The manufacturing research has been focusing on the improvement of product performance and lightweight design. The synergic effects between material properties and manufacturing solutions have been considered, extensively. Specifically, joining techniques have been developing with the aim to propose new suitable solutions considering dissimilarities in the properties of the materials that have to be combined. Setting of new manufacturing routes is, therefore, a demanding task. In this direction, there are several methods available in the scientific literature that are focused on sensitivity analysis or optimization/minimization techniques to reduce the necessary attempts or to find a solution/correlation among big data. In this work, the goal of obtaining high joint efficiency between Aluminum and Polycarbonate sheets by the Friction Spot Joining process is considered as a case study. This process must face two main issues, i.e., the mechanical, physical and chemical compatibilities between the parts and the integrity protection of the polymeric sheet near the joining area. The process parameters influences were analysed using numerical simulations performed by a commercial FE code. The number of executed analyses was reduced with a planned DoE. From these results, the Code2Vect algorithm was employed with the aim to visualize, efficiently, high-dimensional data and to evaluate the influences of some identified parameters on the process answer. Finally, a transfer function involving the input and output quantities of interest was derived in a compact representation by a Newton Raphson minimization technique.

A novel sensitivity analysis on friction spot joining process performed on aluminumpolycarbonate sheets by simulation

Serratore G.;Gagliardi F.
;
Filice L.;Chinesta F.
2020

Abstract

The manufacturing research has been focusing on the improvement of product performance and lightweight design. The synergic effects between material properties and manufacturing solutions have been considered, extensively. Specifically, joining techniques have been developing with the aim to propose new suitable solutions considering dissimilarities in the properties of the materials that have to be combined. Setting of new manufacturing routes is, therefore, a demanding task. In this direction, there are several methods available in the scientific literature that are focused on sensitivity analysis or optimization/minimization techniques to reduce the necessary attempts or to find a solution/correlation among big data. In this work, the goal of obtaining high joint efficiency between Aluminum and Polycarbonate sheets by the Friction Spot Joining process is considered as a case study. This process must face two main issues, i.e., the mechanical, physical and chemical compatibilities between the parts and the integrity protection of the polymeric sheet near the joining area. The process parameters influences were analysed using numerical simulations performed by a commercial FE code. The number of executed analyses was reduced with a planned DoE. From these results, the Code2Vect algorithm was employed with the aim to visualize, efficiently, high-dimensional data and to evaluate the influences of some identified parameters on the process answer. Finally, a transfer function involving the input and output quantities of interest was derived in a compact representation by a Newton Raphson minimization technique.
Code2Vect
Dissimilar materials
Friction spot joining
Machine learning
Mechanical fastening
Newton-Raphson
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/313253
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