48 results about "Manufacture execution system" patented technology

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 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 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 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 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.

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 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.

A method includes: receiving an auxiliary routing request from a manufacturing execution system (MES) apparatus of a first site by an inter-site backup management apparatus; selecting an auxiliary route to a second site based on the auxiliary routing request and a statistical model by the inter-site backup management apparatus; including the auxiliary route in a route associated with a wafer lot by the MES apparatus; and performing a semiconductor processing operation on a wafer of the wafer lot according to the route.

A method for operating a plurality of production plants by a manufacturing execution system (MES), includes providing central computational hardware as a regional hub running MES software configured to manage production processes throughout the plants, configuring a first MES for a first single plant connected to the regional hub, creating for each further plant the respective manufacturing executions system by inheriting all configurations of the first MES to the further MESs, and configuring the additional plants over time in the existing solution in the regional hub without reinstalling software of the MES and without reapplying some configurations already performed in the first plant. In multi-plant solutions, the TCO is decreased. The same number of servers hosting the MES / MOM solution serving one plant, manages multiple plants. The set of servers constitutes a single MES / MONM solution distributed environment hosted by the same regional hub or single virtual datacenter for Cloud providers.

This invention relates to a method, electronic device, and storage medium for acquiring model feature data. The method includes the following steps: a manufacturing execution system sends the basic attribute features of a mold part to a model management system; the model management system matches the model file and then transmits the model file to mold programming software; the mold programming software acquires the geometric feature data of the mold part; the basic attribute features include at least one of the following: part name, part material, material hardness, part size, and product name; the model file includes a three-dimensional model of the part and the basic attribute features matching the three-dimensional model; the geometric feature data includes at least one of the following: contour data, standard color data, part hole type data, model facet count data, model volume data, and four-way graphic color value data. The solution provided in this application can automatically acquire the geometric feature data of a mold part based on its basic attribute features, effectively improving efficiency and accuracy.

The invention provides a material handling system. The system comprises a central scheduling device used for receiving a carrying instruction issued by a manufacturing execution system MES; matching carrying equipment based on the carrying instruction; sending the carrying task to carrying equipment; the carrying equipment is used for receiving a carrying task; generating a plurality of candidate paths based on the carrying task; decomposing each candidate path into a plurality of continuous space-time units; sending the space-time units of the plurality of candidate paths to a central scheduling device; the central scheduling equipment is also used for receiving the space-time units of the plurality of candidate paths; based on the space-time units of the plurality of candidate paths, performing conflict rehearsal on the plurality of candidate paths by using a digital twin system, and selecting an optimal path from the plurality of candidate paths; sending the optimal path to the carrying equipment; the carrying equipment is further used for receiving the optimal path; and carrying according to the space-time unit of the optimal path.

This utility model discloses a detection device for detecting defects on the undercarriage of automobiles, including a camera structure, a field control console, and a MES (Manufacturing Execution System) central control platform. A first track is positioned above the camera structure, which moves towards or away from the undercarriage of the automobile and along the length of the first track via a lead screw drive assembly. The MES central control platform is communicatively connected to the camera structure to receive, analyze, identify, and record the captured images of the undercarriage. The field control console is communicatively connected to the MES central control platform and electrically connected to the camera structure, the first track, and the lead screw drive assembly. It controls the operation of the camera structure, the first track, and the lead screw drive assembly, and displays the analyzed images of the undercarriage. By combining the camera structure and the MES central control platform, the device automatically determines whether there are any abnormalities in the assembly of the automobile chassis. The rework station can quickly identify the location of abnormalities by comparing the captured images, improving work efficiency.

It is the objective of the present invention to provide a method for operating a plurality of edge production resources by a manufacturing execution system that requires less investments into the centralized MES architecture and guarantees low latency in data transmissions and high throughput of manufactured products. This objective is achieved according to the present invention by a method for operating a plurality of edge production resources by a manufacturing execution system, said method, comprising the steps of: a) providing a number of interlocking edge apps and track and trace edge apps to the production resources at shopfloor level; b) providing a number of higher-level interlocking apps and higher-level track and trace apps also related to the edge production resources at an elevated supervision level wherein the edge apps provide only a subset of functionalities as compared to the central, higher-level apps at the elevated supervision level; c) creating a bill of process at the elevated supervision level thereby defining a number of products to be produced on at least one of the edge production resources; d) loading the data for the production of a subset of the number of products defined in the bill of process into the cache of the respective edge production resources; e) producing the subset of the number of products according to the defined bill of process by the respective edge production resources; f) exchanging data between the edge apps and the higher level apps during the production of the subset according to the functionalities defined in the edge apps and in the higher-level apps; g) after completion of the production of the subset of the number of products, deleting all data related to this subset of the products in the caches of the edge production resources, and h) processing the data related to this subset of the number of products in the higher-level apps according to the functionalities provided by these higher-level apps. Thus, the present method paths a way to distribute the track & trace and interlocking functionalities in a smart way over the MES architecture thereby benefitting from small and flexible edge structures and reliable and powerful higher level structures. In particular, the deletion of all data related to a product for that the production is finished, allows to "reset" the edge apps and refresh them functionality-wise and storage-wise for the production of the next bunch of products.

The invention discloses a selection box multi-choice label processing device in a semiconductor manufacturing execution system, and aims to solve the problems of low rendering efficiency and insufficient multi-choice label display adaptive capability under the condition of large data volume. The device comprises a user operation response module, a label processing engine, a virtual scrolling engine and an interaction processing module. The label processing engine automatically folds the over-limit labels according to a preset priority by dynamically calculating the total width of the labels and comparing the total width with the available width of the container. The virtual scrolling engine calculates a visible item index by monitoring a scrolling event, and only renders a visible area item to improve performance. And the interactive processing module coordinates the two to work cooperatively. According to the method, the response efficiency and the user experience of a system interface under a large data volume are effectively improved.

A method for automatically configuring a software system. In this case, the configuration request is processed by a plurality of software agents, each agent having a large language model (LLM). Each agent contributes to completion requests based on its role and professional knowledge (domain experts, application experts, configuration experts). The result is a new or adapted configuration of the software system.

This disclosure provides a roller conveyor laser cutting system, comprising: a workshop manufacturing execution system, a first transmission track, at least one material-carrying worktable, at least one laser cutter, and at least one lifting device corresponding to each laser cutter; the laser cutters are located above the first transmission track, each laser cutter is configured with a corresponding cutting station, and the lifting devices are located below the cutting stations of the corresponding laser cutters; the material-carrying worktable is used to carry the sheet material to be cut and is capable of moving along the first transmission track in response to the control of the workshop manufacturing execution system; the lifting devices are used to perform lifting operations in response to the control of the workshop manufacturing execution system to raise the material-carrying worktable to the cutting station of the corresponding laser cutter or lower it to the first transmission track; the laser cutter is used to perform laser cutting on the sheet material carried by the material-carrying worktable located at the corresponding cutting station.

The invention provides an FCBGA carrier plate production scheduling optimization method, system and device and a medium, and belongs to the technical field of semiconductor manufacturing. According to the method, technological parameter data of key procedures such as laser drilling, electroplating and laminating are collected in real time, and a quality risk digital twin dynamically evolved along with the production progress is constructed; calculating the quality risk entropy of each production batch based on the quality feature data in the digital twin; calculating a dynamic priority score in combination with the quality risk entropy, the delivery time data and the equipment state data; executing a shunting scheduling decision according to the priority score and the quality risk entropy, and generating a differentiated scheduling instruction; and finally, the manufacturing execution system drives the production equipment to execute corresponding operation. According to the method, accurate prediction and active prevention and control of the quality risk in the production process of the FCBGA carrier plate are realized, the process loss of high-value materials is effectively reduced, and the equipment utilization rate and the production yield are improved.