Abstract
To increase the reliability and accuracy of tolerance design, more and more research works are considering not only orientation and position deviations; they are also forming errors in tolerance modeling. As a direct cause of form errors in industrial mass production, the processing features of the machining system degrade over time. Under the Industry 4.0 paradigm, an assembly tolerance design method based on Skin Model Shape is proposed to take the effect of degrading processing features into consideration. A continuous-time multi-dimensional Markov process is trained through maximum likelihood estimation based on the nodal sampling point set on the machined surface. Degradation of the machined surface is modeled based on the joint probability distribution of nodal displacements. Assembly force constraints and assembly entity constraints are applied to spatial assembly simulations. Tolerance synthesis takes the manufacturing cost and assembling probability as design objectives. A design example of the rotary feed component in a five-axis machine tool is proposed for explanation and verification.
Highlights
Under the innovative concept of Industry 4.0, automated and digitized systems in smart factories could enable the real-time integration and analysis of massive amounts of data by the use of electronics and information technologies. This would result in a more flexible and optimized manufacturing process [1,2,3]. This theory points to the improvement of intelligent solutions in the tolerance design of mechanical products, including the replacement of empiricism with knowledge-intensive and data-based processes
The intention of this paper is to propose a solution to assembly tolerance design problems considering processing feature degradation
Repetitive experiments and variated models are applied in the design process due stochastic characteristic of the multivariate Gaussian process (MGP)
Summary
Under the innovative concept of Industry 4.0, automated and digitized systems in smart factories could enable the real-time integration and analysis of massive amounts of data by the use of electronics and information technologies. It was verified to be of great help in improving the diagnostic performance of an empirical classification system involving the degradation of mechanical systems These applications of stochastic processes in manufacturing modeling have shown great potential in simulating the tolerance of a large branch of mechanical products in mass production based on measuring data. The intention of this paper is to propose a solution to assembly tolerance design problems considering processing feature degradation These problems are commonly encountered in the practical production of equipment manufacturing in industries such as high-precision computer numerical control machining, aeronautics, and astronautics. Estimation and verification of the efficiency of the proposed method are illustrated through an example of the transmission shaft on a five-axis high-precision machine tool (VTM200F)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
