Combination Of Process Parameters Research Articles

Optimization on Stir Casting Process Parameters of Al7050/Nano-B4C Metal Matrix Composites

Aluminum matrix composites are widely employed in aerospace, military, automobile, and transport applications. The high-strength with low-weight materials are required to fulfill the requirement of high-performance applications. The low-weight materials are reinforced with hard reinforcements to obtain high-strength-to-weight properties for using high-performance applications. The process parameters of fabrication technique define the mechanical and tribological properties. Many types of optimization tools are used for optimizing the process parameters of fabrication method. In this research, the aluminum alloy 7050 and boron carbide are selected as matrix material and reinforcement material. The fabrication of Al7050/B4C composites is produced by the stir casting method. The optimization on stir casting process parameters is done by using the Taguchi approach. The L9 orthogonal array is chosen for this investigation. The chosen input stir casting process parameters are wt% B4C, stirring time (10, 15, and 20 min), stirring speed (300, 350, and 400 rpm), and melting temperature (700, 750, and 800°C). The microhardness is selected as a valuable response parameter for optimizing the stir casting process parameters. The influencing stir casting process parameter sequence is determined by using mean table. The influencing parameters of stir casting on microhardness are stirring speed, stirring time, wt% B4C, and melting temperature. The 9 wt% of boron carbide addition increases the microhardness, and it is higher than the other wt%. The optimum combination of input process parameter combination is 9 wt% boron carbide, 750°C melting temperature, 350 rpm stirring speed, and 15 min stirring time (A3B2C2D2). The percentage of microhardness value improvement is 20.3%.

DoE Approach to Setting Input Parameters for Digital 3D Printing of Concrete for Coarse Aggregates up to 8 mm.

This paper is primarily concerned with determining and assessing the properties of a cement-based composite material containing large particles of aggregate in digital manufacturing. The motivation is that mixtures with larger aggregate sizes offer benefits such as increased resistance to cracking, savings in other material components (such as Portland cement), and ultimately cost savings. Consequently, in the context of 3D Construction/Concrete Print technology (3DCP), these materials are environmentally friendly, unlike the fine-grained mixtures previously utilized. Prior to printing, these limits must be established within the virtual environment's process parameters in order to reduce the amount of waste produced. This study extends the existing research in the field of large-scale 3DCP by employing coarse aggregate (crushed coarse river stone) with a maximum particle size of 8 mm. The research focuses on inverse material characterization, with the primary goal of determining the optimal combination of three monitored process parameters-print speed, extrusion height, and extrusion width-that will maximize buildability. Design Of Experiment was used to cover all possible variations and reduce the number of required simulations. In particular, the Box-Behnken method was used for three factors and a central point. As a result, thirteen combinations of process parameters covering the area of interest were determined. Thirteen numerical simulations were conducted using the Abaqus software, and the outcomes were discussed.

Dimensional accuracy and impact resistance of 3D printed clay reinforced with scrap polymer powder

PurposeThe purpose of this paper is to give an insight into relevant aspects of 3D printing of clay paste enhanced with scrap polymer powder which have not been investigated by previous studies. Specifically, the geometrical features of the deposited lines, dimensional accuracy of benchmarks and mechanical properties of printed parts are investigated.Design/methodology/approachFirstly, the 3D printer is used to deposit lines of the paste under various combinations of material composition and process parameters. 3D scanning is used to measure their dimensional and geometrical errors. The results are elaborated through statistics to highlight the role of material and processing conditions. Then, four benchmark parts are printed using materials with different percentages of polymer powder. The parts are scanned after each step of the post-processing to quantify the effects of printing, drying and melting on dimensional accuracy. Finally, drop weight tests are carried out to investigate the impact resistance of specimens with different powder contents.FindingsIt is found that the quality of deposition varies with the printing speed, nozzle acceleration and material composition. Also, significant differences are observed at the ends of the lines. Materials with 10 Wt.% and 40 Wt.% of powder exhibit relevant shape variations due to the separation of phases. Accuracy analyses show significant deformations of parts at the green state due to material weight. This effect is more pronounced for higher powder contents. On the other hand, the polymer reduces shrinkage during drying. Furthermore, the impact test results showed that the polymer caused a large increase in impact resistance as compared to pure clay. Nonetheless, a decrease is observed for 40 Wt.% due to the higher amount of porosities.Research limitations/implicationsThe results of this study advance the knowledge on the 3D printing of clay paste reinforced with a scrap polymer powder. This offers a new opportunity to reuse leftover powders from powder bed fusion processes. The findings presented here are expected to foster the adoption of this technique reducing the amount of waste powder disposed of by additive manufacturing companies.Originality/valueThis study offers some important insights into the relations between process conditions and the geometry of the deposited lines. This is of practical relevance to toolpath planning. The dimensional analyses allow for understanding the role of each post-processing step on the dimensional error. Also, the comparison with previous findings highlights the role of part dimensions. The present research explores, for the first time, the impact resistance of parts produced by this technology. The observed enhancement of this property with respect to pure clay may open new opportunities for the application of this manufacturing process.

Design Criteria for the Construction of Energy Storage Salt Cavern Considering Economic Benefits and Resource Utilization

Underground salt caverns have been widely used for oil and gas storage and have attracted increasing attention. The construction design of salt caverns is directly related to the final storage capacity, economic benefits, and resource utilization. However, due to the numerous combinations of multi-stage process parameters involved in the construction design, it is difficult to optimize them individually through indoor experiments and numerical simulations. In this regard, this paper attempts to put forward the basic principles of cavern construction design criteria with economic benefits and resource utilization as indicators. Firstly, 1258 groups of cavern construction process parameters were randomly generated under certain basic rules, including inner tube depth, outer tube depth, oil pad depth, duration, and water injection flow rate, for five direct leaching stages. Then, the cavern capacity, economic benefit, and rock salt resource utilization corresponding to these process parameters were obtained through batch processing using single-well salt cavern leaching simulation software (SSCLS). Finally, the influence laws of the distance between the inner tube and oil pad and lifting heights, and the rates of the inner tube and oil pad on the expected economic benefits and salt resource utilization, are discussed. In the actual project, it is recommended to increase the distance between the inner tube and the oil pad, increase the ratio of oil pad lifting height to duration, and use the appropriate lifting height to obtain greater expected revenue and resource utilization. This work will improve the efficiency and scientificity of cavern construction design, which is of great significance in guiding the construction and design for energy storage in salt caverns.

Multi-objective optimization of process parameters of laser cladding 15-5PH alloy powder based on gray-fuzzy taguchi approach

Laser cladding is a new surface treatment technology that is widely used for surface modification of metal parts, and the high quality of the surface geometry of the cladding layer can save a lot of resources for the company. To obtain high quality of the clad layer, the L25 Taguchi experiment of laser cladding process parameters was designed to laser-clad a single 15-5PH layer on the surface of 45# steel; the effect of process parameters on the surface morphology and dilution rate of the coating was determined by ANOVA; the optimal combination of process parameters was obtained by combining gray correlation and fuzzy inference system method. The ANOVA results show that the scanning speed among the laser cladding process parameters plays a key role in obtaining the best superposition of the four geometrical features of the cladding layer simultaneously; With the optimization objectives of larger clad width and height, smaller clad depth, and 30% dilution rate, the optimal combination of process parameters, (P: 600W, V: 500 mm min−1, F −1 : 1.3 r min−1), obtained based on the Gray-fuzzy Taguchi Approach, was compared and analyzed to find a significant improvement in the geometric quality characteristics of the optimized clad layer. The analysis of microstructure, physical phase, hardness, wear resistance and corrosion resistance showed that the 15-5PH clad layer was able to effectively enhance the surface properties of the 12Cr13 substrate. The optimization method proposed in this study can solve the problem of parameter optimization in the industrial multi-parameter and multi-response processes.

Optimization and Improvement of the Projection Welding of Nut Based on Regression Analysis

Since it has the advantages of high production efficiency, no shunting effects, and the ability to arrange solder joints on narrow locations without the limitation of point distance, projection welding of nut has been widely used in the automotive industry. This paper presents a new welding quality prediction and analysis framework by using regression analysis techniques. The relationship between the welding parameters (welding time, welding current and electrode force) and the Pull-out load of the M6 welded square nut and the 1.5 mm thick pickled hot-rolled steel was obtained by multiple nonlinear regression analysis. The influence and interaction of welding parameters on the Pull-out load are discussed. Using this regression model, a better combination of process parameters can be obtained. The mechanical properties, microstructure and microhardness of welded joints were also investigated.

Optimisation and analysis of jet impingement erosion behaviour of composite titanium based ENi-P coated naval steel (AH36)

ABSTRACT This paper aims to address the impact of jet impingement on nano titanium-based ENi-P composite coatings deposited through electroless deposition on AH36 steel through Taguchi design of experiments. L9 Taguchi DOE was utilised to synthesise nine coatings by varying the four process parameter combinations suggested by the technique. Jet impingement combined with AFS 50/70 quartz sand erosion experimental run was conducted on the acidic, alkaline and nine ENi-P-TiO2 composite coatings administered through a waterjet erosion tester. The influence of C14-SB type Zwitterionic surfactant and nano TiO2 were discussed along with temperature and bath pH to achieve better resistance against the jet impingement on the surface of the coatings. Analysis of variance, the S/N ratio, and interaction plots were used to determine the optimal bath input parameters to deliver the least weight loss from the erosive environment and identify its use in the marine environment. The proposed optimal coating was validated using a confirmation test, and the weight loss was reduced by more than 35% compared to the initial condition parameter (A2B2C2D2). In addition to mechanical properties, the quality of the deposits was analysed through morphological and chemical composition probed through scanning electron microscope, energy dispersive X-Ray analysis and powder X-Ray diffraction methods. As a result, the Composite Modified Resilience (CMR) value of ENi-P-TiO2 optimal coating was improved by over 41.17%, and its corresponding weight loss was reduced to 35% compared to the initial condition. This experiment paves the way for further study on electroless deposits and their characteristics on AH36 steel generally used for shipbuilding in commercial ships, naval, and marine associated defence applications.

Effect of nanoparticle on mechanical properties of activated tungsten gas welding of austenite stainless steel 316L and optimization of process parameters

Abstract Austenite stainless steel 316L was developed to improve corrosion resistance and is widely used in automobile components, thermal power plants, and pressure vessels due to their superior toughness and intergranular corrosion resistance. The austenite stainless steel 316L has a low carbon content of 0.03%, which helps in minimizing harmful carbide precipitation during welding. The joint strength of welded joints is poor unless proper care is taken. As a result, an attempt was made to use an activated Tungsten Inert Gas (A-TIG) welding procedure to improve the joint strength of butt welded joints of austenitic stainless steel 316L. The process parameters such as current, the volume of flow, and filler diameter were chosen in the study and generated an L 9 design matrix using MINI Tab software. The welded joints were prepared as per the design matrix using the activated flux of aluminum oxide nano powder as per the combination of process parameters. The mechanical tests such as tensile strength, hardness, and impact strength were evaluated and microstructural evaluation of welded joints was also assessed. The input parameters were optimized for better tensile strength of joints using Taguchi S/N analysis. It is found from the optimization that the highest ultimate tensile strength of 690.40 MPa was obtained at a current of 90 A, shielding gas flow of 13 l min–1, and filler material diameter of 2.5 mm. The model was also validated by conducting experiments.

Intelligent assessment of quality characteristics of miscanthus fiber-reinforced polypropylene for sustainable products development

This study aims at determining the optimal material and process parameters that will maximize the quality characteristics of miscanthus fiber-reinforced polypropylene (MFRPP) composite. Taguchi L16 was utilized in the design of experiment and larger-the-better signal-to-noise ratio was used in the analysis of the impact strength of MFRPP. Optimal combination of material and process parameters and the main effects were determined, and the significant variables were identified using analysis of variance. Artificial neural network (ANN) and extreme learning machine (ELM) were utilized on the Taguchi experimental data and used in the prediction of the impact strength of MFRPP. The results showed the optimum impact strength occurred at 25 wt% miscanthus fiber loading. The results of the predictions made revealed that both ANN and ELM are very efficient in predicting the impact strength of MFRPP as shown by the relative errors when compared with the experimental data. Both the performance metrics assessments and the quality of prediction show that ELM is a better machine learning technique than ANN. The high impact strength of MFRPP composite is a confirmation that MFRPP is a very useful material for industrial applications.

An Interactive Analysis of Influencing Factors on the Separation Performance of the Screw Press

In order to optimize the separation performance of the screw press and enable its water removal rate and production to meet the production requirements, the influencing rule of the interactive effect of multi-factor parameters on its separation performance was studied by numerical simulation and experimental means. The internal flow field of the screw press was simulated by Fluent software. The rotation speed of the screw axis, back pressure of the slag outlet, and initial water content were taken as influencing factors, and the water removal rate and production were taken as objective functions. The Box–Behnken method was used to analyze the influencing rules of the interactive factors on the water removal rate and production. The results show that the significant factors affecting the water removal rate of the screw press are in the following order: initial water content > back pressure > rotation speed. The significant factors affecting screw press production are in the following order: rotation speed > back pressure > initial water content. The optimal combination of process parameters for the screw press is an initial water content of 55%, a screw axis rotation speed of 30 r/min, and a 5 kPa back pressure at the slag outlet. The water removal rate of 48.9% and production of 234.2 kg/d were obtained.

A Fast Prediction Model for Liquid Metal Transfer Modes during the Wire Arc Additive Manufacturing Process

The liquid metal transfer mode in wire arc additive manufacturing (WAAM), plays an important role in determining the build quality. In this study, a fast prediction model based on the Young-Laplace equation, momentum equation, and energy conservation, is proposed, to identify the metal transfer modes, including droplet, liquid bridge, and wire stubbing, for a given combination of process parameters. To close the proposed model, high-fidelity numerical simulations are applied, to obtain the necessary inputs required by the former. The proposed model's accuracy and effectiveness are validated by using experimental data and high-fidelity simulation results. It is proved that the model can effectively predict the transition from liquid bridge, to droplet and wire stubbing modes. In addition, its errors in dripping frequency and liquid bridge height range from 6% to 18%. Moreover, the process parameter windows about transitions of liquid transfer modes have been established based on the model, considering wire feed speed, travel speed, heat source power, and material parameters. The proposed model is expected to serve as a powerful tool for the guidance of process parameter optimization, to achieve high-quality builds.

Vibration quality evaluation of reinforced concrete using energy transfer model

Vibration is an important step to ensure the compactness of reinforced concrete. In this study, the energy transfer model is firstly proposed based on the working mechanism of the internal vibrator and vibration energy theory to evaluate the vibration quality, and the reliability of the model is verified by the experiment of sinking ball. In addition, the optimal combinations of process parameters are obtained. The worse the fluidity of concrete and the larger the aggregate proportion, the faster the energy attenuation in concrete, but the total energy absorbed by concrete and the energy transfer efficiency of the vibrator increase. The overall efficiency is greater than 57% and the highest average efficiency is 66.1%. The rebar not only accelerates the energy attenuation rate but also reduces the effective energy in the concrete. In the experiments, the average energy consumption rates of rebar are 28.5%, 57.3% and 70.9% with the reinforcement spacing of 20, 10 and 5 cm respectively. The proposed model provides a new method to evaluate the vibration quality, which contributes to dealing with unqualified areas in time and providing reliable process parameters for vibrating construction.

Process optimization of line patterns in extreme ultraviolet lithography using machine learning and a simulated annealing algorithm.

Resolution, line edge/width roughness, and sensitivity (RLS) are critical indicators for evaluating the imaging performance of resists. As the technology node gradually shrinks, stricter indicator control is required for high-resolution imaging. However, current research can improve only part of the RLS indicators of resists for line patterns, and it is difficult to improve the overall imaging performance of resists in extreme ultraviolet lithography. Here, we report a lithographic process optimization system of line patterns, where RLS models are first established by adopting a machine learning method, and then these models are optimized using a simulated annealing algorithm. Finally, the process parameter combination with optimal imaging quality of line patterns can be obtained. This system can control resist RLS indicators, and it exhibits high optimization accuracy, which facilitates the reduction of process optimization time and cost and accelerates the development of the lithography process.

Formability and surface finish analysis of AA-6061 sheets in multipoint incremental forming process

ABSTRACT Incremental sheet metal forming (ISF) is` a versatile manufacturing process carried out without the help of a die and is one of the most sought-after research areas. This research work provides a deep investigation into the impact of input parameters on formability and surface roughness. A Multipoint Incremental Forming (MPIF) tool is used in this work. Through MPIF, better surface finish and improved formability can be achieved. Also, the time required for metal forming can be reduced. The main goal in this work is to obtain improved formability and excellent surface finish in the MPIF process. Response Surface Methodology (RSM) and Multi-Objective Genetic Algorithm (MOGA) are used in this work to find the optimum combination of process parameters, including sheet thickness, vertical step depth, speed and feed rate to obtain improved formability and surface finish.

ANN for design and fabrication of ENi-P-nano TiO2 coatings on AH36 steel

Designing optimal ENi-P-nano TiO2 with higher surface hardness is time-consuming and expensive. Thus, this study is aims to develop the optimal optimiser-based ANN model to forcast Vickers hardness for newer process parametric combinations and find the ideal combination before manufacture. Consequently, three ANN model were devised using ADAM, AdaMax, and RMSprop optimisers with identical data set for training and testing. mean Squared Error (MSE) and R 2 values were used to compare and assess their performance. Rectified Linear Unit (ReLU) is used to provide nonlinearity to the neural network's output since the activation function affects ANN model performance. The study also highlights hyperparameter setting's impact on optimiser performance. The ADAM-based ANN model was determined as optimal design through comparing the predicted and experimental Vickers hardness for the unknown combinations using Taguchi DOE. In addition, FESEM and XRD micrographs confirmed the optimal coating's morphology and phases. This study results shown the compatibility of utilising ANN-based prediction models for ENi-P-nanoTiO2 coating design and prediction, however future research much incoporates more process parameters and their level ranges.

Laser repair of tungsten damaged by fusion-relevant plasmas

As a hotspot, the ITER tungsten divertor receives both extreme plasmas and considerable research attention. The projection is that certain plasma-induced defects in tungsten are inevitable under the scheduled ITER operation. Although the exact consequences of such defects on the divertor lifetime are unclear currently, approaches to combat them are desirable but remain limited. Here, we develop the idea of healing such defects through laser remelting. With a suitable combination of processing parameters—such as laser power, scan speed, and preheating temperature—the remelted (pristine) tungsten surface was nearly crack-free. Revealed by electron backscatter diffraction (EBSD) analysis, the remelted microstructure resembled that of fully recrystallized tungsten. Furthermore, the linear relationship between the normalized melt pool depth and the normalized enthalpy of the surface was established, the former of which indicates the healing depth. Lastly, proof-of-principle experiments were performed on damaged tungsten specimens containing respectively blisters, nanostructure fuzz, and fatigue cracks, yielding promising healing effects. Based on additional considerations of the plasma exposure behavior of laser remelted tungsten and deployment of the laser repair system, we conclude that the laser repair approach is compatible with the ITER operation plan.

A New Approach to Empirical Optimization of Laser Powder Bed Fusion Process for Ti6Al4V Parts

Optimization of all the process parameters for laser powder bed fusion (L-PBF), considering the effects of individual parameters on Ti6Al4V fabricated parts, can be complex and challenging. Therefore, for the first time, the effects of three main variable process parameters (laser power, scan speed, and hatch spacing) on three outcomes parameters (surface roughness, bulk porosity, and production rate of parts) were studied in this work. Then, the combination of above-mentioned process parameters in the form of volumetric energy density (VED) was investigated in order to establish a practical method for optimization of process parameters for making Ti6Al4V parts with the desired quality targets, i.e., the smoothest surface, the lowest bulk porosity and a higher production rate. It was revealed that although VED is a reliable metric for the optimization of process parameters, some thresholds and ranges should be considered for all three parameters of laser power, scan speed, and hatch spacing. It was demonstrated that by employing an optimum laser power of 180 W or 270 W and changing the scan speed and hatch spacing to keep VED in the range of 50-100 J/mm3, fabrication of samples with micro-roughness Ra < 10 µm and bulk porosity less than 0.15% is achievable. In addition, the surface of the L-PBF fabricated parts may appear in two categories of surface morphology; wavy surface classified “meso-roughness topography” and non-wavy surface termed “micro-roughness”. Since there was not any correlation between the value of roughness of samples with meso-rough surface and their bulk porosity, and besides, their process parameters were far from optimized parameters, the samples with meso-rough surface were not included in the final results. However, it was realized in the samples with micro-rough surfaces, the value of their micro-roughness could accurately indicate the porosity content of Ti6Al4V samples.

The Use of Sacrificial Graphite-like Coating to Improve Fusion Efficiency of Copper in Selective Laser Melting

Thin and ultrathin carbon films reduce the laser energy required for copper powder fusion in selective laser melting (SLM). The low absorption of infrared (IR) radiation and its excellent thermal conductivity leads to an intricate combination of processing parameters to obtain high-quality printed parts in SLM. Two carbon-based sacrificial thin films were deposited onto copper to facilitate light absorption into the copper substrates. Graphite-like (3.5 µm) and ultra-thin (25 nm) amorphous carbon films were deposited by aerosol spraying and direct current magnetron sputtering, respectively. The melting was analyzed for several IR (1.06 µm) laser powers in order to observe the coating influence on the energy absorption. Scanning electron microscopy showed the topography and cross-section of the thermally affected area, electron backscatter diffraction provided the surface chemical composition of the films, and glow-discharge optical emission spectroscopy (GDOES) allowed the tracking of the in-deep chemical composition of the 3D printed parts using carbon film-covered copper. Ultra-thin films of a few tens of nanometers could reduce fusion energy by about 40%, enhanced by interferences phenomena. Despite the lower energy required, the melting maintained good quality and high wettability when using top carbon coatings. A copper part was SLM printed and associated with 25 nm of carbon deposition between two copper layers. The chemical composition analysis demonstrated that the carbon was intrinsically removed during the fusion process, preserving the high purity of the copper part.

The Microstructure and Properties of Ni-Si-La2O3 Coatings Deposited on 304 Stainless Steel by Microwave Cladding

In this investigation, microwave radiation was used alongside a combination of Ni powder, Si powder, and La2O3 (Lanthanum oxide) powder to create surface cladding on SS-304 steel. To complete the microwave cladding process, 900 W at 2.45 GHz was used for 120 s. "Response surface methodology (RSM)" was utilized to attain the optimal combination of microwave cladding process parameters. The surface hardness of the cladding samples was taken as a response. The optimal combination of microwave cladding process parameters was found to be Si (wt.%) of 19.28, a skin depth of 4.57 µm, irradiation time of 118 s, and La2O3 (wt.%) of 11 to achieve a surface hardness of 287.25 HV. Experimental surface hardness at the corresponding microwave-cladding-process parameters was found to be 279 HV. The hardness of SS-304 was improved by about 32.85% at the optimum combination of microwave cladding process parameters. The SEM and optical microscopic images showed the presence of Si, Ni, and La2O3 particles. SEM images of the "cladding layer and surface" showed the "uniform cladding layer" with "fewer dark pixels" (yielding higher homogeneity). Higher homogeneity reduced the dimensional deviation in the developed cladding surface. XRD of the cladded surface showed the presence of FeNi, Ni2Si, FeNi3, NiSi2, Ni3C, NiC, and La2O3 phases. The "wear rate and coefficient of friction" of the developed cladded surface with 69.72% Ni, 19.28% Si, and 11% La2O3 particles were found to be 0.00367 mm3/m and 0.312, respectively. "Few dark spots" were observed on the "corroded surface". These "dark spots" displayed "some corrosion (corrosion weight loss 0.49 mg)" in a "3.5 wt.% NaCl environment".

Information-rich quality controls prediction model based on non-destructive analysis for porosity determination of AISI H13 produced by electron beam melting

The number of materials processed via additive manufacturing (AM) technologies has rapidly increased over the past decade. As of these emerging technologies, electron beam powder bed fusion (EB-PBF) process is becoming an enabling technology to manufacture complex-shaped components made of thermal-cracking sensitive materials, such as AISI H13 hot-work tool steel. In this process, a proper combination of process parameters should be employed to produce dense parts. Therefore, one of the first steps in the EB-PBF part production is to perform the process parameter optimization procedure. However, the conventional procedure that includes the image analysis of the cross-section of several as-built samples is time-consuming and costly. Hence, a new model is introduced in this work to find the best combination of EB-PBF process parameters concisely and cost-effectively. A correlation between the surface topography, the internal porosity, and the process parameters is established. The correlation between the internal porosity and the melting process parameters has been described by a high robust model (R2adj = 0.91) as well as the correlation of topography parameters and melting process parameters (R2adj = 0.77–0.96). Finally, a robust and information-rich prediction model for evaluating the internal porosity is proposed (R2adj = 0.95) based on in situ surface topography characterization and process parameters. The information-rich prediction model allows obtaining more robust and representative model, yielding an improvement of about 4% with respect to the process parameter-based model. The model is experimentally validated showing adequate performances, with a RMSE of 2% on the predicted porosity. This result can support process and quality control designers in optimizing resource usage towards zero-defect manufacturing by reducing scraps and waste from destructive quality controls and reworks.