Parametric Study and Multi-Criteria Optimization in Laser Directed Energy Deposition of 316L Stainless Steel

Abstract

Directed Energy Deposition (DED) is an additive manufacturing technique in which a heat source is used to generate a small pool of molten material while powder feedstock is fed into the melt pool to create tracks of raised material on the surface of a part. Given the appropriate process parameters for the chosen material system and process conditions, fully dense complex geometric features are able to be constructed. In order to generate a high quality clad, two main criteria must be met: sufficient bonding with the substrate with minimized dilution of the clad by the base material and minimal porosity. Track shape is a key indicator in determining the quality of the process. This paper evaluates the influence of several of the key processing parameters — laser power, scanning speed, and powder mass flowrate — on single-clad track morphology. An analysis of variance (ANOVA) is performed to evaluate the significance of the main input parameters and the interactions between multiple parameters. A second-order polynomial model is then fit to the data to allow for predictive modelling of track shape based on a set of inputs. Finally, a multi-criteria cost function is generated, and sequential quadratic programming is performed to solve the objective function. Through these operations, the correct combination of processing parameters can be selected in order to generate a cladded track with desirable geometric traits.

Laser metal deposition materials-process-performance characterization studies

“…One method to simplify the extensive nature of parametric studies is to first define the scope of the study by identifying the key processing parameters and focusing on the main effects. Kersten et al identified laser power, scanning speed, and powder mass flowrate as the key processing parameters in a study on optimization of laser DED of SS316L material [115]. Felix et al used a 2 3 -full factorial design to determine the optimal processing window, and used the optimal process parameters to determine the influence of alternative parameters on mechanical properties [116].…”