25 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.

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 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.

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.

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 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.

A layout optimization method, system, electronic device, storage medium and program product, the layout optimization method comprising: obtaining a conflict pattern group that does not conform to a layout parameter rule in a target layout; within a lithography limit process window, shrinking the feature size of a pattern in the conflict pattern group to an optimized feature size to obtain an optimized target layout. Since the shrinking of the feature size will affect the pitch, the method of adjusting the feature size of the pattern in the conflict pattern group to the optimized feature size within the lithography limit process window improves the process capability limitation problem, and easily makes the optimized target layout conform to the process requirement; moreover, the method of adjusting the feature size of the pattern to improve the process capability limitation problem also reduces the demand for re-drawing the layout, which is also conducive to reducing the probability of repetitive work caused by the information gap between the layout design party and the manufacturer, thereby improving the work efficiency.

The invention provides an evaluation method for controlling based on temperature and humidity measuring points in a factory. The method comprises the following steps: arranging the temperature and humidity measuring points and collecting temperature and humidity data of all quarters; calculating process capability indexes of all quarterly data of each measuring point and carrying out first-order classification; carrying out clustering analysis on all quarterly data of each measuring point and carrying out second-order classification; determining a final evaluation category of each measuring point based on the first-order classification and the second-order classification; and setting a jump category condition, analyzing the final evaluation category of each measuring point, and readjusting the final evaluation category of each measuring point. According to the method, the real-time performance and accuracy of process control and the accuracy of decision making can be improved.

The embodiment of the application provides a steel product mechanical property margin analysis adjustment method and device, relates to the product performance analysis technical field, and the method comprises the following steps: confirming the margin of product mechanical property data based on process capability statistics of product mechanical property data; setting an adjustment target of the margin, and adjusting the margin based on process parameters in a steel manufacturing process; and analyzing whether the adjusted margin meets adjustment requirements. The technical scheme of the application realizes the analysis of product mechanical performance through the margin of product mechanical performance, and realizes the adjustment of product mechanical performance through the adjustment of the margin, so that the product performance stability level is improved.

This invention discloses an integrated control scheme for optimal four-parameter continuous sampling inspection and first-generation process capability index. The specific steps are: (1) Given; (2) Determine the limit process and calculate; (3) Determine the process capability of the boundary process; (4) Calculate the integrated control scheme parameters (); (5) Execute the integrated scheme; (6) Collect data for normality test. If the normality is ≥ 0, proceed to (7); otherwise, stop production for maintenance; (7) Record data and calculate; (8) Compare with : if ≥ 0, continue to step (9); otherwise, stop production for maintenance; (9) Compare with : if ≥ 0, proceed to (10) without inspection; otherwise, return to (5); (10) Observe whether the system variables change. If they change, return to (5); otherwise, do not inspect. This invention is used for production lines with limited inspection capabilities. While meeting quality and cost requirements, it reduces the first and second types of risks. It can be used for quality control of production processes with tolerance upper and lower limits and limited inspection capabilities.

This invention proposes an example-based tolerance optimization method and system for locking and unlocking mechanisms, belonging to the field of intelligent firearms manufacturing. The method optimizes the tolerance design of the locking and unlocking mechanism by comprehensively considering processing costs and process capability indices while ensuring qualified assembly accuracy. Based on a tolerance example library of locking and unlocking mechanisms, the method constructs optimization objectives for product processing costs and quality losses through contribution analysis and calculation. It establishes an objective optimization model with process capability indices and tolerance accumulation as constraints, achieving a balance between processing costs and assembly quality losses. This invention can meet the design accuracy requirements of precision manufacturing, improve production efficiency, enhance part quality, and further reduce production costs.

This application discloses a method, apparatus, electronic device, and storage medium for determining matching risk. The method includes: acquiring first dimension data of multiple first matching parts and second dimension data of multiple second matching parts; constructing a first normal distribution of the first dimension data and a second normal distribution of the second dimension data; obtaining process capability indices of the first and second matching parts based on the first normal distribution, the second normal distribution, and a target formula; and determining the matching risk of the first and second matching parts based on the process capability indices. This method can determine the matching risk of the first and second matching parts based on the first dimension data of the first matching parts and the second dimension data of the second matching parts, revealing the impact of interactions between different matching parts on the final assembly result, avoiding incompatibility issues when assembling the first and second matching parts, improving the success rate of the assembly result, and reducing structural quality risks.

The application provides a method for dynamically evaluating metallurgical coke for furnace, based on the median of a non-normal coke quality data set, two normal data sets are constructed, then the weighted standard deviation of the two normal data sets is calculated, a non-normal process capability index model is created, then the weight of each coke quality index is calculated by using a difference coefficient method, the weight is combined with the established non-normal process capability index model, a non-normal coke quality data multivariate process capability comprehensive evaluation model is obtained, so that the evaluation process of coke quality is realized. The application can accurately evaluate the coke quality of the coking industry for providing metallurgical coke for blast furnace, provide high-quality coke for the ironmaking process, and ensure the stable operation of the blast furnace.

The utility model discloses a lockset reshaping jig which comprises an upper die base, a lower die base, a lockset and reshaping blocks, a reshaping cavity is formed in the top of a lower die, a plurality of reshaping blocks are arranged in the reshaping cavity, the lockset is located in the reshaping cavity and located between the reshaping blocks on the two sides, and the lockset is formed through powder metallurgy injection molding. The production efficiency is improved, the precision is improved, the cost is reduced (traditional die-casting and stamping processes are replaced), the processing capability of the product is improved, the next process can be carried out only when the size, the appearance and the surface roughness can meet the requirements, and the yield of the product is improved.

This invention discloses a simulation analysis method for pole-mounted circuit breaker opening distance based on VSA (Variable Size Analysis). The technical solution includes: S1. Constructing a full-dimensional chain model related to the opening distance; S2. Determining the control target for the opening distance; S3. Determining the reference coordinate system for each part based on actual processing technology and assembly sequence; S4. Creating assembly relationships and measurement variables; S5. Assigning tolerance values ​​to each part based on actual process capabilities; S6. Performing Monte Carlo simulation calculations on the model with assigned tolerance values ​​to obtain the first round of simulation results; S7. Analyzing the error situation of the first round of simulation results; S8. Iterating based on the error situation until the control target is met. This invention solves the problems of complex dimensional chain calculations during design, repeated adjustments to the opening distance during assembly, and low assembly efficiency. By using VSA software for simulation analysis, the difficulty of dimensional chain calculations is reduced. Each part is processed and assembled according to the simulated tolerances and assembly sequence, eliminating the need for adjustments, thus ensuring the opening distance meets the requirements and achieving high assembly efficiency.

The surface mount process parameter feedforward adaptive regulation method based on tin paste printing detection relates to a process parameter adaptive regulation method and belongs to the technical field of electronic assembly process optimization. The method aims to solve the problem that a chip mounter is difficult to adaptively adjust parameters according to real-time working conditions, resulting in poor mounting consistency. The method first constructs a welding offset prediction network model for predicting the position deviation of an element after welding according to tin paste printing offset and process parameters; and then constructs a process parameter compensation model based on deep reinforcement learning to dynamically generate optimal compensation parameters based on the prediction results. In actual production, real-time offset data is obtained through a tin paste detection device to drive the above-mentioned model to adjust key process parameters such as mounting coordinates and height of the chip mounter online, thereby realizing feedforward adaptive compensation. The method can effectively improve the element mounting accuracy and process process capability, and provides an efficient cross-process fusion optimization scheme for precise electronic assembly.