Hybrid prediction-optimization approaches for maximizing parts density in SLM of Ti6Al4V titanium alloy

Abstract

It is well known that the processing parameters of selective laser melting (SLM) highly influence mechanical and physical properties of the manufactured parts. Also, the energy density is insufficient to detect the process window for producing full dense components. In fact, parts produced with the same energy density but different combinations of parameters may present different properties even under the microstructural viewpoint. In this context, the need to assess the influence of the process parameters and to select the best parameters set able to optimize the final properties of SLM parts has been capturing the attention of both academics and practitioners. In this paper different hybrid prediction-optimization approaches for maximizing the relative density of Ti6Al4V SLM manufactured parts are proposed. An extended design of experiments involving six process parameters has been configured for constructing two surrogate models based on response surface methodology (RSM) and artificial neural network (ANN), respectively. The optimization phase has been performed by means of evolutionary computations. To this end, three nature-inspired metaheuristic algorithms have been integrated with the prediction modelling structures. A series of experimental tests has been carried out to validate the results from the proposed hybrid optimization procedures. Also, a sensitivity analysis based on the results from the analysis of variance was executed to evaluate the influence of the processing parameter and their reciprocal interactions on the part porosity.

A new control parameter to predict micro-warping-induced job failure in LPBF of TI6AL4V titanium alloy

“…Concerning the energy density, Gong et al [23] and Song et al [24] showed that the optimal process parameters are bounded by a minimum and a maximum value of uniform energy density. In addition to this, previous experimental tests by some of the authors [25] have pointed out that, even for uniform energy density values within the optimum zone indicated in the literature, micro-warping phenomena occur in some cases, leading to failure of the printing process.…”

Optimization of Laser Cutting Parameters for PMMA Using Metaheuristic Algorithms

“…Chaki and Ghosal developed [55] a hybrid ANN and simulated annealing (SA) model to predict cut quality during laser cutting of mild steel plates. ANN and RSM methods were established to predict the density of SLM fabricated parts in Ti6Al4V materials in [56]. PSO, self-adaptive harmony search, and GA were integrated into these models and the impacts of laser processing parameters and their interactions on the part porosity were assessed.…”

Gyártási paraméterek változtatásának hatása additívan gyártott titán alkatrészek mechanikai tulajdonságaira

“…Elsayed és szerzőtársai befolyásoló tényezőként említették a fémpor szemcsék méretét és morfológiáját, valamint a lézersugárzás által bevitt hőmennyiséget [6]. Costa és társai hat gyártási paraméter (lézersugár teljesítmény, szkennelési sebesség, pásztázási vonalak távolsága, építési irány, szkennelési stratégia, rétegvastagság) hatását vizsgálták SLM technológiával gyártott Ti-6Al-4V alkatrészek tömörségére [7]. A szakirodalom vizsgálata után megállapítható, hogy fontos megvizsgálni azt, hogy az igényeket, milyen gyártási paraméterekkel lehet legjobban teljesíteni.…”