38 results about "Production logistics" patented technology

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 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 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 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.

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 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 invention provides a formation and capacity grading intelligent production logistics system for new energy lithium battery production, belongs to the field of lithium battery production, and solves the problems that an existing formation and capacity grading system is low in efficiency, poor in quality and the like. Comprising a feeding mechanism, a flattening mechanism, a formation mechanism, an OCV detection mechanism and a discharging mechanism, the upper flattening mechanism comprises a flattening machine box, an upper machine cover is provided with a main control computer, the left side of the upper portion of the flattening machine box is provided with a material conveyor, a feeding conveyor and a flattening carrying assembly, and the middle of the upper portion of the flattening machine box is provided with a flattening pressing assembly, a transverse pushing assembly and two induction gratings; a material conveyor and a first waste conveyor are arranged on the right side of the upper portion of the flattening machine box, the formation mechanism comprises a formation machine box, a formation conveyor and a formation material carrying assembly, two formation material storage assemblies and two formation pressing assemblies are arranged above the formation conveyor, and a turnover material transferring mechanism is arranged on the left portion of the upper side of the formation conveyor. The whole process is automatically circulated, the production efficiency and consistency are improved, and the battery quality and reliability are guaranteed.

The invention discloses a multi-warehouse collaborative dynamic optimization method adaptive to multi-variety variable-batch mixed line production, and relates to the technical field of logistics distribution optimization, and the method comprises the steps: carrying out the modeling of a multi-warehouse scene analysis problem, and carrying out the analysis of a multi-warehouse scene; performing multi-bin material state correlation analysis, and based on the multi-bin scene model, constructing a correlation relationship among multiple bins; dynamically optimizing a multi-bin collaborative seasoning threshold value, constructing an environment comprising a workshop, an inner bin and an outer bin, and solving a multi-bin collaborative optimal seasoning threshold value; a production logistics collaboration mechanism: constructing a production logistics collaboration double-layer optimization model, and realizing deep collaboration of production and logistics; and production logistics collaborative scheduling optimization is carried out, a multi-objective optimization algorithm and a production logistics collaborative mechanism are combined, minimization of maximum completion time and production waiting time, maximization of task income and minimization of material waiting time are taken as objectives, and through bidirectional feedback of production and logistics states, distribution priority and production scheduling are optimized. And the production income is evaluated from production and material levels.

The invention relates to the technical field of discrete manufacturing workshops, in particular to a discrete manufacturing unmanned intelligent workshop AGV scheduling optimization method under a machine fault and a related device. The method comprises the following steps: constructing a workshop scheduling model for the discrete manufacturing unmanned intelligent workshop according to a preset multi-constraint condition and a preset objective function, and determining optimal operation parameters for the workshop scheduling model based on a grey wolf-tabu search algorithm, the optimal operation parameter is used for representing an optimal scheduling strategy for the AGV and an optimal operation index of the discrete manufacturing unmanned intelligent workshop. According to the invention, machine fault disturbance can be handled in real time, and rapid recovery of production logistics and minimization of productivity loss are realized through dynamic scheduling.

A heterogeneous AGV workshop production logistics synchronous scheduling method comprises the steps that workshop production data is acquired, and the workshop production data comprises workpiece batch and process information, parallel machine information of all stages, heterogeneous AGV information and the matching relation between the heterogeneous AGV information and workpieces; constructing a mixed integer linear programming model by taking minimization of the maximum completion time and minimization of the total energy consumption of the workshop as targets; carrying out cooperative control on processing and transferring links by adopting an SAPT rule; the SAPT rule is used for dynamically deciding to adopt a Gold moment transportation mode or a full-load transportation mode according to the real-time idle state of the AGV, the batch size of workpiece sub-batches and machining; and solving the mixed integer linear programming model by adopting an improved water wave optimization algorithm, and outputting an optimal production and logistics scheduling scheme. According to the scheduling method, synchronous scheduling of production and logistics can be realized, and the maximum completion time is effectively reduced; the total energy consumption of a workshop is reduced, and the production efficiency and the energy utilization efficiency are remarkably improved.

The invention relates to the technical field of manufacturing industry informatization, and provides a matrix workshop production logistics system informatization software and hardware integration system which comprises a business application layer, a software layer and a hardware layer. The business application layer is used for implementing a specific management function in the flexible matrix manufacturing workshop and supporting information circulation in a production process; the business application layer comprises an APS system, an ERP system, an MES system, a PLM system, a logistics scheduling system and an AGV system; the software layer is connected with the business application layer and the hardware layer and is used for processing, communicating and coordinating business data; the software layer comprises subsystems corresponding to the systems of the business application layer; and the hardware layer integrates servers and devices corresponding to the systems of the business application layer and the subsystems of the software layer. According to the invention, a vertical system integration architecture of business layer-software layer-hardware layer is constructed based on a full-life-cycle production logistics business process, and closed-loop control of the full-business process of the flexible matrix manufacturing workshop is realized.

This invention provides a method for calculating the demand for containers for ship hull parts. It decomposes the entire production logistics process into eight key stages: work-in-process inventory in production, transshipment volume in the logistics transfer loop, storage volume in the storage area, secondary transfer and downstream usage in the usage stage, and recycling volume in the recycling stage. By calculating the container demand segment by segment, the total number of containers required by the system is finally obtained. Traditional methods rely on estimations based on management experience; this invention, through formulaic calculations, transforms demand forecasting into data-driven forecasting, reducing subjective bias. Furthermore, this invention's calculation method covers multiple departments, including production, warehousing, logistics, and recycling, promoting collaborative work among departments based on the same data standard. Based on the calculated values, targeted improvements can be implemented for high-percentage stages, such as reducing storage time and improving transfer efficiency, achieving cost reduction and efficiency improvement.

The application discloses an intelligent suspension conveying system of mechanical structure steel, and relates to the technical field of conveying equipment.The system comprises a field device layer, a process control layer and a transportation management layer.The field device layer is composed of a track module, a suspension carrier, a driving device, a flow switching mechanism and a buffer section, and provides a physical operation basis.The process control layer realizes real-time monitoring and safety control through a sensor network, a PLC controller, a section speed control module and an actuator.The transportation management layer comprises four core modules, namely, task allocation, path selection, load scheduling and conflict detection, and uses an improved wolf swarm optimization algorithm for task scheduling, combines time-space conflict detection with a conflict resolution algorithm based on a back-to-back search, and forms a complete closed-loop control system.The application can intelligently schedule and orderly transport multiple mechanical structure steel workpieces in a complex track network, significantly improves the automation and intelligent level of production logistics, and ensures a safe and efficient transportation process.

The invention discloses a fabricated building engineering management system and method. The system comprises a component production monitoring module, a logistics scheduling module, a construction site management module, a quality tracing module, a progress collaboration module, a cost accounting module, a safety early warning module and a system operation and maintenance module. According to the invention, a management system covering the whole process of component production, logistics scheduling, construction site management and the like is constructed, and real-time acquisition and sharing of data of each link of the fabricated building engineering are realized by using an information technology. The progress coordination and consistency of production, logistics and construction are ensured through the progress coordination module, the whole life cycle management of component quality is realized through the quality tracing module, and the cost accounting module and the safety early warning module respectively provide powerful support for cost control and safety management.

The utility model relates to the technical field of logistics automation, in particular to a simple and convenient-to-produce logistics pick-up light bar which comprises a rear shell, first clamping rods which are symmetrically distributed are fixedly connected to the upper side in the rear shell, an LED light bar is arranged in the rear shell, first mounting holes matched with the first clamping rods are symmetrically formed in the LED light bar, and the first clamping rods are fixedly connected to the upper side in the rear shell. And the LED light bar is clamped and fixed with the first clamping rod through the first mounting hole. According to the logistics pick-up light bar, the front cover, the LED light bar, the chip and other assemblies are connected through the clamping type design, so that the overall structure and internal elements are easy, convenient and rapid to disassemble and replace, maintenance or replacement can be rapidly conducted once a fault occurs, and the maintenance cost and the downtime are reduced.

The invention provides a turnover vehicle positioning management method and system for elevator part production logistics. The method comprises the following steps that a vehicle identification code and a positioning device are arranged on a turnover vehicle; scanning equipment is used for scanning the vehicle identification code to collect identity information of the turnover vehicle, and the material information and the identity information of the turnover vehicle are associated and uploaded to a server; the positioning device sends the position information to the server at a fixed time interval; the production execution system is connected with the server and updates material information and position information in real time; and forming a logistics thermodynamic diagram and a circulation path through the material information and the position information. The method has the advantages that the positioning device sends position information in real time, the real-time position of the tote cart and the information of the borne materials can be accurately tracked, the problems that in a traditional method, updating of the material information is lagged, and tracking is difficult are solved, the information of the tote cart and the materials is automatically collected through the two-dimensional code scanning device, manual input errors are avoided, and the working efficiency is improved. And the accuracy and the consistency of the data are improved.

The present application relates to the technical field of industry chain monitoring and management, in particular to a monitoring method and system for industry chain breakpoint management; the method comprises: collecting production, logistics, finance, policy and environmental dynamic information through multi-source data acquisition, generating industry chain comprehensive features through standardization, dimension embedding representation and cross-dimension fusion, and introducing historical trend dependence to enhance forward-looking prediction; and constructing a dynamic coupling network, using dynamic edge weight to quantify the risk propagation strength between nodes, realizing cross-level breakpoint propagation analysis; and calculating risk indicators by fusing node features and network structure, combining adaptive threshold to filter breakpoint candidate nodes, using a nonlinear propagation function to predict multi-step evolution trend and map it to multi-level warning level. According to the risk level, a management strategy is generated, and the effect is evaluated in real time and the parameters are dynamically adjusted through a closed-loop optimization mechanism. The present application realizes closed-loop management of risk identification, prediction and adaptive management.

The invention discloses an insole product full-life-cycle intelligent management method and system based on a block chain. The method comprises the steps that initial production data such as insole raw material batches, production process stages and quality inspection parameters are collected and packaged into product birth records, meta-information containing timestamps and node identifiers is bound to generate initial product blocks, and the initial product blocks are chained for evidence storage. In the logistics circulation link, logistics event data is collected to be associated with a tagging identifier to form a logistics track record, data block construction is executed, and uplink evidence storage is carried out to form a logistics chain block sequence; in the sales and use links, user interaction data and use state data are collected and are associated with a tagging identifier to form a use process record, data block construction is executed and chaining and evidence storage are carried out, and a full-life-cycle block chain is constructed by integrating three types of blocks with the tagging identifier as an index on a use chain block sequence. Accurate association and complete tracing of data in production, logistics and use links are achieved, and the problems that traditional data are scattered and tampered easily, and a life cycle link is broken are solved.

The invention discloses a shared material box type temporary storage machine, and relates to the field of production logistics automation, the shared material box type temporary storage machine comprises a machine cabinet and a plurality of material boxes stored in the machine cabinet, and a plurality of conveying mechanisms are vertically arranged on the left portion of the inner side of the machine cabinet at equal intervals; the movable butt-joint mechanism and the positioning assembly operate in a matched mode to take and place the material boxes conveyed on the conveying mechanism, efficient and automatic transfer and temporary storage of the material boxes are achieved through cooperative cooperation of the conveying mechanism and the movable butt-joint mechanism, the conveying mechanism conveys the material boxes to the movable butt-joint mechanism, and the conveying mechanism conveys the material boxes to the movable butt-joint mechanism. The movable butt-joint mechanism stably holds the material box and precisely determines the material box to be located at a follow-up operation station so that other special mechanisms can complete assembling or disassembling operation of a material plate, after operation is completed, the movable butt-joint mechanism and the conveying mechanism are reversely matched, the material box is automatically sent out, automatic feeding, precise positioning and ordered backflow of the material box are achieved, and the working efficiency is improved. And the automation level and the production takt of the feeding and discharging links are remarkably improved, and the smoothness of continuous production is guaranteed.

The invention relates to the technical field of industrial automation and intelligent logistics control, in particular to an aluminum electrolysis covering material intelligent unmanned transportation system and method and a storage medium. According to the invention, the intelligent transportation scheduling system and the intelligent bin system are arranged, the intelligent transportation scheduling system obtains the vehicle information, the material supply bin information, the material unloading bin information and the task information, a deep learning algorithm is adopted to determine the scheduling result, automatic vehicle distribution for material taking and unloading is realized, and the task response speed and the overall operation efficiency are improved. The intelligent warehouse system automatically opens and closes a warehouse door, and carries out real-time information interaction and state monitoring with the transport vehicle and the intelligent transport scheduling system. According to the intelligent unmanned transportation system for the aluminum electrolysis covering materials, whole-course autonomous operation such as feeding, transportation and discharging of the covering materials is achieved, the problems that in a traditional electrolytic aluminum production logistics link, logistics transportation efficiency is low, cost is high, and safety is low are solved, and intelligence and unmanned operation of the electrolytic aluminum industry are improved.

The invention discloses a logistics simulation optimization method, and belongs to the technical field of intelligent manufacturing and logistics optimization. By constructing a digital model, logistics data and equipment operation data are accurately collected and preprocessed, and a simulation model is constructed by using professional simulation software. And identifying a logistics bottleneck and an equipment bottleneck in the battery cell production line based on a simulation result, then proposing a targeted simulation optimization scheme, and realizing continuous optimization of the production line through virtual verification and actual application feedback. According to the invention, the bottleneck station can be accurately identified, the battery cell production logistics efficiency and the equipment utilization rate are effectively improved, the cost is reduced, and scientific and technical support is provided for battery cell production logistics management of a digital factory.

The application 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, which comprises the following steps: step 1, establishing unified state data and standard parameter baseline, calculating consistency deviation value and setting two-stage deviation determination threshold; step 2, receiving on-site events and determining a scheduling time window; step 3, determining task priority and generating a production to-be-executed list; step 4, generating a carrying task set from the production to-be-executed list and determining carrying equipment and task allocation under constraints; step 5, carrying out channel conflict-free path planning and generating a time-space occupation table; step 6, carrying out cross-consistency checking and executing issuing or local recalculation according to the threshold; and step 7, executing on-site operation and updating unified state data, and executing consistency recovery when the deviation exceeds the limit. The application realizes real-time collaborative scheduling and high-reliability operation of workshop production and logistics tasks.