The increasing interest from the engineering community to manufacture near-net-shape components in order to improve the material utilisation and cost competitiveness at a product level as well as the product characteristics drives research towards a deeper understanding of cold forming technologies. The herein research investigated the shear forming process applied to 304L stainless steel and Inconel 718 and intended to facilitate an improved exploitation route of the technology into component applications by characterising it geometrically and metallurgically. First, the identification and impact of the key processing variables (KPVs) on the geometry and surface roughness of the component when applied to 304L stainless steel and Inconel 718 were studied through experimental work using a systematic approach and then compared to the literature (triangulation). A design of experiments approach was undertaken on an industrial scale machine and predictive numerical models were established by statistical analysis to allow optimisation of the process capabilities within component tolerances.The feeds and speeds were revealed to have a significant impact across the different thicknesses and geometries.Secondly, the microstructure and texture of 304L stainless steel and Inconel 718 post shear forming were studied using scanning electron microscopy coupled with electron back-scattered diffraction. Elongated grains following the roller path were observed as well as shear bands, which are characteristic of high local deformation.The grain size was found to be dependent on the cone angle and an increased hardness was noted. The primary mechanism of deformation was identified as simple shear. The statistical analysis of the texture of the Inconel 718 parts after a two-step aging treatment revealed a significant link between the torsion component B and the cone angle, initial thickness, and their interaction. The research and findings were considered in light of the current literature and recommendations and areas for future research were given.
|Date of Award||4 Jun 2019|
- University Of Strathclyde
|Sponsors||University of Strathclyde & Rolls-Royce|
|Supervisor||Paul Blackwell (Supervisor) & Andrzej Rosochowski (Supervisor)|