention discloses a production logistics global modeling and joint optimization method based on demand prediction, and the method employs a LightGBM model to carry out middle and short term periodic demand prediction, and considers the influence of time lag nonlinear factors on demands. A production-inventory strategy joint optimization model taking periodic replenishment as a core is constructed, and a (T, s, S) strategy framework is adopted to perform joint modeling on a safety inventory level s, a target inventory level S and a production quantity q in each period. The model adopts an improved self-adaptive differential evolution algorithm, minimizes total cost as a target function, comprehensively considers inventory holding cost, stockout cost, production cost and transportation cost, meanwhile, restrains the service level not to be lower than a preset standard, and realizes production-inventory coordinated optimization under the condition of prediction uncertainty. The whole-process production logistics model is constructed, the expandability is good, and the service level and the operation cost control level are remarkably improved.

The application discloses a kind of distributed production material distribution scheduling method, it is applicable to multiple warehouse, multiple factory, multiple material and multiple vehicle collaborative distribution scene.This method minimizes each factory maximum material supply delay as target, constructs scheduling calculation model;Adopt three-layer joint coding structure including material allocation layer, batch loading layer and path optimization layer, through linkage reconstruction mechanism guarantee that scheduling scheme meets demand, capacity and time consistency constraint.Solving by using knowledge feedback intelligent optimization algorithm, establish material allocation, batch loading and path structure knowledge base;Then realize global search by layered crossover, carry out knowledge-driven local search to elite individual for delay bottleneck, replenishment waiting and path inefficiency, use high-quality fragment in knowledge base to feedback repair and dynamic update to poor individual.The application can collaboratively optimize material allocation, vehicle loading and distribution path, improve material supply timeliness and distributed production logistics scheduling efficiency.

The application discloses a logistics data analysis method for supply chain management, and belongs to the technical field of logistics data analysis; according to the supply chain, a supply chain logistics network is acquired, and various logistics channels are acquired according to the supply chain logistics network, and then corresponding logistics data in the various logistics channels is collected; the logistics data in the various logistics channels is analyzed to acquire abnormal logistics data; correct logistics data is acquired according to the abnormal logistics data, and various logistics data values are acquired according to the correct logistics data, wherein the logistics data values include production logistics data values and sales logistics data values; the logistics data values are used to generate corresponding alarm signals, and the various logistics channels are decided and rectified according to the alarm signals; and the application improves the transportation accuracy of logistics data of supply chain management and improves the satisfaction degree of customers.

The application discloses a kind of continuous casting tundish residual steel height on-line detection and automatic control method, comprising the following steps: setting liquidus temperature measuring point in tundish;Casting operation starts, liquid steel enters tundish;Temperature measured by temperature measuring instrument continues to rise and is higher than 1450 DEG C, start into continuous casting state;Temperature measured by temperature measuring instrument is maintained at 1500-1550 DEG C, continuous casting state continues to carry out;Temperature measured by temperature measuring instrument drops and is lower than 1500 DEG C, start to detect temperature drop rate;Temperature drop rate measured by temperature measuring instrument reaches per minute cooling more than 12.5 DEG C, judge tundish residual steel as low liquid level state;Record current tundish tonnage data;Close tundish outlet, end casting operation.The application solves the security risk when manual operation, prevents abnormal accident from happening due to manual judgment, effectively controls production logistics stability and safety, solves production safety and the effect of controlling continuous casting production quality problem.

The utility model discloses a platform system capable of loading and unloading goods bidirectionally, and relates to the technical field of loading of logistics loading and unloading containers. The platform system capable of loading and unloading bidirectionally comprises a front-end platform group, a passage platform, rear-end sliding platforms, rear-end fixed platforms and feeding platforms, the front-end platform group is adjacently arranged at one end of the passage platform, the rear-end fixed platforms are adjacently arranged at the other end of the passage platform, and the rear-end sliding platforms and the feeding platforms are arranged at the side ends of the rear-end fixed platforms; the front-end platform set comprises a left support, a right support, a middle support, an overturning platform, a tipping oil cylinder, a hydraulic control system, an electric cylinder and a photoelectric sensor, at least one side end of the middle support is provided with the overturning platform in an overturning mode, and the overturning platform is jacked up through the tipping oil cylinder and then used for pouring a container of an automobile to be close to the rear-end sliding platform. According to the bidirectional loading platform, loading and unloading efficiency can be improved, bidirectional loading of containers is achieved, and the warehouse-out loading efficiency and the warehouse-in unloading efficiency of production logistics are greatly improved.