P. F. Bariani

A combined DFMA and TRIZ approach to the simplification of product structure

Abstract In order to tackle the problem of part count reduction more effectively, an approach that combines the design for manufacture and assembly (DFMA) method with the theory of inventive problem solving (TRIZ) is presented in this paper. This new approach was developed by merging the common characteristics and connecting the complementary aspects of the two methods, which were then applied to the redesign of a satellite antenna.

Determination of Yield Locus of Sheet Metal at Elevated Temperatures: A Novel Concept for Experimental Set-Up

The constant demand of increasing performances and safety in vehicle industry has led significant innovations in the materials used in sheet metal forming processes. In particular, multiphase steels and lightweight alloys have known higher and higher importance, thanks to the development of new stamping processes at elevated temperatures, which guarantee, at the same time, better formability, lower springback and more accurate micro-structural control in the formed sheets. With respect to these aspects, the correct design and optimization of the new processes cannot prescind of the mechanical characterization of materials in biaxial stress conditions, especially when it strongly varies according to the stress and temperature. In this paper, a novel experimental set-up is presented for determining the in-plane yield locus of sheet metals at elevated temperatures. A cruciform specimen, whose geometry was optimized by numerical simulation, is used for the study of the yield locus in the range of biaxial tensile stresses. The test machine concept is based on punch-wedge mechanism, which uses the vertical movement of the press for the deformation of the specimen along two perpendicular axes. In the first part of the paper, the optimization of the cruciform specimen by thermo-mechanical FE analyses is outlined. Details on the experimental set-up are then given with the description of the apparatus, the measurement of plastic strains and the heating system for tests at elevated temperatures.

Modelling Nimonic 80A rheological behaviour through artificial neural networks

Abstract In this paper neural networks are utilized to represent the rheological behaviour of nickel-base superalloys under hot forging conditions. A feedforward back-propagation neural network has been trained and tested on rheological data, obtained from hot compression experiments, performed under single- and multi-step deformation conditions, both at constant and varying strain rates. The good agreement between experimental and calculated flow curves shows that a properly trained neural network can be successfully employed in representing a material response to hot forging cycles.

Transformation Plasticity in 42CD4 Steel

This paper deals with the experimental investigation of transformation plasticity of the 42CD4 steel and, mainly, of phases in which austenite can transform during cooling. The aim was to generate data to be implemented in the numerical model of the cooling phase which follows hot forming operations as it was recognized that the accuracy of numerical predictions is sensitively influenced by this parameter. The calibrated numerical model was then validated through on field-measurements and laboratory physical simulations of cooling.