Production Cost Optimization Research And Production Auxiliary System Design Of Mounted Bearing Assembly

With the emergence and rapid development of Industry 4.0,intelligent and digital technologies are becoming more and more mature.For bearing units with housings,traditional processing methods have problems such as high production costs,low measurement efficiency,low matching efficiency,and serious parts backlog and waste,which are not suitable for the current large-scale,low-cost,high-quality component production.model.Therefore,manufacturers of bearing components with housings have an urgent need for intelligent and digital production transformation.In response to this demand for enterprise development,this paper conducts research on the production cost optimization and production auxiliary systems of bearing units with housings,and mainly completes the following research contents:(1)Improve the cost-tolerance model according to the concept of soft standardization to optimize the cost of component processing.Based on actual working conditions and production data,the existing cost-tolerance model was improved,and a cost-tolerance model suitable to produce bearing units with housings was established by combining factors such as tolerance range,processing cost and production batch.And the effectiveness is verified by experiments.(2)A component parameter acquisition algorithm based on the combination of point cloud processing algorithm and fitting algorithm is proposed.The point cloud processing algorithm adopts the bilateral filtering method to perform noise reduction processing on the collected 3D point cloud data,to filter out noise and irrelevant information,to obtain more accurate component point cloud data,and to ensure the credibility of subsequent algorithms.The fitting algorithm is based on the processed point cloud data and calculates and fits the component parameters based on the weighted total least squares method,which replaces traditional manual measurement and improves production efficiency.(3)Through the comparison and analysis of various algorithms,select the optimal algorithm to design the specific algorithm for the system.This paper considers many factors such as feasibility,accuracy,efficiency,and implementation difficulty of different algorithms.Through comparative experiments,a multi-objective matching algorithm based on genetic algorithm is finally used to design an intelligent matching module.This algorithm has low time and space complexity,can replace manual matching,and improve matching quality and efficiency.(4)This paper designs and tests the production auxiliary system software.First,choose a suitable programming language,design the framework of the program,and ensure the stability and reliability of the system.Secondly,the interface design is carried out according to the functional requirements of the system and the user’s usage habits to ensure that the user’s operation is simple and the interface is beautiful.Finally,the software is tested to ensure the stability of the software.The production auxiliary system of bearing units designed in this paper is comprehensively optimized for factors such as production cost,production efficiency and scrap rate,and provides a low-cost and high-quality production mode transformation idea for bearing unit manufacturers.It also provides reference and reference to produce bearing components and the development of related fields,and has certain theoretical reference significance and practical application value.