55 results about "Production logistics" patented technology

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 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 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.

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 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 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 provides a temperature measurement-based production logistics planning system for research and development of thermosensitive chips. The temperature control safety and the logistics scheduling intelligent level of the thermosensitive chips in the multi-node circulation process are improved; the method comprises the following steps: firstly, deploying temperature sensors in a material storage area, a transportation path node and an equipment interface, collecting environment temperature-time sequence data, constructing a temperature fluctuation feature vector, and calculating a thermal stress equivalent value based on a material response function; thirdly, a constraint rule is established according to parameters such as thermal exposure duration and path transportation time efficiency of each node, and multi-objective optimization is fused to generate an optimal logistics path meeting thermal threshold limitation; and finally, when the path thermal risk is close to the material tolerance, the system intelligently judges and executes local temperature control or path reconstruction, and whole-process closed-loop adjustment is realized. Dynamic temperature control and path cooperative control in the thermosensitive chip transportation process are achieved, and the thermal safety, path intelligence and production yield of thermosensitive chip transportation are improved.

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.

The present invention relates to the field of production logistics in industrial vehicle manufacturing, and specifically to a conveying and stacking rack for automobile spare parts. It comprises a number of gearboxes, and also includes: a number of supporting brackets arranged in an array in the vertical direction, a U-shaped sliding platform connected to the number of supporting brackets; a supporting base arranged below the bearing base and hinged to the bearing base at one end; a power mechanism capable of driving the U-shaped sliding platform to move in the vertical direction; a number of self-locking mechanisms capable of positioning the gearbox through the ribs on the gearbox; a number of heightening mechanisms capable of connecting the number of supporting brackets, an anti-drop assembly capable of preventing the number of supporting brackets from falling off, and a sliding translation mechanism capable of moving the number of supporting brackets into the vehicle compartment. This device can improve the efficiency of loading and unloading gearboxes and reduce the labor intensity of workers.

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 discloses an intelligent suspension conveying system for mechanical structural steel, and relates to the technical field of conveying equipment, the system comprises a field equipment layer, a process control layer and a transportation management layer, the field equipment layer is composed of a track module, a suspension carrier, a driving device, a flow dividing and converging 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 (Programmable Logic Controller), a segment speed control module and an actuator; the transportation management layer comprises four core modules, namely a task distribution module, a path selection module, a load scheduling module and a conflict detection module, performs task scheduling by applying an improved wolf pack optimization algorithm, and forms a complete closed-loop control system in combination with space-time conflict detection and a conflict resolution algorithm based on concentric-square-shaped search. According to the invention, a plurality of mechanical structural steel workpieces can be intelligently dispatched and orderly transported in a complex track network, the automation and intelligence level of production logistics is obviously improved, and the transportation process is ensured to be safe and efficient.

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 invention provides a logistics detection method and device, a medium and electronic equipment. The logistics detection method comprises the following steps: obtaining production logistics data; performing a simulation test on a digital twin model of the production logistics based on the production logistics data to obtain a duration ratio of an idle state, a running state and a waiting state of equipment in the digital twin model; obtaining logistics detection information based on the duration ratio, if the duration ratio of an idle state in the duration ratio is maximum, the logistics detection information is that bottleneck equipment for producing logistics is at the preceding stage of the target equipment, and if the duration ratio of an operation state in the duration ratio is maximum, the logistics detection information is that bottleneck equipment for producing logistics is at the preceding stage of the target equipment. If yes, the logistics detection information indicates that the bottleneck equipment is the target equipment, and otherwise, the logistics detection information indicates that the bottleneck equipment is at the rear stage of the target equipment. According to the logistics detection method, bottleneck equipment in production logistics can be quickly checked, so that the detection efficiency is improved.