Geometry modeling of single track cladding deposited by high power diode laser with rectangular beam spot

Laser cladding of stainless-steel ball valves by a high-power diode laser source with a rectangular beam spot

Identification and qualification of temperature signal for monitoring and control in laser cladding

During the laser cladding process, thermal stresses are induced because of the high-energy input, high temperature gradient, fast cooling rate, and inconsistency of the clad-substrate material. The induced thermal stresses not only increase the crack tendency, but also influence the mechanical performance of the deposited layer. In this study, a three dimensional (3D) uncoupled thermo-mechanical finite element (FE) model was established to simulate the stress evolution of laser cladding of cobalt-based coatings on mild steel A36. The temperature field was simulated first and then used as transient thermal loading to simulate the stress evolution. Stress distributions for three cases: single track on a flat substrate, double-track on a flat substrate, and double-track on a cylindrical substrate, were investigated in detail. To check the accuracy of the simulation results, validation experiments were carried out using an 8-kW high-power direct diode laser. The thermocouples were used to monitor the temperature cycles at several marked points. The cross-sections of single and double tracks on a flat substrate obtained experimentally were compared with the simulation results. The residual stress on the clad was experimentally determined by an X-ray diffraction machine. The experimentally obtained data showed a significant consistency with the prediction results.

Magnesium is the lightest structural metal; therefore it has been used in a variety of industries such as automotive, aerospace, electronics and defense. Among different joining processes, laser welding is advantageous due to its low heat input, high depth-to-width weld ratio and good mechanical properties. In this study, a fiber laser is used to weld AZ31B magnesium alloy in a lap joint configuration. Pores were formed in the weld bead that are caused by a thick oxide layer existing on the surface of as-received AZ31B samples. Process parameters including laser power and welding speed are studied to determine their effects on pore formation and maximum lap-shear load of the weld bead. Hardness and tensile tests are carried out to reveal the mechanical properties of the weld bead. A regression analysis is performed that establishes a mathematical relation between the process parameters and the weld maximum lap-shear load. Three regression models are compared in order to determine their accuracy in prediction of the maximum lap-shear load and results revealed that the linear model could best predict the maximum lap-shear load by process parameters.

The present work deals with the application of a High Power Diode Laser (HPDL) to improve the mechanical properties of Al2O3 particle-reinforced Aluminum Matrix Composites (AMCs). An experimental plan in which laser power and interaction time were individually varied was carried out to evaluate the influence of both process parameters on the surface performance of the AMCs. In this respect, the evolution of their surface morphology was assessed by contact-gauge profilometry. Further samples were, then, analyzed by FIMEC micro-indentation test, depth-sensing load controlled scratch and wear test. Experimental findings show that mechanical and tribological proprieties of the laser treated substrates can be considerably improved, although in an operating range of process parameters rather narrow. Finally, an analytical model was proposed to correlate the wear performance of the AMCs investigated to their morphological and mechanical properties.The present work deals with the application of a High Power Diode Laser (HPDL) to improve the mechanical properties of Al2O3 particle-reinforced Aluminum Matrix Composites (AMCs). An experimental plan in which laser power and interaction time were individually varied was carried out to evaluate the influence of both process parameters on the surface performance of the AMCs. In this respect, the evolution of their surface morphology was assessed by contact-gauge profilometry. Further samples were, then, analyzed by FIMEC micro-indentation test, depth-sensing load controlled scratch and wear test. Experimental findings show that mechanical and tribological proprieties of the laser treated substrates can be considerably improved, although in an operating range of process parameters rather narrow. Finally, an analytical model was proposed to correlate the wear performance of the AMCs investigated to their morphological and mechanical properties.

Laser powder bed fusion (L-PBF) as an additive manufacturing process produces nearly fully dense nickel alloy 625 (IN625) parts with complex features. L-PBF generates surfaces and microstructure through directional solidification that can be controlled by scan strategies and selection of process parameters. This study provides experimental investigations on microstructure formation including sizes of cellular grains and growth directions of columnar grains on the nickel alloy 625 test coupons. The effects of process parameters including laser power, scan velocity, hatch distance, and scan strategy that produce various solidification cooling rates and thermal gradients during the process, which also contribute to resultant microstructure, have been analyzed. Optimization studies are conducted on several objectives to improve the productivity while controlling the process effects on the resultant microstructure using response surface regression, desirability functions, and multi-objective genetic algorithm optimization.

Laser cladding of Inconel 625-based composite coatings reinforced by porous chromium carbide particles

An experimental investigation on energy-effective additive manufacturing of aluminum parts via process parameter selection

<div class="section abstract"><div class="htmlview paragraph">Laser cladding is a method of material deposition through which a powdered or wire feedstock material is melted and consolidated by use of a laser to coat part of a substrate. Determining the parameters to fabricate the desired clad bead geometry for various configurations is problematic as it involves a significant investment of raw materials and time resources, and is challenging to develop a predictive model. The goal of this research is to develop an experimental methodology that minimizes the amount of data to be collected, and to develop a predictive model that is accurate, adaptable, and expandable. To develop the predictive model of the clad bead geometry, an integrated five-step approach is presented. From the experimental data, an artificial neural network model is developed along with multiple regression equations. A multi-layer perceptron network application is employed which uses a feed forward back propagation network architecture for the overall training process through external data consisting of input (process parameters) and target (shape parameters) values. Once a desired level of network training is achieved, simulation results (predicted shape parameters) are generated for a new input data set within the trained network boundary conditions. Furthermore, a comparison between different approaches to sensitivity analysis (clamping technique and sensitivity index) is presented to illustrate the uncertainty in the outputs of the model in relation to its inputs. Experimental validation is conducted by predicting specific process parameters for unique bead geometry. The predicted and resulting bead geometry values are seen within the 95th percentile accuracy.</div></div>

Fabrication of graphene/azobenzene-perylene diimide derivative modified electrochemical sensors for the dopamine detection based on full factorial experimental design

In tropical regions such as the Philippines, pineapple leaf fiber (PALF) is abundantly available as a low-cost and renewable source for industrial purposes. In this research, PALF was used as a reinforcing material for cement-based composites to open up further possibilities in waste management. Since natural fibers are not fully compatible with the matrix due to their hydrophilic nature, surface treatment is necessary to enhance the fiber-matrix bonding. Fibers were treated using sodium hydroxide (NaOH) with varying concentrations (4%, 8% and 12%) for 6-hr immersion time at room temperature. PALF was then added at varying content (1%, 4% and 7% w/w cement) to the concrete mixture with a design mix ratio of 2:1 (sand: cement) and a constant water-cement ratio of 0.55. The samples were mechanically characterized after 28 curing days following ASTM C209 and ASTM C473. Full factorial experimental design (FFED) was used to investigate the effects of alkali treatment and the fiber content on the mechanical strengths of the composite. Experimental methods, analysis of variance (ANOVA) and normality test were carried out to evaluate, analyze and validate the results. The best results for tensile strength parallel to the surface and flexural strength at 2.028 MPa and 1.495 kN, respectively, were observed at composites with 1% PALF with 4% NaOH. Meanwhile, composites with 1% PALF with 12% NaOH showed the best result for tensile strength perpendicular to the surface at 1.681 MPa. According to ANOVA results, only the model for the tensile strength perpendicular to the surface showed a curvilinear behavior (p-value=0.012). Results revealed that the factor with the most significant effect was the interaction of the fiber content and alkali treatment on the tensile strength parallel to the surface (p-value=0.000), tensile strength perpendicular to the surface (p-value=0.001) and flexural strength (p-value=0.001).

Surface profile is one of the foremost aspects to evaluate milling performance. Its generation mechanism is affected by a variety of factors such as tool geometry, runout values, and process parameters and thus still deserves further investigation. This paper aims to propose a unified method to study the surface generation mechanism and to predict the machining quality for variable pitch tools considering runout. First, a Floquet theory based algorithm is extended to analyze the machining stability and output the dynamic responses of the machining system. The resultant trajectories of cutting edges are obtained by kinematic synthesis of system vibrations, tool rotations, and machining feed. Next, both the surface location error (SLE) and the surface roughness are simultaneously extracted from the edge trajectories. A series of cutting tests are performed to validate the prediction results. Some new characteristics of the machined surface profile in terms of form errors and teeth marks are discovered and theoretically explained. Finally, the joint influences of tool geometry, runout values, and process parameters on the surface generation mechanism and quality are analyzed in detail with the proposed method.

The machining performance, such as carbon emission, dilution ratio rate, and powder utilization rate, can be improved by selecting appropriate process parameters in laser cladding. However, the importance evaluation of machining performance by users is often fuzzy. How to make a reasonable decision about laser cladding parameters under this condition? To resolve the problem, a multi-objective fuzzy decision-making approach of laser cladding parameters is proposed using support vector regression (SVR), multi-objective dragonfly algorithm (MODA), and fuzzy TOPSIS. Firstly, SVR is used to build the correlation model among laser cladding dilution rate, powder utilization rate, carbon emission, and process parameters. Secondly, MODA is applied to search non-dominated process parameters (non-dominated solution) based on the model. Finally, the non-dominated process parameters are sorted by fuzzy TOPSIS according to the user’s evaluation, the process parameter ranking first is the laser cladding process parameters that best meet the requirements of users, and the feasibility and effectiveness of the approach are verified via the experiments. The low-carbon decision-making problem of laser cladding parameters under the fuzzy evaluation can be well solved by the proposed approach.

Laser cladding is a novel additive manufacturing and surface treatment process associated with many interactive process parameters. Using the response surface method with a central composite design, a structured design of experiments approach was chosen to examine the influence of selected process parameters on the bead geometry and hardness for single-track laser-cladded specimens using AISI 420 stainless steel powder on a AISI 1018 substrate. In the present study, robust predictive models for hardness, bead aspect ratio, and wetting angle with the substrate were determined using multiple regression analysis. The geometry and hardness relationships to the process inputs were evaluated using F-statistics from the analysis of variance and compared by utilizing perturbation plots, 3D surface mapping, and contour plots. The highly coupled non-linear relationships are evident from these analyses, but this study revealed that the laser speed has the most significant effect on the bead microhardness and the powder feed rate was found to be the most significant parameter for these bead geometry parameters. The perturbation plots confirmed this sensitivity of those process parameters. This research study gives a guideline for the selection of appropriate process parameters for the laser cladding process to achieve desired hardness and bead geometry.

In this study, an experimental investigation on surface roughness and roundness in turning of Aluminium using solid carbide insert was examined. The effects of the feed, spindle speedand depth of cut on surface roughness were studied. To find out the optimum process parameter, Full Factorial design of experiments was employed. The influence of each process parameters were determined by the use of analysis of variance (ANOVA). The result shows that the selected turning parameters significantly influence the surface roundness and roughness of the machined component.