Abstract

Part distortion is a common problem in the manufacturing life cycle and is defined as the deviation of part shape from original intent after being released from the fixture. Excessive distortion that occurs after machining creates the need for secondary corrective operations or even parts to be scrapped in extreme cases which costs money and time to the manufacturer. It was found through a literature review that a significant amount of research has been done on distortion prediction in aerospace components or materials (Aluminium and Titanium), however there was a lot less research on components and materials like stainless steel that are used in the civil nuclear industry. This paper aims to predict distortions induced during milling of 316L stainless steel through a Finite Element Model (FEM) and understand the effects of various parameters in order to optimise the process . A full factorial design of experiments was considered to review the effects of key process parameters and this was replicated both in modelling and real time experiments. A slot milling operation for a simple geometry was selected for this research. Along with cutting parameters (feed and spindle speed), clamping force of the fixture was also taken into account in simulations. The workpieces were scanned using a coordinate measuring machine (CMM) before and after machining in order to determine the distortion induced in the component. Hexagon’s MSC MARC was used to simulate the cutting process, which takes the material's heat treatment history in consideration. The software also uses the toolpath information during simulations which helps the user to achieve a more accurate model. Comparing simulated results against real time experiments, it was found that the initial residual stress balance in the material has a significant impact on distortions rather than the cutting and process parameters hence workpiece’s process history plays a critical role in distortion modelling. The main aim of this research is to develop a methodology of using FEM to predict part distortion in order to minimise or eliminate defects and successive corrective actions during machining of large high value components within the civil nuclear industry. In terms of future work, the team at Nuclear AMRC are looking to investigate various workpiece materials that are also widely used in the industry along with complex workpiece geometries and toolpaths to replicate the process on actual components.