Methodical procedure of virtual manufacturing for analysing WAAM distortion along with experimental verification

Abstract

This paper deals with a principal development of virtual manufacturing (VM) procedure to predict substrate distortion induced by Wire Arc Additive Manufacturing (WAAM) process. In this procedure, a hollow shape is designed in a thin-walled form made of stainless steel. The procedure starts with geometrical modelling of WAAM component consisting of twenty-five deposited layers with austenitic stainless-steel wire SS316L as feedstock and SS304 as substrate material. The hollow shape is modelled based on simplified rectangular mesh geometry with identical specimen dimensions during the experiment. Material model to be defined can be retrieved directly from a database or by conducting a basic experiment to obtain the evolution of material composition, characterized using Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray (EDX) analysis, and generated using advanced modelling software JMATPRO for creating new properties including the flow curves. Further, a coupled thermomechanical solution is adopted, including phase-change phenomena defined in latent heat, whereby temperature history due to successive layer deposition is simulated by coupling the heat transfer and mechanical analysis. Transient thermal distribution is calibrated from an experiment obtained from thermocouple analysis at two reference measurement locations. New heat transfer coefficients are to be adjusted to reflect actual temperature change. As the following procedure prior to simulation execution, a sensitivity analysis was conducted to find the optimal number of elements or mesh size towards temperature distribution. The last procedure executes the thermomechanical numerical simulation and analysis the post-processing results. Based on all aspects in VM procedures and boundary conditions, WAAM distortion is verified using a robotic welding system equipped with a pulsed power source. The experimental substrate distortion is measured at various points before and after the process. It can be concluded based on the adjusted model and experimental verification that using nonlinear numerical computation, the prediction of substrate distortion with evolved material property of component yields far better result which has the relative error less than 11% in a comparison to database material which has 22%, almost doubled the inaccuracy.