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Research On Online Quality Control Method For Front Axle Assembly Process

Posted on:2020-09-26Degree:MasterType:Thesis
Country:ChinaCandidate:H ZhanFull Text:PDF
GTID:2381330578473018Subject:Industrial Engineering
Abstract/Summary:PDF Full Text Request
The front axle is a complex mechanical assembly product with many assembly processes and complicated assembly processes.There are error propagation and error accumulation effects in the front axle assembly process.There are nonlinear constraint relationships among many quality control points.The quality characteristic deviation will affect the final assembly quality of the product.With the rapid development of digital information technology,the front axle assembly process is gradually developing towards automation and intelligence.This dissertation aims to solve the problem of the influence of deviation transfer on the product quality in the front axle assembly process,and proposes a digital control model for quality control.A quality online based on ant colony optimization generalized regression neural network(ACO-GRNN)is designed.Optimize the model to achieve online control of the assembly process.The research content of this dissertation is as follows:(1)Explain the research status of assembly quality control and related fields at home and abroad,analyze the process flow and characteristics of front axle assembly,propose the quality control mode of digital twin drive,and introduce the key enablement of quality control application of front axle assembly process.technology.(2)Through the analysis of artificial neural network,GRNN is selected as the basic prediction model for online optimization of front axle assembly quality.The mathematical model of GRNN optimization improvement problem is constructed.The ant colony algorithm is merged with GRNN.The robustness and parallelism of ant colony algorithm are used to optimize the GRNN smoothing factor vector,and the ACO-GRNN model is designed.The feasibility of the improved generalized regression network prediction model based on ant colony algorithm is verified by simulation experiments.(3)Taking the assembly process control of a light truck front axle as an example,combined with the characteristics of the front axle assembly,built a software and hardware architecture,designed the database structure,and developed a digital twin-drive front axle assembly quality control system using the development tools.Finally,the practicality of the system is verified by the actual quality process control.
Keywords/Search Tags:assembly quality, process quality control, digital twinning, generalized regression neural network, ant colony optimization
PDF Full Text Request
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