46 results about "Process capability" patented technology

The invention discloses a cooperative control system and method for multi-process processing of a PCB (Printed Circuit Board). Multi-source process data of each process is collected, a process state baseline is formed through mutual verification of redundant sensors, process drift characteristics are examined and identified based on process capability, a process reference library is constructed in a layered manner by adopting a dynamic threshold value, and a generated process deviation parameter is detected; performing correlation analysis on adjacent processes to determine a transfer coupling degree, positioning a defect transfer link through bidirectional verification combining forward tracking and reverse backtracking, and cascading and accumulating process deviation parameters along the link to form a process incidence matrix; carrying out backtracking on defect diffusion to determine a sweep range, generating process state parameters according to the sweep range, and extracting trend turning characteristics to construct a process characteristic spectrum; defect amplification factors are extracted through sensitivity decoupling, process critical nodes are identified, a regulation and control rule base is constructed, process characteristic chromatograms are integrated, and process control instructions are output, so that defect source positioning and propagation path tracking are realized.

The invention provides a reliability detection method and system based on chip module packaging and a medium. The method comprises the following steps: querying a basic threshold value by obtaining chip module packaging process detection parameters and design data; combining the real-time influence data with a preset rule to obtain compensation data, and calculating a correction threshold value; obtaining a process capability state and threshold control data through historical data and statistical process control, further calculating a dynamic threshold, and comparing detection parameters to obtain a process state; after all procedures are qualified, evaluating edge states to obtain risk factors and summing the risk factors to obtain a comprehensive risk value, obtaining a final threshold by combining reliability test data and a reference threshold, and determining the reliability state of the module after comparison; therefore, through calculation processing and threshold comparison of the basic threshold, the corrected threshold, the dynamic threshold and the final threshold, the technology for detecting the packaging reliability of the chip module is realized.

The invention discloses a numerical control machining process generation method based on a PVFNN neural network, and the method mainly comprises the steps: 1) data preprocessing: collecting and processing the 3D shape, material and quality information of a part; 2) constructing and segmenting a data set to form a training, verification and test set; 3) constructing a PVFNN neural network model, integrating a 3D convolutional neural network, a point cloud neural network and a full connection network, and realizing feature fusion through a feature fusion layer and an MLP; 4) performing model training and verification, using a training set to train the model, and using a test set to evaluate performance; 5) process generation: performing model processing on new part information to generate a processing process; the method is used for automatically learning the capability of the discrete manufacturing process from design and manufacturing data, the accuracy and efficiency of numerical control machining process generation are improved, and the problem that in the prior art, due to the influence of manufacturing process capability knowledge and manufacturing experience, a user often cannot select the optimal manufacturing process is solved.

Embodiments of the present application mainly relate to the field of process engineering, and in particular relate to a process device determination method, an electronic device, a medium, and a computer program product. The method comprises: establishing an ontology between multiple process capabilities and multiple types of process device; receiving process formula information inputted by a user, the process formula information comprising process operation information, and a parameter value and material information corresponding to the process operation information; on the basis of the process operation information, generating semantics corresponding to a process capability; performing semantic matching between the semantics of the corresponding process capability and the ontology, to determine a type of process device; and, on the basis of the parameter value and / or the material information corresponding to the process operation information, determining a design parameter value of the process device having said type.

The embodiment of the invention discloses a quality data evaluation method for a multi-variety small-batch manufacturing process, and the method comprises the steps: 1, employing a tolerance coefficient method as a data conversion algorithm, and obtaining a tolerance utilization rate of a single monitoring characteristic; step 2, performing process capability evaluation on each monitoring characteristic, combining standardized data of multiple monitoring characteristics for single monitoring characteristics capable of accumulating the total sample number N and single monitoring characteristics incapable of accumulating the total sample number N so as to perform control process capability evaluation, and performing process control in an auxiliary single-value monitoring mode; and step 3, evaluating the control process capability in the step 2, and formulating a quality state evaluation criterion of multi-variety small-batch process control. According to the technical scheme provided by the embodiment of the invention, the problems of low accuracy of quality evaluation, difficulty in establishing an effective control model and control limit and the like of a quality control mode of multi-variety and small-batch products are solved.

The present invention discloses a lead-free tin-spraying process capability testing method and control method for different solder mask thicknesses. The testing method comprises the following steps: printing solder mask ink on a test board formed with a circuit circle PAD; making the light-blocking PAD pattern on the solder mask exposure film correspond to the circuit circle PAD on the test board; exposing and developing to form a solder mask layer; tin-spraying treatment; determining the tin-spraying process capability for different solder mask thicknesses based on the tin-on rate of the test board with different solder mask thicknesses according to different sizes of solder mask window PADs and solder mask window cycles. The method of the present invention can determine the range of the tin-spraying process capability for different solder mask thicknesses, which is conducive to clearly understanding the process capability and status of the production line, and providing effective data support for the process capability and specification design of the PCB, thereby providing the best solution for the selection of the process, effectively avoiding the quality problem of poor tinning during the PCB tin-spraying process, making the production process run smoothly, and ensuring product quality.

The invention discloses an optimal relaxed single-level continuous sampling OCSP-V and process capability index Cpmk integrated control scheme. The method comprises the following steps: setting a detection number limit, a detection quality upper limit and a risk value; carrying out normality test on the latest production data, if the latest production data are qualified, calculating a process qualification rate and a lower confidence limit, otherwise, stopping the machine; calculating a pIOL value, a process capability and an index in a limit process state; and comparing the process qualified rate with the effective working interval, and deciding to execute the optimal scheme. In the effective interval, the number of continuous qualified products, the inspection score, the sample size and the process capability index key value are calculated, and an integrated control scheme is executed; and keeping recording the latest # imgabs0 # data, calculating a process capability index and a process qualification rate, and comparing the process capability index and the process qualification rate. The method is suitable for production quality control with tolerance upper and lower limit requirements and limited inspection capability, can meet quality, cost and two kinds of risk control at the same time, and can control the risk at a set level.

A method for graphically displaying process data, an electronic device and a storage medium are applied to the electronic device, and the method comprises the following steps: collecting a plurality of test sample data by factory equipment; related parameters of the production process capability are analyzed and calculated; integrating a plurality of calculation formulas according to the calculation results of the related parameters and the quantity of the plurality of test sample data to draw a histogram distribution diagram so as to display the distribution state of the plurality of test sample data; and viewing the test sample data through Excel in the form of data and graphic display.

The invention relates to a process standard establishment method, system and device for airworthiness conformity and a computer readable storage medium. The airworthiness conformity-oriented process standard establishment method comprises the following steps: S1, determining an expected use range of a certain process; s2, determining key performance indexes of the process; s3, determining a key process route; s4, determining key control elements and key process parameters; s5, determining the control range of the key process parameters; s6, judging the stability of the process; s7, issuing a process standard trial draft; s8, in an expected use range, adopting a process standard trial manuscript to carry out trial production on typical products, analyzing production process capability, and carrying out a verification test; and S9, submitting a process standard verification analysis report corresponding to the process. According to the airworthiness conformity-oriented process standard establishment method, system and equipment and the computer readable storage medium provided by the invention, the process standard establishment period can be effectively shortened, and the test cost can be reduced.

This application relates to the field of electronic circuit design technology, and in particular to a PCB layout optimization method suitable for signal transmission. This method acquires manufacturer-specific process capability parameters, constructs a manufacturing disturbance model including conductor geometric deviations, dielectric non-uniformity, and interlayer alignment errors, and embeds an electromagnetic simulation engine to form a dynamic signal integrity analysis model. Based on this, an adaptive layout constraint rule set is generated, driving the layout and routing algorithm to perform manufacturing robustness-oriented automatic routing. This solves the problem of signal integrity degradation in high-speed signal links on PCBs due to manufacturing fluctuations, pre-compensating for manufacturing-introduced non-ideals during the design phase, and improving the first-pass success rate and signal performance consistency of high-speed PCBs.

This application relates to a method, apparatus, electronic device, and storage medium for dynamic process capability assessment. In this disclosure, an access control threshold is first calculated; in the absence of historical data, multi-level random simulations are performed to generate a virtual sample set, and then initial prior distribution parameters are determined; if it is determined that the measured samples to be assessed in the current group pass the access control threshold verification, the prior distribution parameters are recursively updated based on the sample statistical parameters to obtain posterior distribution parameters characterizing the current manufacturing process. Then, a first probability that the process mean is within a preset mean interval, a second probability that the process standard deviation is less than a preset standard deviation limit, and a third probability that the process capability index is greater than or equal to the process capability index target are calculated to obtain the process capability assessment result for the current manufacturing process. This disclosure has at least one advantage: it does not rely on historical data, has a data quality filtering mechanism, and is applicable to small sample scenarios.

The application provides a supply chain data traceability monitoring method and system and a storage medium, relates to the technical field of supply chain quality traceability, and comprises the following steps: collecting production data of different material batches in each link of a supply chain, including raw material performance, processing process parameters and quality inspection results; calculating process capability indexes of each node through an industrial internet gateway, synchronously uploading the production data to the cloud, converting the production data into a vector format, and generating a cross-organization data sequence with material batches as the main line; analyzing link correlation based on the sequence, and constructing a quality influence topology graph dynamically reflecting the influence weight of process parameters on the final quality; when a quality inspection finds a batch quality defect, combining the topology graph and the parameter deviation of the defective batch, calculating the prediction probability of the upstream link as the source of the defect, and generating a visual report showing the most possible source link and the conduction path of the defect, so that accurate traceability of the supply chain quality defect and visual presentation of the influence path can be realized.

This invention discloses a quality control method, apparatus, and system for printed circuit boards (PCBs), relating to the field of PCB manufacturing technology. The method includes: acquiring data collected by various sensors of a PCB manufacturing equipment at each time point within a preset time period; calculating the process capability index of the PCB manufacturing equipment at each time point; connecting the process capability indices at all time points to form a real-time process capability index curve; comparing the real-time process capability index curve with historical process capability index curves; determining whether the PCB manufacturing equipment is abnormal based on the comparison result; if the PCB manufacturing equipment is abnormal, calculating the abnormality level based on the comparison result, and generating control instructions for controlling the PCB manufacturing equipment to perform corresponding actions based on the abnormality level. This method can effectively avoid the problems of PCB defects and increased PCB production costs caused by abnormal process capability indices.

This invention discloses a method for constructing a digital twin geometric model of process capability based on point clouds, comprising: acquiring three-dimensional point cloud data of the area covered by the target process and its corresponding single quality characteristic of an aerospace part product, thereby obtaining a three-dimensional point cloud dataset; obtaining a sequence of measured quality characteristic values ​​for digital twin modeling based on processing and measurement modes; acquiring a theoretical three-dimensional MBD model of the aerospace part product and performing lightweight processing to obtain a lightweight model; labeling the quality characteristic and its corresponding theoretical measurement points; fusing the sequence of measured quality characteristic values ​​with the lightweight model, and performing visualization differentiation and state backtracking on this basis to obtain a digital twin geometric model that integrates measured information; determining the process accuracy using the sequence of measured quality characteristic values ​​obtained under different modes; evaluating process capability according to the process accuracy levels, and providing adjustment suggestions based on the mean offset.

The invention relates to but not limited to the field of large part assembly, in particular to a high-precision assembly part shape maintaining method based on Monte Carlo large model prediction. Comprising the following steps: aiming at multi-stage components of specific product clear group assembly design, extracting the boundary dimension of each stage of component; determining the manufacturing tolerance of each stage of component after forming based on the target boundary dimension in combination with the manufacturing process capability; based on a process instruction of assembling each level of component to the assembled part, segmenting the assembly process and defining the tolerance of each level of assembly process to be in a linear relation with the manufacturing tolerance after the corresponding level of component is formed; constructing a fit tolerance prediction model based on a Monte Carlo method, and determining the contribution degree sequence of the tolerance of each level of assembly process to the tolerance of the whole product; carrying out random sampling on the fit tolerance coefficient to obtain an optimal fit tolerance coefficient; the effectiveness of a prediction result is checked through a visual model, and under the condition that the prediction result is effective, the optimal solution is called as an implementation parameter to complete assembly of the whole part product.

The invention provides a method for monitoring and analyzing the stability of an injection molding process. The method comprises the following steps: detecting an injection pressure value of injection molding equipment according to a set acquisition frequency; wherein the set acquisition frequency is set according to actual working condition requirements; determining a process capability index of the injection molding equipment according to the injection pressure value; judging whether the process capability index of the injection molding equipment is within a set threshold range or not, if yes, determining that the injection molding equipment is stable, and if not, generating an early warning instruction and executing early warning; according to the invention, the injection pressure of the injection molding equipment is continuously acquired for multiple times, the injection molding process capability index value is determined according to the acquired injection pressure value, and the influence of factors such as temperature and a mold is considered in the determination process, so that the stability of the current injection molding equipment can be accurately judged, frequent shutdown of injection molding production is effectively prevented, and the production efficiency is improved. And the production continuity and yield are ensured.

The application relates to the technical field of electronic component reliability, and discloses a flat transformer voltage withstand performance sure reliability modeling and evaluation method, which comprises the following steps: firstly, a constitutive model fusing a physical mechanism is constructed, a time degradation model and a temperature influence model are established based on the geometric size, material properties and environmental stress of an insulating layer, and a process capability parameter is introduced to represent manufacturing fluctuation; secondly, a reliability evaluation model is established, a failure threshold and a margin equation are defined, and physical parameters are identified as random variables to quantify uncertainty; then, Monte Carlo algorithm is used to sample random variables, virtual samples are generated, and voltage withstand margin is calculated on an evaluation time sequence; finally, the number of samples meeting a safety criterion is counted, instantaneous reliability is calculated, and a full-life-cycle reliability curve is generated. The application effectively decouples and quantifies the influence of manufacturing processes, temperature stress and time degradation on voltage withstand performance, and realizes sure reliability evaluation with high confidence.

The invention provides an instance-based unlocking and locking mechanism tolerance optimization method and system. Belongs to the field of intelligent firearm manufacturing. According to the method, on the basis of ensuring that the assembly precision is qualified, the machining cost and the procedure capability index are comprehensively considered, and the tolerance of the unlocking and locking mechanism is designed and optimized. According to the method, on the basis of an unlocking and locking mechanism tolerance instance library, through analysis and calculation of contribution degrees, product processing cost and quality loss optimization targets are constructed, a target optimization model with process capability indexes and tolerance accumulation as constraint conditions is established, and the processing cost and the assembly quality loss are balanced. The design precision under precision manufacturing can be met, the production efficiency is improved, the part quality is improved, and the production cost is further reduced.

This invention relates to the field of metal cutting technology and discloses a corner-cutting device for aluminum alloy doors and windows, including a table, a mounting bracket, a disc cutter, and an MQL nozzle, as well as a micro-lubricant atomization adaptive system. This system includes: a cutting load dynamic calculation module for generating a cutting intensity coefficient by integrating sawing current, temperature, and feed rate; a cutting configuration feature extraction module for generating cutting geometric feature coefficients based on the entry angle and wall thickness; an atomization delivery efficiency evaluation module for obtaining the effective atomization factor; and a system capability degradation evaluation module for calculating the process capability degradation degree by combining tool wear, vibration intensity, and operating condition coefficients, and dynamically adjusting the MQL atomization amount through a lubrication compensation mapping model. This invention can adaptively adjust the lubrication supply according to real-time changes in cutting conditions, effectively solving the problems of insufficient cooling or oil mist contamination caused by fixed-parameter lubrication, and significantly improving machining quality and tool life.

Systems, methods, and computer-readable medium storing instructions for characterizing a recipe of a production system for producing a product include receiving (a) specification limits of a product parameter of the product, (b) resource allocation input information, and (c) historical product information, generating a model that models a relationship between each of a respective proposed target value and both (a) resource allocation impact information and (b) process capability impact information, and displaying or storing the model. In some aspects, displaying the model includes displaying a relationship between each of the respective proposed target values and both (a) resource allocation impact information, and (b) process capability impact information. Further aspects include causing the production system to operate using a selected target value.

The invention relates to the technical field of gear precision measurement and intelligent manufacturing automation control, in particular to a gear measurement center measurement process automation and intelligent scheduling system, which comprises a data acquisition module used for acquiring machining state characteristic parameters of a to-be-measured gear in a machining process; the first processing module is used for marking the physical index of the abnormal gear tooth unit as a high-risk area; the second processing module is used for decomposing the measurement program into a discrete measurement microtask set; the third processing module is used for resolving a process capability confidence index of the gear to be tested; the scheduling execution module is used for generating a hierarchical scheduling instruction: if the process capability confidence index is higher than a preset inspection-free threshold value, generating a direct release instruction and skipping residual measurement tasks; on the contrary, after the optimal cooling waiting time is over, the focusing scanning task is triggered to be executed; according to the method, the measurement uncertainty caused by processing residual heat is effectively eliminated, and the consistency of precision geometric quantity measurement results is guaranteed.

This invention discloses a digital twin-driven collaborative management and control method and system for LCD backlight panel production, specifically relating to the field of production management technology. It addresses the resource misallocation, quality risks, and efficiency losses caused by existing static planning methods that neglect the dynamic coupling relationship between the capacity differences of production lines at specific processes and the process paths of work-in-process. The method involves constructing a digital twin model corresponding to the physical production line, integrating process capability vectors and process path vectors, identifying candidate production line sets based on vector data, assessing parameter resonance risk levels, locating key bottleneck processes in the process network topology, generating dynamic routing schemes to avoid high-risk paths and bottlenecks, and triggering real-time adjustments to the work-in-process production path through the manufacturing execution system to achieve dynamic collaborative optimization of production resources and order requirements.

The present application relates to the technical field of ultra-precision optical manufacturing, and particularly relates to a fast tool planing machining method for a microlens array, a medium and equipment. The method comprises the following steps: determining a feasible planing tool without interference according to surface shape data of a microlens array to be machined; constructing a parameter physical model of a planing base frequency, surface roughness and a machining time length of a single unit based on microlens unit parameters, tool parameters and machining parameters; taking parameter limit conditions as nonlinear constraints and total machining time length as an objective function to optimize and solve fs, Rt and D L , fx to obtain the shortest machining time length; and completing machining by using the optimized parameters. The present application innovatively constructs a multi-physical parameter model, realizes collaborative optimization of optical performance (surface shape), process capability (roughness, dynamic characteristics) and manufacturing efficiency (machining time), ensures nanoscale roughness and dynamic stability, significantly shortens the machining cycle of a large-scale array, and provides an efficient path for batch manufacturing of ultra-precision optical elements.

The application relates to a process standard establishment method, an establishment system, an establishment device and a computer readable storage medium facing airworthiness compliance. The process standard establishment method comprises the following steps: S1, determining an expected use range of a certain process; S2, determining a key performance index of the process; S3, determining a key process route; S4, determining a key control element and a key process parameter; S5, determining a control range of the key process parameter; S6, judging the stability of the process; S7, issuing a process standard draft; S8, in the expected use range, using the process standard draft to produce typical products, analyzing production process capacity, and performing verification tests; and S9, submitting a process standard verification analysis report corresponding to the process. The application provides a process standard establishment method, an establishment system, an establishment device and a computer readable storage medium facing airworthiness compliance, which can effectively save a process standard establishment period and reduce test costs.

Methods, apparatus, and processor-readable storage media for automatically migrating process capabilities using AI techniques are provided herein. An example computer-implemented method includes determining, for a process of an enterprise, process requirements by analyzing data related to the process and data related to the enterprise; generating a recommendation of process capabilities to be incorporated into the process by processing, using AI techniques, the analyzed data; forecasting behavior of the process in conjunction with portions of the recommended process capabilities by performing simulations of the process incorporating the portions of the recommended process capabilities; developing modified versions of the process, based on the forecasting, by migrating feature sets into portions of code associated with the process; testing the modified versions of the process by performing simulations of the modified versions; and deploying at least one of the modified versions of the process based on the testing.

The invention belongs to the technical field of production planning and scheduling systems, and discloses a production planning and scheduling method and system. The method comprises the following steps: acquiring process capability data of each machine tool and process demand data of each order; based on the process capability data and the process demand data, calculating to obtain a process matching degree matrix of each machine tool to each order; based on the process matching degree matrix, the orders are distributed to all machine tools; generating a remodeling time matrix of remodeling time between any two orders of each machine tool based on a pre-collected basic remodeling time database, the process capability data and the process demand data; on the basis of the remodeling time matrix of each machine tool, optimizing order sorting on each machine tool, and minimizing total remodeling time to obtain a final order allocation table; and the overall remodeling total time length is accurately evaluated and minimized, so that the utilization rate and the productivity of the machine tool are remarkably improved in a multi-variety and small-batch production mode, the delivery cycle is shortened, and the plan and execution deviation is reduced.

The invention relates to a product quality index stability dynamic monitoring method and system, and the method comprises the steps: collecting various types of manufacturing data covering steelmaking, hot rolling and cold rolling procedures, and constructing a whole-process material quality history; constructing a layered quality index monitoring framework according to the whole-process material quality resume; the layered quality index monitoring architecture at least comprises a process index monitoring layer, a user side monitoring layer and a manufacturing side monitoring layer; according to a preset index rule engine, performing dynamic calculation on the process index monitoring layer, the user side monitoring layer and the manufacturing side monitoring layer, and obtaining monitoring indexes corresponding to each layer; and performing visual display and SPC process capability analysis on the monitoring indexes corresponding to each layer, and outputting a dynamic monitoring result corresponding to each layer. According to the invention, real-time monitoring and tracing of data of the whole process of steelmaking, hot rolling and cold rolling are realized, and the quality control precision and decision-making efficiency are improved.

The present application belongs to the technical field of precision strip steel production quality control, and particularly relates to a precision strip steel statistical process control method for small batch and multi-variety, and the specific steps are as follows: step S1: establishing a precision strip steel variety feature database; step S2: grouping historical varieties based on a K-means clustering algorithm; step S3: determining the cluster to which the current variety belongs; step S4: extracting historical quality data of the same cluster variety and removing outliers by using a 3σ criterion; step S5: data fusion based on similarity weighting; step S6: adaptive control limit calculation; step S7: multi-quality characteristic comprehensive control; step S8: abnormal mode identification; step S9: process capability evaluation; and step S10: control chart dynamic updating. The method effectively solves the problems of insufficient data, low historical data utilization, single-variable control limitations, fixed control limits and weak abnormal diagnosis capability by using K-means clustering analysis and data fusion technology and adaptive control limit calculation.

This invention discloses a collaborative control system and method for multi-process PCB manufacturing. It collects multi-source process data from each process, establishes a process status baseline through cross-verification of redundant sensors, identifies process drift characteristics based on process capability review, and constructs a process benchmark library using dynamic threshold hierarchies to detect and generate process deviation parameters. It performs correlation analysis on adjacent processes to determine the transmission coupling degree, locates defect transmission links through bidirectional verification combining forward tracing and reverse backtracking, and accumulates process deviation parameters along the links to form a process correlation matrix. It backtracks defect propagation to determine the affected area, generates process status parameters based on the affected area, and extracts trend reversal features to construct a process feature map. It extracts defect amplification factors through sensitivity decoupling, identifies critical process nodes, constructs a control rule library, integrates the process feature map, and outputs process control commands, thus realizing the location of defect sources and the tracking of propagation paths.

The invention provides a method for transmitting process steps in a quality tool, relates to the technical field of manufacturing industry management and data processing, and realizes automatic transmission of the process steps and special characteristics among APQP, PFMEA, CP, DFMEA, MSA and SPC modules by fusing a bill of materials, production parameters and process images to generate an adaptive semantic association model and combining an adaptive dynamic topology network. According to the process steps, an APQP flow chart is generated and then automatically transmitted to a PFMEA generation report, special characteristics are imported into APQP from a DFMEA list and marked on CP, and finally the APQP is output to an MSA / SPC module to generate a measurement task and a process capability report, so that the consistency of data in different files is ensured. Compared with a fixed transmission path described by a file, by dynamically adjusting the network topology weight, monitoring the data integrity in real time and automatically repairing format errors or omissions, an automatic transmission mechanism remarkably improves the collaboration efficiency between modules, and errors caused by manual intervention are reduced.