A physics-driven model for the remote laser welding and development of process capability space framework for the selection of robust process parameters

Abstract

New environmental regulations and policies have transformed the manufacturing industry to develop capabilities for high uptake of structures which are lighter, stronger, and cost-effective. This transformation has expedited the development of new lightweight materials and joining technologies to support the high-volume manufacturing. The use of Aluminium alloys for lightweight manufacturing has increased in the past decades in the automotive industry from 35 kg to around 200 kg per vehicle. Welding of high-strength aluminium alloys is challenging due to high hot cracking susceptibility due to the rupture of the molten metal film at the grain boundaries during the solidification process. There are two possibilities to reduce the susceptibility to hot cracking: (i) Optimisation of process parameters to influence solidification conditions to promote generating equiaxed grain structure in the fusion zone; and (ii) Welding of dissimilar aluminium alloys and optimising the concentration of the weld. It is crucial to have shortened lead time for the rapid development and deployment of new joining processes for the new lightweight materials. Current methodologies for the selection of robust process parameters provide limited performance due to (i) a limited understanding of the interaction of the material with the advancement in joining technologies; (ii) extensive dependence on manual expertise for the selection of process parameters based on a trial and error method; (iii) time intensive high fidelity models to survey the parameters space resulting in limited industrial applicability and scalability, hence constitute a significant barrier in quick selection of robust process parameters to decrease the lead time. The proposed framework is based on three methodologies which explore Remote Laser Welding: (i) developing physics-based simulations to establish the relationship between material's behaviour with the varying process parameters; (ii) incorporating a sequential modelling approach to balance between high accuracy and computation time to survey the parameter space; and (iii) development of the process capability space for the quick selection of robust process parameters. Three physical phenomena are considered in the development of numerical modelling which are (i) heat transfer, (ii) fluid flow and (iii) diffusion to investigate the effect of process parameters on the weld thermal cycle, solidification parameters and solute intermixing layer during laser welding of high-strength aluminium alloys all of which provides a qualitative relationship to the grain morphology. The governing physical phenomena are decoupled sequentially, and process performance indicators are estimated based on the governing phenomena. At each step, the process capability space is defined over the parameters space based on the constraints specific to the current physical phenomena. The process capability space is defined by the constraints based on the process performance indicators. The process capability space is refined at each step (sequential modelling) based on the requirements of downstream processes. The numerical model is developed using COMSOL Multiphysics software which is further verified experimentally with measurements specific to each physical phenomenon. The proposed modelling framework decreases the total computation time to survey parameter space by 55% and the developed model shows good accuracy with an error of 3.1%