65 results about "Manufacture execution system" patented technology

The invention provides an abnormity early warning method and system used in a fan manufacturing process. The abnormity early warning method comprises the steps that a multi-source process data stream composed of part forming process data, structure assembling process data and performance testing process data in the fan manufacturing process is acquired; performing process feature analysis processing on the multi-source process data stream to obtain a time sequence evolution feature process coupling feature; performing combined anomaly identification processing on the time sequence evolution features and the process coupling features through a pre-deployed manufacturing anomaly diagnosis model to generate a process anomaly identification result; based on the front-back sequence relation of all the procedures in the fan manufacturing process and the abnormal probability value and the possibility level in the procedure abnormal identification result, the abnormal target procedure node and the associated procedure range of the abnormal influence are positioned; and generating an early warning instruction according to the target process node and the associated process range, and pushing the early warning instruction to a manufacturing execution system. Abnormity real-time monitoring and early warning in the fan manufacturing process are achieved, and the fan manufacturing quality and production efficiency are improved.

The invention relates to the technical field of automatic control of a dispensing process, and discloses an intelligent dispensing control method based on a self-adaptive track and dynamic fault-tolerant control. The method comprises the following steps: acquiring spatial pose data of a workpiece to be dispensed through a visual system, identifying a Mark point, and generating positioning reference information; the information is fused with height measurement data, and a dispensing track and dispensing height control parameters are obtained through calculation; driving an injection mechanism to dispense glue according to the control parameters, collecting a glue dispensing image, and comparing the image template to realize real-time judgment and alarm control of the offset and blockage state of the nozzle; after dispensing is completed, coverage rate analysis is conducted on the dispensing image, and a qualification result used for workpiece circulation judgment is generated; all control parameters, image data and judgment results are uploaded to a manufacturing execution system, the time interval between dispensing and the previous process is recorded, and process tracing and time card control are achieved. According to the invention, the dispensing precision and consistency are improved, and the automatic and fault-tolerant performance is good.

The invention relates to the technical field of enterprise data management, in particular to a lightweight-based enterprise data dynamic integrated management system, which is characterized in that an acquisition module is used for deploying edge computing nodes, receiving multi-source heterogeneous information streams from manufacturing execution systems and equipment logs, dynamically analyzing and standardizing the information streams, and adding metadata tags; uploading is carried out in a batch processing mode; the map construction module is used for constructing a semiconductor blood relationship map by taking the standardized key information as a blood relationship clue; a graph database is used for efficient storage, and a RESTful API interface is configured to support batch import, so that data storage and relevance expression are more flexible and efficient; the prediction module performs reasoning on the atlas by adopting a graph neural network to generate predictive risk distribution, and a correlation analysis set generated by the prediction module is stored back to the atlas in a structured manner; by introducing a multi-thread concurrent write-in and lock mechanism, the atlas supports complex combination query based on a Cypher query language, and supports multi-level and traceability query.

The invention provides an MES-based defect detection and quality control optimization method and system. Defect prevention and process dynamic adjustment are realized through a full-process data closed loop. The method comprises the following steps: collecting multi-process data, extracting features such as material batches, process parameters and equipment numbers to construct defect tags, cleaning historical data, constructing time window features, performing multi-class defect classification prediction by adopting an LSTM + attention mechanism model, and analyzing feature contribution degrees in combination with an SHAP value. And setting a multi-stage early warning mechanism, triggering equipment pause and maintenance notification based on a yield threshold, performing graded response according to defect severity, dynamically adjusting equipment parameters, and linking process optimization suggestions. And iterating the model and the rule, returning rework data to generate an optimized sample, mining a defect-parameter association rule in combination with an Apriori algorithm, and updating the equipment health degree evaluation model. The problems of hysteresis quality and staticization of traditional quality control are solved, and an intelligent closed-loop system from defect prediction to process optimization is constructed.

The invention provides a wafer graph processing system based on semiconductor packaging detection equipment, and the system comprises a defect detection equipment layer which is used for detecting wafer defects in real time and outputting defect types and coordinates; the equipment connection control layer is used for communicating with detection equipment through an SECS / GEM protocol based on an EAP, collecting defect data and converting the EAP data into a standardized format identified by MES through a Highway101 protocol and an EIS; the business execution layer comprises a data storage module, a dynamic updating module and a graphic processing module; and the user operation layer supports multi-dimensional query of defect records and automatic execution of Loss marking and process Move operation. The method comprises the following steps: scanning a wafer through a defect detection equipment layer, outputting defect types and coordinates through a classification algorithm, converting defect data into a standard format, and transmitting the defect data to an MES (Manufacturing Execution System); the service execution layer updates the state of the wafer graph, marks the defect chip as Loss, and records a change history; and the MES controls the wafer to flow to the next process, so that the problems in the prior art are effectively solved, the precision is improved, and the reject ratio is reduced.

The invention discloses a warehouse management method and system based on the Internet of Things, and the method comprises the steps: determining a target material and the demand data of the target material according to a production task issued by a manufacturing execution system; obtaining attribute information of the target material based on the demand data, and distributing priority for the target material according to the attribute information to obtain priority information of the target material; wherein when the target materials comprise various materials, the priorities of different types of materials in the target materials are distributed according to first-class information, and the priorities of the same type of materials in the target materials are distributed according to second-class information; obtaining layout information of a current platform, wherein the layout information comprises storage position information and transportation path information; and according to the priority information of the target materials, the storage positions of the target materials on the current platform are adjusted, so that the target materials with higher priorities can be delivered out of a warehouse in a shorter transportation path. The storage position and the transportation path of the material can be adjusted according to the priority information of the material, and effective operation of a production link is ensured.

The invention discloses an automatic product grabbing system and method, and relates to the technical field of industrial robots, in the system, an equipment body is provided with a grabbing station and a placing station, an inbound positioning assembly outputs an AGV tool vehicle in-place signal, and a jacking positioning assembly establishes a preset grabbing height; the visual positioning assembly collects an image output pose compensation amount, the bar code recognition assembly obtains a bar code and interacts with the manufacturing execution system to obtain a verification result, the controller issues the compensation amount to the industrial robot control end when verification is allowed, and an end effector is driven to complete positioning, locking and unlocking of grabbing locked by a tool vehicle clamp; the tray transferring and positioning mechanism completes transferring and positioning of the shipping tray, and the unlocking and locking mechanism unlocks / locks the locking block handle and conducts visual review in the placing process. By means of the technical scheme, the grabbing and placing alignment precision and the mistake proofing capacity are improved, the risks of collision, falling and locking omission are reduced, and the takt time stability and traceability are improved.

The invention relates to the technical field of production management, and discloses a material data change management method, device and equipment and a medium which are applied to a manufacturing execution system.The method comprises the steps that planned order material data of a current vehicle is acquired; based on the planned order material data, determining a material use quantity required by production of each station, and eliminating missing material data to generate processed material data; comparing the plan order material data with the processed material data to generate a loading difference list according to a comparison result; and updating the planned order material data according to the loading difference list to obtain target order material data. According to the technical scheme provided by the invention, accurate material breakpoint control can be realized, so that material change, trial assembly and production plans are kept consistent.

The invention provides a multi-dimensional data fusion analysis method and system, and the method comprises the steps: collecting multi-source manufacturing information of a manufacturing execution system, carrying out the time sequence alignment of the multi-source manufacturing information through employing a production technology constraint, carrying out the attribute reduction of a multi-dimensional manufacturing data set obtained through alignment, and obtaining a core attribute set, and calculating the importance value of each manufacturing sub-task based on the core attribute set, and generating a task priority sequence. Based on the task priority sequence, candidate resources corresponding to the priority subtasks are extracted from the multi-dimensional manufacturing data set, and the multi-dimensional matching degree of the candidate resources is calculated. And performing weighted fusion on the multi-dimensional matching degree through historical execution data to obtain a resource matching matrix, and performing resource conflict resolution according to the resource matching matrix and the task constraint relationship to generate a resource allocation scheme. According to the method, accurate resource allocation is realized through time sequence alignment and multi-dimensional matching degree calculation, so that the resource utilization rate and the production scheduling efficiency are improved.

This invention discloses a four-dimensional error-proof batch traceability method, device, equipment, and storage medium for vehicle parts. The method receives VIN codes, vehicle model configuration information, and BOM lists from a Manufacturing Execution System (MES), adjusts system settings and verification parameters according to preset rules, scans the barcodes of automotive parts to be installed using a portable data assistant (PDA) client, compares the scan results with the verification parameters, and prohibits installation and triggers an error message if any parameter in the part model, version number, installation sequence, or installation station does not match. For target parts that pass verification, the scan information is recorded and a relationship between the target part and the vehicle is established. The uniqueness of barcodes for individual traceable parts is verified, and a one-scan-multiple-synchronization mechanism is implemented for batch traceable parts. This enables precise error prevention and flexible traceability of part installation, ensures accurate traceability of key parts, and effectively improves the overall vehicle quality control level and production management efficiency.

The invention discloses a flexible manufacturing-based DPA component matching method, which comprises the following steps of: establishing a DPA component requirement catalog, establishing a management database, and creating catalog entries for each component needing DPA detection; the method comprises the following steps: establishing DPA components, and creating a corresponding DPA component for each basic component needing to execute DPA detection in enterprise product bill of material structure management; the method comprises the following steps: establishing a corresponding relation between a DPA component requirement directory and a component, establishing a mapping relation between a DPA requirement directory and a DPA component, triggering to generate or call a corresponding DPA component demand according to the mapping relation, and realizing automatic conversion from a detection requirement to a specific execution material; and establishing a matched operation system, and integrating the system into a manufacturing execution system or a material demand planning module of an enterprise resource plan. According to the method, automatic identification of DPA detection requirements, intelligent matching of detection materials and accurate accounting of related cost can be realized.

The invention relates to the technical field of data processing, in particular to a multi-source data integration and treatment method for improving the intelligent decision-making capability of an MES system, and the method comprises the steps: each data source sends data to the MES system in real time, and determines a trust score based on the passing probability, the transmission duration, the missing field proportion, the difference with a reference value and the historical comprehensive difference; calculating a weight coefficient in combination with the data difference and the trust score, and generating a fusion estimation value; calculating uncertainty by using the data source correlation coefficient and the weight coefficient; and determining a super-tolerance probability based on the fusion estimation value and the uncertainty, further calculating a governance priority score in combination with the business influence quantity, and performing integrated governance on the multi-source data. According to the method, the problems of unreliable MES multi-source data fusion and low decision-making efficiency are solved, and the accuracy of multi-source data management and the decision-making efficiency of an MES system are improved by intelligently quantifying the data quality and the business risk.

The invention relates to the field of manufacturing execution systems and intelligent manufacturing, in particular to a manufacturing execution system management method oriented to production data, which comprises the following steps: a multi-source data acquisition step: acquiring physical sensing state data, manual interaction time data and system scheduling data of a manufacturing execution system, and integrating to generate multi-source heterogeneous production data; a trust quantitative evaluation step of quantifying the distortion degree of the execution state based on the multi-source heterogeneous production data to obtain an execution trust entropy; a cross validation prediction step: comparing the physical sensing state data with the man-machine interaction time data to calculate execution trust entropy, and predicting system failure risk; a dynamic scheduling decision step: setting a scheduling degradation adjustment mechanism based on execution trust entropy, and outputting a target scheduling instruction to adjust the running state of the system; according to the method, the dynamic balance between pursuit of efficiency and maintenance of authenticity of underlying data is realized, and the vulnerability resistance of the complex manufacturing network is effectively improved.

This invention relates to a predictive maintenance method for power module packaging reflow oven equipment, comprising: collecting multi-physics operating status data of the reflow oven; aligning the multi-physics operating status data with quality inspection data in a manufacturing execution system in a time series, and classifying and labeling product quality based on a fuzzy membership function to construct training samples; extracting features from the multi-physics operating status data, filtering the extracted features in conjunction with an equipment physical degradation model, and constructing a degradation feature vector; inputting the degradation feature vector into a multi-level diagnostic model for processing, and outputting fault warning information and process compensation parameters; determining the equipment health level based on the fault warning information, and executing a corresponding graded response strategy based on the equipment health level. This method enables predictive maintenance of the reflow oven through multi-physics fusion monitoring, dual-drive diagnosis, and closed-loop linkage.

The invention relates to the technical field of data processing, in particular to a weighted polling method, a data synchronization method, a manufacturing execution system and equipment. In the weighted polling method, a first operation value is calculated through a first calculation strategy according to the total weight; wherein the total weight is the sum of the weights of all the objects; traversing all objects allowed to be scheduled, and performing bit operation by utilizing the first operation value, the bit mask of the current object and the second operation value until the first operation value is determined to be matched with the bit mask of the current object, and taking the current object as a target object to be scheduled; wherein the second operation value is obtained according to the bit mask of the current object. According to the method, bit operation is used for replacing traditional division, multiplication and modular operation, the calculation complexity is extremely low, and especially in a high-performance distributed environment, the efficiency of data synchronization and object (server) request distribution can be improved. According to the method and the device, extremely low calculation complexity and excellent performance can be provided in a high-performance load balancing scene.

The invention discloses a distributed tool management method and system based on a block chain, and belongs to the technical field of block chains, the tool management system comprises a distributed tool library, a block chain, a tool input module and a tool management module, and the tool management module is used for receiving a first tool scheduling task from a manufacturing execution system; based on the first tool scheduling task, an optimal tool scheduling scheme is calculated from a distributed tool library, and the optimal tool scheduling scheme is used for scheduling a target tool closest to the first machine tool; generating a tool scheduling request based on the optimal tool scheduling scheme, and uploading the tool scheduling request to the smart contract of the block chain; receiving an approval passing instruction from the block chain smart contract; and performing tool scheduling based on the optimal tool scheduling scheme. According to the tool management system based on the block chain, the speed and the safety degree of tool scheduling can be improved.

The invention provides a high-concurrency process information management method, device and equipment oriented to an MES (Manufacturing Execution System). The method comprises the following steps: constructing a process function dependency graph based on a process function dependency relationship among processes in the MES, and constructing a process flow dependency graph based on a process flow dependency relationship among the processes; determining a node mapping relation based on the function attribute associated information of the process nodes in the process function dependency graph and the process sequence associated information of the process nodes in the process flow dependency graph; analyzing a mutual association relationship between process nodes in the process function dependency graph and the process flow dependency graph based on the node mapping relationship to obtain interactive process nodes; and fusing the process function dependency graph and the process flow dependency graph based on the interactive process nodes to obtain a high-concurrency process information database. According to the invention, efficient management and rapid access of the MES system process information and the complex dependency relationship thereof are realized, and timeliness and accuracy of production scheduling are guaranteed.

The application provides a signal sending method and device, and belongs to the technical field of semiconductor manufacturing. The signal sending method is applied to an equipment automation control EAP device, and comprises the following steps: obtaining a communication state of a processing equipment, wherein the communication state comprises online and offline, and the processing equipment comprises a main equipment and an auxiliary equipment corresponding to the main equipment; receiving a material monitoring signal of the processing equipment, wherein the material monitoring signal comprises a conveying signal of the auxiliary equipment and an unloading signal of the main equipment; judging whether a preset condition is met according to the communication state and the received material monitoring signal; and in the case that the preset condition is met, sending a material conveying signal for the main equipment to a manufacturing execution system MES client. The technical scheme of the application can send the conveying signal of the processing equipment.

The invention relates to the technical field of manufacturing execution systems, in particular to a supply chain interruption risk adaptive identification and recovery method, which comprises the following steps: obtaining product BOM structure data and a raw material inventory state, mapping a main material and an alternative material into directed nodes, establishing a BOM alternative directed acyclic graph, and establishing a BOM alternative directed acyclic graph; and extracting physical performance parameters of each node in the BOM substituted directed acyclic graph, and generating a resource node attribute vector set. According to the method, the optimal alternative path combination is calculated with the purpose of minimizing the performance loss, the executable self-adaptive reconstruction production instruction is directly generated, the closed-loop recognition and recovery process enables a production system to dynamically adapt to fluctuation of a supply chain, passive production interruption response is changed into active risk avoidance and self-optimization adjustment, and the production efficiency is improved. And the toughness of the production plan is enhanced.

A method for the automated configuration of software systems involves processing a configuration request from multiple software agents, each of which has a large language model. Each agent contributes to fulfilling the request based on its role and expertise (domain expert, application expert, configuration expert). The result is a new or adapted configuration of the software system.

The invention discloses a production line transcoding nested control method based on BIM and MES, particularly relates to the technical field of industrial automation control, and is used for solving the problem that a control chain is difficult to construct, verify and dynamically adjust timely and reliably under the conditions of production line equipment adjustment, process path change and non-uniform model and protocol of a field controller, so that the production efficiency is improved. Therefore, the production process continuity and the process safety are ensured. Neutral control instructions carrying security constraints are generated through a control anchor point library based on a building information model and a manufacturing execution system process section anchor point nesting diagram, the neutral control instructions are unified into a controller instruction stream through a transcoding plug-in, and connectivity and capability verification and automatic replacement reconstruction are executed before issuing. The control chain can be quickly constructed and verified when the equipment is adjusted, the path is changed or the controller is heterogeneous, the mismatching risk of manual configuration is reduced, and the adaptability and the reliability of the control configuration are improved.

The invention discloses a manufacturing execution system MES equipment online operation state data processing system and method. The system comprises a business layer, a data layer, an acquisition layer and an equipment layer. Wherein the equipment layer achieves a multi-thread and high-concurrency data acquisition function by utilizing a unique goroutine and channel mechanism of Golang; the acquisition layer is used for efficiently processing data of multi-source heterogeneous equipment, ensuring that operation parameters of various types of equipment can be acquired in real time, and providing timely and accurate data support for subsequent state research and judgment; wherein the service layer uses a JavaScript script to create an equipment operation judgment rule base, dynamically analyzes equipment parameters, studies and judges an equipment operation state, and writes the equipment operation state back to a data table.

The application discloses a data management method, system, device and medium of a semiconductor manufacturing execution system, and the method comprises the following steps: creating or obtaining unique identifiers of upper-layer components and lower-layer components in a connection component tree, each layer of components of the component tree is mapped to state data of different scopes to realize isolation of component states at a hierarchical boundary; confirming a mixing mode of context data between the upper-layer components and the lower-layer components; mixing the state data of the upper-layer components and the context data of the lower-layer components based on the mixing mode and the unique identifiers to form current scope data corresponding to the lower-layer components; and the lower-layer components obtain service data provided to the upper-layer components based on the unique identifiers in the current scope data through a scope component, so that the service data is used by the service. The application realizes a dynamic state isolation mechanism, a state management tool can well realize state isolation at a component level, extraction and reuse of complex services are realized, and data combination forms between components are more flexible.

The invention belongs to the technical field of tire production, and particularly relates to an online non-stop switching emptying process for extruded rubber. According to the invention, the unit glue discharging amount of the extruder is calculated, the total glue discharging revolution required for completing glue discharging and emptying actions is calculated, the time is calculated by combining the real-time rotation speeds of crown glue of various specifications in the rotation speed formula table of the manufacturing execution system during production, and time conversion countdown is carried out by utilizing a PLC calculation function, so that the non-stop switching of glue types is realized; compared with the prior art, cost loss caused by glue emptying when equipment is shut down is successfully avoided, a glue material switching quality monitoring method is perfected, the time utilization rate of the equipment is increased to 95% or above after the technology is applied, and the problem of time cost loss caused by glue emptying when the equipment is shut down during glue material switching in an extrusion project can be solved.

This invention provides a semiconductor processing control method and system based on mapping graph inheritance. The method includes: configuring step inheritance attributes for each process step and configuring machine drawing attributes for each machine; when a batch to be processed arrives at the current machine, it is associated with the current process step; determining the required mapping graph data source information based on the step inheritance attributes, machine type, and machine drawing attributes; verifying the correctness of the required mapping graph data source; if the verification passes, acquiring the associated mapping graph data and executing processing; if the verification fails, intercepting the exception; the system includes: a manufacturing execution system module, configuring step inheritance attributes and machine drawing attributes, and determining the mapping graph data source information; an equipment automation system module, initiating a pre-verification request, and controlling whether the current machine processes based on the verification result; and an appearance inspection image management system module, storing and managing the mapping graph data, and verifying the mapping graph data source information.

The invention discloses an over-gauge product automatic sorting method based on EAP, and relates to the technical field of sorting, a manufacturing execution system determines whether a wafer is qualified according to a detection value reported by a measuring machine, and generates a corresponding mark; calculating a necessary sorting index in combination with the batch confusion index and the rework complexity index, comparing the necessary sorting index with a preset threshold value, and judging whether the wafers must be sorted by the sorting machine or not; and when the index is lower than a threshold value, the system intelligently controls the wafer to complete sorting operation on the processing machine or the sorting machine according to the sorting capacity of the processing machine. In this way, the high-load state of the sorting machine can be effectively relieved; meanwhile, whether the wafer must pass through the sorting machine or not can be judged according to specific conditions, and the stability of the operation process is ensured; therefore, whether the sorting machine is bypassed or not can be intelligently and dynamically determined on the premise of keeping the wafer classification accuracy, so that the utilization rate of the sorting machine is further reduced, and the overall production efficiency is improved.

The invention relates to the technical field of cement production quality management and control, in particular to a cement raw material quality online management method and system. The method comprises the steps that a worker enables a neutron instrument to be in communication connection with a distributed control system, enables a luminoscope to be in communication connection with a manufacturing execution system, and enables the distributed control system to be in communication connection with the manufacturing execution system; the distributed control system obtains production operation parameters and sends the production operation parameters to the manufacturing execution system; the luminoscope obtains mill raw material detection data and kiln raw material detection data and sends the mill raw material detection data and the kiln raw material detection data to the manufacturing execution system; and the neutron detector obtains the in-mill raw material detection data and forwards the in-mill raw material detection data to the manufacturing execution system through the distributed control system. Through the mode, the quality data information island problem can be solved, the data information is collected, monitored, alarmed and analyzed in real time, the statistics and analysis workload can be effectively reduced, and the management efficiency is improved.

The present disclosure provides a welding method and welding system for terminal posts, said welding system comprising a control apparatus, a manufacturing execution system, and a welding device. The control apparatus is used for, when a first target verification result represents that verification is successful and a downward pressing result of a pressing plate mechanism in the welding device represents that downward pressing is completed, sending to the welding device target welding coordinates of each terminal post. The downward pressing result of the pressing plate mechanism is determined on the basis of height feature information of the pressing plate mechanism and height feature information of bus assemblies corresponding to a plurality of terminal posts, and the target welding coordinates of a terminal post are determined on the basis of first terminal post coordinates of said terminal post in a welding station coordinate system and the height feature information of the bus assembly corresponding to said terminal post. The welding device is used for, on the basis of the target welding coordinates of each terminal post, welding each terminal post and the corresponding bus assembly.

The utility model discloses an intelligent logistics elevator system. The system comprises a rack of a vertical frame structure, a cargo carrying platform capable of ascending and descending in the vertical direction, a lifting assembly driven by a synchronous motor and a PLC capable of achieving accurate control. The control assembly further comprises a position sensor, a weight sensor and a human-computer interaction interface (HMI), and intelligent control over platform lifting, load monitoring and state display is achieved. In addition, the system performs data interaction with an external warehouse management system (WMS) and a manufacturing execution system (MES) through an industrial Ethernet or a wireless communication module. The conveying device is arranged above the cargo carrying platform and used for automatically entering and exiting cargoes, the safety assembly comprises an outer protective net and a limiting stopper, and operation safety is effectively guaranteed. The system has automatic operation, manual debugging and remote maintenance modes and is suitable for vertical conveying of light materials such as paperboards and cartons, and the logistics processing efficiency and the intelligent level are improved.

The application relates to a kind of online generation methods of solid wood floor two-dimensional code, comprising: S1, obtaining solid wood floor production order information, and determining corresponding production process flow information based on the solid wood floor production order information;S2, each batch of solid wood floor workpiece is screened by machine vision identification device, and the solid wood floor workpiece screened according to the pre-set standard condition is classified according to the production order information, and different types of solid wood floor workpiece are respectively placed in different trays;S3, based on the information in the two-dimensional code label of any tray obtained by scanning code equipment and the process production information of each solid wood floor workpiece in the tray obtained by manufacturing execution system in the processing process according to the production process flow information, the final two-dimensional code label corresponding to the tray is generated.