Henrik Borgström

Optimising grey iron powder compacts

Abstract The grey iron microstructure Fe–2C–2Si powder based compact is tailored by different kinds of in situ and post sintering processing. This has been achieved by combining thermodynamic and kinetics modelling of microstructure development with sintering and controlled heat treatment experiments of tensile test specimens die compacted at 600 MPa. Applying optimised sintering conditions led to a grey iron like microstructure with 95% relative sintered density. Sinter hardening the compacts led to 500 MPa in yield strength and 600 MPa in ultimate tensile strength in combination with ductile fracture. Quenched and tempered condition showed the same strength values, but combined with brittle fracture due to martensitic structure. Pore rounding and partial pore filling by graphite were obtained by austenising isothermal hold during the cooling of the sintering cycle.

Liquid Phase Sintering of Ferrous Powder Metallurgical Materials

The properties of powder metallurgical, PM, components are dependent on that the dilemma of full density and suitable microstructure is resolved. Whilst it is often possible to achieve full density, it may or may not coincide with a suitable microstructure. Therefore, this thesis has addressed key aspects in the PM processing chain in the viewpoint of achieving a suitable microstructure after sintering. These key aspects have included Properties of Ferrous Powder, Green Body Consolidation, Sintering and Post-sintering Heat Treatments. To do this two ferrous alloy systems have been considered. A pre-alloyed gas atomized high speed steel, HSS, system that has either been loose powder sintered or sintered after a forming process called starch consolidation. Starch consolidation concerns the manufacture of a porous green body by mixing an aqueous-slurry consisting of spherical powder, starch, dispersant and thickener. After drying, these green bodies have been liquid phase sintered in different atmospheres to manipulate the microstructure locally at the surface or globally. The other considered system has concerned die-pressed grey iron powder mixtures consisting of lubricant coated iron powder and ferrosilicon as well as liquid forming additive in powder form for some mixtures. Common to both systems is that the sintering temperature needs to be accurate in order to achieve a successful microstructure. Furthermore, if the heating rate and the cooling rate are controlled for the grey iron powder mixture system, a microstructure with bainite and nodular graphite leads to yield and ultimate tensile strength of 500 and 600 MPa, respectively. For the HSS system conventional heat treatments were not attempted, but the experimental results and thermodynamic modelling results show that the carbon content in the matrix needs to be around 0.6 wt-% C if the desired microstructure of martensite and carbide is to be obtained. This work has demonstrated through model experiments and X-ray photoelectron analysis that the nitrogen pressure, p, in the atmosphere and the bulk nitrogen content CN is related through CN = constant√p if the surface oxide has been reduced first.

Variation of Tensile Properties of High Silicon Ductile Iron

The casting processes are characterized by complex relationships between predictors and responses. It is the fundamental understanding of these complex relationships that often involves hundreds of factors, which improves quality without losing productivity and raising cost. In this work, cast solid solution strengthened ferritic spheroidal graphite irons GJS-500-14 and GJS-600-10 (EN 1563:2012) have been evaluated. These materials offer stronger components with good machinability owing to their even hardness properties. In this case the predictors are chemical composition, gating layout, foundry set-up, testing procedure and equipment etc. and the responses are the tensile properties (Rp0.2, Rm, A5). Here 200 tensile specimens compiled from industrial foundry melts from over 30 years of research have created a state-of-the-art platform for statistical engineering in order to perform Exploratory Data Analysis (EDA) and data visualization. This statistical platform has provided new insight on how foundries should treat complex relationships between predictors and responses in order to identify sources of variation and interaction effects.