In order to study the effect of laser power density on the microstructure and properties of laser remelting 304 stainless steel, the temperature field and phase transition model of pulsed laser remelting stainless steel were established, and the temperature distribution and phase transition zone boundary during laser remelting were analyzed. The effects of laser power density on the microstructure, element distribution, hardness and corrosion resistance of the remelting layer on the surface of stainless steel were studied. The simulation and experimental results show that with the increase of laser power density, the surface temperature of stainless-steel increases gradually, and the surface quality of remelted layer becomes better and then worse. After laser remelting of 304 stainless steel, the hardness of the remelting layer is higher than that of the substrate, the self-corrosion potential shifts to the right, the self-corrosion current density decreases, and the corrosion resistance increases. Laser remelting technology is beneficial to improve the comprehensive properties of 304 stainless steel surface.
The present study presents comprehensive analytical solutions for the thermoelastic response of semi-infinite media subjected to exponentially decaying volumetric heat sources with two distinct temporal profiles, namely exponential decay and rectangular step pulses. The governing coupled thermoelastic equations are nondimensionalized using characteristic thermal diffusion scales, revealing the fundamental parameter gamma = c(1) (2)/ alpha(2) delta(2) that governs the relative importance of elastic wave propagation to thermal diffusion. Closed-form solutions are derived for both temperature and stress fields using Laplace transform techniques, yielding expressions involving complementary error functions with complex arguments. The stress solutions are decomposed into five distinct wave propagation, and causal elastic response. A novel compact operator formulation is introduced for the step pulse solution, demonstrating the principle of superposition and revealing the self-similar nature of the thermoelastic problem. The solutions show that maximum thermal stresses do not necessarily coincide with maximum temperatures in space or time, particularly for rapid heating cases where elastic waves propagate ahead of the thermal front. The analytical results provide fundamental insights into the selection of optimal pulse parameters for applications ranging from laser material processing to thermal barrier coating evaluation, where control of thermal stress is critically important for preventing material damage.
To conduct an in-depth investigation into the impact of laser welding process parameters on the welding surface quality and welding deformation, qualitative laws summarising the influence of welding parameters, proposing optimal combinations of welding process parameters, multidimensional experimental analysis is used to analyse 304 stainless steel sheet. Firstly, the effects of the main laser welding parameters are initially determined by simulation, then a multidimensional experimental matrix was established, encompassing a variety of methodologies, such as single-factor, single-factor targeted, orthogonal, repeatability. In the experiments, the weld surface quality and weld distortion were assessed using a high magnification CCD camera and a six-jointed hand-held measuring arm, respectively. Through simulation and process experiments, the qualitative laws of welding speed, welding power and defocusing amount on welding surface quality and welding deformation are summarised, and the effect of welding power is further subdivided into the separate laws of peak welding power and duty cycle. The implications of this multidimensional experimental analysis are significant for intelligent upgrading and transformation of tasks within mechanical manufacturing enterprises. This meticulous experimental analyses and qualitative research contributes to the refinement and enhancement of previously vague empirical rules, thereby providing a clearer and more coherent understanding of qualitative patterns. This study is a foundational step towards facilitating the intelligent transformation of relevant enterprises and workshops.
Laser drilling can provide precise holes in hard-to-machine materials, yet its environmental assessment in terms of life cycle, is often confined to beam-on energy. This consideration of narrow metric, in general, omits significant contributors to processes such as cooling and vacuum loads, warm-up and idle power, assist-gas production, and rework that substantially influence overall sustainability of the manufacturing process. The current study develops a gate-to-gate life-cycle assessment (LCA) for laser drilling of AISI 304 steel and Inconel 625 alloy. A 500 W Nd:YAG laser drilling process was assessed using a foreground inventory that includes laser electricity, vacuum-pump electricity with measured duty factor, shielding-gas (argon) consumption, and upstream impacts of removed material. The relevant parameters considered and tested in the analysis were drilled hole size, electricity mix (fossil fuel-based vs renewable), and laser substitution (Nd:YAG laser vs CO2 laser). Findings demonstrates that for AISI 304 steel, operational energy dominates global warming potential (GWP), whereas for Inconel 625 alloy the material term becomes comparable or dominant across toxicity, resource scarcity, and land-use categories. Argon production is a major contributor to ionizing radiation and water consumption, indicating that gas management is a high-leverage opportunity for impact reduction. Increasing hole volume raises all impacts, the relative rise is larger for Inconel, notably for mineral resource scarcity and toxicity, reflecting Nickel, Molybdenum, and Tantalum intensive supply chains. At constant geometry, substituting a CO2 laser yields larger GWP reductions (36-38%) than a grid switch to renewable (13-14%), while the cleaner energy grid slightly increases ionizing-radiation and water use midpoints (CO2 substitution reduces water use by similar to 27%). The LCA therefore connects operational parameters (pulse and scan settings, gas flow, pump duty cycles, and equipment selection) and upstream procurement choices (electricity mix and assist-gas selection) to per-hole impacts, providing a documented foundation for co-optimizing quality, productivity, and environmental performance in industrial drilling of AISI 304 steel and Inconel 625 alloy.
In order to improve the surface properties of 45 steel, laser cladding technology was used to prepare CoCrNi composite coatings with different TiC content on the surface of 45 steel using TiC powder and CoCrNi alloy powder as cladding materials. The phase composition and microstructure of the coating were studied by X-ray diffractometer (XRD), scanning electron microscope (SEM) and metallographic microscope (OM). The microhardness, friction and wear properties and corrosion resistance of the coating were measured. The results show that the phase of the coating was mainly composed of FCC solid solution phase when the content of TiC was 0%similar to 5%. The phase of the coating was composed of TiC phase and FCC solid solution phase when the content of TiC was 15%similar to 25%. TiC particles in the shape of irregular polygons, spheres and cross petals were uniformly dispersed in the coating. Due to the second phase strengthening effects of TiC, the average microhardness of the coating reaches the maximum value 401.5 HV0.3, which is about twice the hardness of the substrate 45 steel, and the minimum weight loss is 2.6 mg when the content of TiC was 25%. The wear form of the coating is mainly abrasive wear. With the increase of TiC content, the corrosion resistance of the coating decreases and then increases. The corrosion resistance of the coating is obviously better than 45 steel. When the content of TiC is 25%, the corrosion resistance of the coating is the best, the self-corrosion potential is -479.08 mV, the self-corrosion current density is 1.16x10(-4) mA.cm(-2). TiC/CoCrNi composite coatings possess excellent corrosion resistance and wear resistance, which can effectively improve the surface properties of 45 steel.
Results of pathology along with camera-fitted digital microscopy is very vital to find the physiological and statistical impacts of analytes such as Cefixime, Ciprofloxacin, and Cobalamin for five concentrations (0 mM, 50 mM, 100 mM, 150 mM, and 200 mM). The Count of WBCs attenuates under Cobalamin with an attenuation factor of 4.1 & times;10(3) /& micro;L, retards under Cefixime, and attenuates under Ciprofloxacin. RBCs count retardes from 3.48 & times;106 to 3.20 & times;10(6) /& micro;L. Increases under Cefixime and retarders under Ciprofloxacin. Platelet cells show attenuation of 11 & times;10(3) /& micro;L and 4x10(3) / & micro;L under Cobalamin and Ciprofloxacin respectively while show retardation of 15x10(3)/& micro;L. Compared to Cefixime, Cobalamin exhibits attenuation against WBCs and PLTs and retardation in RBCs and HGB. In contrast, Cefixime shows attenuation against WBCs and PLTs as well as retardation in RBCs, MCV, and HCT. The size of WBCs under Cefixime and Ciprofloxacin remains nearly constant, but under Cobalamin attenuates considerably. Cobalamin upsets WBCs significantly more at higher doses than Cefixime or Ciprofloxacin, which essentially have no effect on WBC size. Retardation or attenuation starts at 100mM. In comparison to Cefixime and Ciprofloxacin, Cobalamin exhibits a faster rate of fluctuation in blood components and indices, according to pathological data.
By adding Al and Ti elements to FeCoNiCrMn-based high-entropy alloys (HEAs) and using laser cladding technology, a surface coating with good formation and high wear resistance was successfully prepared on the surface of 45# steel. Based on advanced analytical methods, the coating formation quality, microstructure, and wear mechanisms under different laser powers were systematically analyzed. The increase in laser power promotes the improvement of formation quality. The coating matrix phase is a dual-phase structure of BCC (body-centered cubic) and FCC (face-centered cubic). The addition of Al and Ti atoms with large atomic radii causes lattice distortion, which promotes phase transformation. The solid-solution strengthening of the BCC phase, as well as the secondphase strengthening and dispersion strengthening provided by TiC particles, enhance the hardness and wear resistance of the coatings.
To further enhance the corrosion resistance of 304 stainless steel, laser surface remelting technology is used for surface treatment. Orthogonal optimization design methodology is used to optimize the parameters of laser surface remelting of 304 stainless steel. Analysis of variance and extreme variance based on L16(45) orthogonal experiments were used to obtain the effects of different parameters on the corrosion resistance of 304 stainless steel. The results show that the parameters affecting the corrosion resistance are as folter > laser scanning speed > laser power. The optimal parameters of orthogonal optimization are laser power 3 W, laser spot diameter 30 mu m, laser repetition rate 70 kHz, laser scanning speed 40 mm & centerdot;s(-1) and laser scanning spacing 10 mu m. The surface corrosion resistance of stainless steel prepared by laser surface remelting with optimized parameters is improved, and the selfcorrosion current density is increased by 8.59% compared with that of the substrate. This paper reveals the influence of 5 laser parameters on the corrosion resistance of stainless steel, which provides a reference for further improving the corrosion resistance of 304 stainless steel.
The influence of machining environment on the processing quality of silicon nitride ceramics during nanosecond laser machining was investigated. Under controlled laser parameters, the process performance of two environments-ambient air and water-jet assistance-was systematically compared. Experimental results demonstrate that nanosecond laser processing in air produced grooves with a depth of 110.36 & micro;m and a width of 10.27 & micro;m on the silicon nitride surface. Under water-assisted conditions, the grooves fabricated by nanosecond laser processing exhibited a depth of 80.13 & micro;m and a width of 5.76 & micro;m. Moreover, it effectively eliminates surface recast layers and microcracks. In water-jet-assisted nanosecond laser processing of silicon nitride, the effective cooling provided by the water jet significantly reduces heat accumulation in the machining zone. The impact of the water jet promotes the rapid expulsion of molten material from the groove and facilitates the timely removal of byproducts, thereby enhancing machining quality. This study provides critical process optimization insights for precision laser machining of hard and brittle materials, demonstrating that water-jet-assisted technology effectively suppresses thermally induced defects commonly associated with conventional laser processing.
To investigate the effects of S-shaped and spiral scanning modes on selective laser melting temperature, a selective laser melting model was established. The temperature field distribution of the S-shaped scanning method and spiral scanning method in SLM is simulated. Compared with the S-shaped scanning method, the laser in spiral scanning is scanned from the outside to the inside, which has a continuous preheating effect on the inside. The internal slows down the external cooling rate through heat conduction, which makes the overall temperature field distribution of the parts more uniform, reduces the temperature gradient and stress concentration. The research results are beneficial for the selection and optimization of selective laser melting parameters
Laser surface treatment offers considerable advantages over other conventional techniques in terms of precision of operation, fast processing, and low-cost. In laser surface processing, laser pulse intensity distribution, laser pulse frequency, and scanning speed play major roles on the maximum temperature increase at the substrate surface. Consequently, investigation into thermal response of the solid substrate to the laser heating pulse with different configuration of laser pulse parameter, laser scanning speed, and laser pulse frequency becomes essential. In the present study, numerical simulation is performed to explore thermal response of a polycarbonate sheet to the pulsed laser scanning. The laser parameters considered include laser pulse frequency, laser beam shape at the irradiated spot, and laser scanning velocity. Transient temperature distributions are computed using COMSOL software. The maps of maximum temperature and the shape of the heat affected regions are predicted in line with the consideration of the threshold glass temperature of polycarbonate (Tg = 420 K). The effects of varying each parameter is compared, and scaling trends are proposed. The present study provides useful insight into design and selection of laser treatment parameters for controlled surface modification of polymeric materials without exhaustive trial-and-error.
Metal Additive Manufacturing (AM) using Selective LASER Melting (SLM) technologies are catalyzing a new industrial revolution, significantly transforming the manufacturing landscape. Notably, tools used in conventional processes like Electric Discharge Machining (EDM) can be efficiently produced by SLM. This research focuses on evaluating the performance of SS316L EDM tools fabricated by using SLM, optimizing critical control parameters like Laser power and scanning speed while keeping layer height and hatch distance constant. Post-manufacturing of SLM technology metal 3D printed EDM Tools, a comprehensive geometrical and surface roughness analysis of fabricated parts was conducted. Minimizing the surface roughness of EDM tools is critical for achieving superior machining results. Therefore, research also emphasizes on analyzing tool wear and surface roughness, alongside optimizing process parameters using the Taguchi method, Analysis of Variance (ANOVA) and Multi-Decision-Making techniques like TOPSIS. Furthermore, the study develops an Artificial Neural Network (ANN) model to predict the surface roughness of EDM tools produced by Metal AM. A detailed literature review covers key process parameters influencing Selective Laser Melting (SLM) technology, the material characteristics of SS316L, and the experimental framework for manufacturing EDM tools. The ANN was trained and tested on data obtained from Metal AM-produced EDM tools, yielding a near-perfect fit, demonstrating the model's effectiveness.
Laser-assisted metal-to-polymer (LAMP) joining is a thermal bonding process that uses laser energy to create hybrid metal-polymer structures through adhesion and mechanical interlocking, without the need for adhesives or fasteners. In this study, the LAMP joining of AISI 1018 lowcarbon steel and PETG (polyethylene terephthalate glycol) is investigated using a 1 kW fiber laser welding system. The effects of key process parameters, such as laser power, scanning speed, and surface texturing, on joint strength are analyzed. Three surface textures, namely transverse, longitudinal, and box pattern grooves, are applied to the steel surface, and the joint strength of textured samples is compared with non-textured joints. Bonding quality at the polymer-metal interface is examined, revealing strong adhesion and a mixed-mode fracture. An empirical model is developed to correlate laser power, scanning speed, and textured patterns with joint strength, validated through regression analysis and analysis of variance. The results show that textured patterns, particularly the box texture, improve joint strength. Additionally, laser power is found to be the most influential factor on joint strength, followed by scanning speed and the types of texturing used. The study also highlights the optimal process parameters, with maximum joint strength achieved at high laser power (600 W), high scanning speed (20 mm/s), and box texture.
The investigation of the influence of irradiation path in the laser forming process is a crucial aspect that opens a way to explore the diverse phenomena involved in the irradiated sheet that led to manufacture complex forms. This paper discusses the influence of angular segment irradiating path on the deformational behaviors of aluminium Al6061-T6 sheets under laser forming process. In order to describe the irradiations along angular segments, mathematical correlations have been established. The validity of the constructed numerical model is assessed by experimental tests that are conducted within the specified operating parameters. Computed predictions concerning evolutions of the temperature, stress, strain and displacement fields in the irradiated sheets are analyzed in order to facilitate a more comprehensive understanding and study of the underlying phenomena occurring in the angular segment forming process. The results indicated that the final bending deflection increases with an increase in the segment angle of the heating line. It is observed that the final shape of the formed aluminium alloy sheet is affected by the angular segment irradiating path. The mechanical properties of the formed sheet are studied experimentally under a benchmark process condition. The findings of the present research will be useful in real laser forming application to manufacture three-dimensional complex shapes.
In this study, the marking on samples by using laser marking on the acrylic sheet is examined. The input experiments factors such as Laser power (20-60 W), Laser speed (200-600 mm/s), and Focal Plane Position (five conditions) are selected. These characteristics determine the output of 17 laser marks designed by the design of experiments (DOE) methodology. In this stage, the Response Surface Method (RSM) is used to find the optimization and statistical modeling of the laser marking process. top section width, Cross section Width, and cross section diameter are responses showing the process's quality. By applying a 50W CO2 laser, the acrylic sheet can achieve the highest values for the Top part of the Specification. By optimizing the laser marking process, a higher degree of process control can be achieved by considering the relative importance of each input parameter. Recent findings indicate that this approach can lead to a 15% improvement in accuracy, a result with significant implications for industrial applications.
For efficient fabrication of microchannels and micro-features on metals, it is essential to accurately predict the performance measures such as the microchannel feature size and material removal during nanosecond laser-based micromachining of metals. The laser based thermal ablation of metal occurs mainly due to the vaporization, melt flow and phase explosion. However, scant literature is noted on considering these aspects together to develop a realistic numerical model. This paper presents the development of a non-linear thermo-physical model of nanosecond pulse laser ablation of stainless steel (SS316L) which mainly incorporates the effects of vaporization, melt flow and phase explosion. Moreover, the developed model considers the realistic assumptions such as Gaussian distribution of heat flux, surface reflectivity of the material based on the measured roughness of the work sample surface and the temperature dependent material properties. The computed results were found in good agreement with the experimental results.
SLM has great potential in aerospace and medical devices. However, there are many factors affecting the performance of SLM molded parts, and it would be time-consuming and costly to investigate them only by experimental methods. In this paper, the influence of forming parameters on the hardness of formed parts is evaluated by machine learning methods, and a prediction model of forming parameters based on artificial neural networks is developed and the accuracy of the prediction model is verified by experiments.
This study concerns a detailed characterization of microstructure and evaluation of corrosion resistance (in Hank's solution) of austenitic stainless steel (AISI 316L) substrate fabricated by laser direct energy deposition (LDED) using a 6 kW fibre coupled diode laser under the optimum process parameters of 600 W applied power, 5 mm/s scan speed and 50 g/ min powder flow rate. LDED with optimum parameters leads to the refinement of microstructure with cellular morphology of predominantly austenitic grains. The corrosion test in Hank's solution shows almost an order of magnitude lower corrosion rate than commercially available wrought AISI 316L. Similarly, immersion in simulated body fluid shows higher kinetics of calcium phosphate deposition on LDED AISI 316L than that on the same steel in wrought condition.
Laser cutting is a high-precision manufacturing technique that relies on the stability of a focused laser beam and an assist gas to produce intricate geometries with minimal mechanical stress. However, fluctuations in beam parameters and gas flow can destabilize the keyhole, leading to defects such as kerf-width deviation, dross attachment, heat-affected zone irregularities, and micro-cracks. Conventional rule-based inspection methods image thresholding and statistical process control suffer from static thresholds and limited adaptability, yielding segmentation accuracies below 85%. This paper presents a comprehensive framework for AI-driven defect detection and quality control in laser cutting. We integrate multi modal in-process sensing (optical, thermal, acoustic) with post-process machine vision, and employ state-ofthe-art convolutional neural networks (U-Net, Mask R-CNN) and hybrid CNN-Transformer architectures for pixel-level segmentation and classification of defects. Self-and unsupervised learning strategies reduce annotation overhead by modelling the manifold of "good" cuts and flagging deviations in real time. Our edge-AI implementation achieves inference times under 30 ms, enabling closed-loop feedback to CNC controllers that adjust process parameters on the fly. Benchmarking on publicly available metal surface datasets demonstrates detection accuracies > 95%, Intersection over Union scores > 0.80, and F1-scores > 0.90. We further analyse the hardware and software requirements for industrial deployment, quantify the cost-benefit, and address integration challenges with MES/SCADA systems. Finally, we outline future directions miniaturized edge-AI modules, Deep Learning based AI diagnostics, and digital-twin coupling to realize zero-defect, self-optimizing laser-cutting cells in smart factories.
Directed energy deposition (DED) with wire as the deposited material has shown great potential for additive manufacturing of thin-wall geometry. It offers higher material deposition efficiency, minimal material wastage, and a cleaner process environment using wire as a feed material. Micro-wires' use got less attention to understanding the manufacturing of high aspect ratio beads, primarily by increasing the height compared to width. So, this study aims to investigate the single-layer deposited samples of stainless steel 316L micro-wire. Processing conditions for continuous wave (CW) and pulsed wave (PW) laser emission investigated for single-layer deposition regarding surface roughness, bead geometry, microstructure, and microhardness. The single layer deposition with an aspect ratio up to 1 was produced successfully, where layer height was between 0.6 and 0.7 mm. The results show that using micro-wire and PW laser yields lower heat affected zone (HAZ) close to powder-bed additive manufacturing (AM) processes.
