Influence of process parameters on kerf geometry and surface roughness in Nd:YAG laser cutting of Al 6061T6 alloy sheet

Leone, Claudio; Genna, Silvio; Caggiano, Alessandra; Tagliaferri, V.; Molitierno, R.

doi:10.1007/s00170-016-8667-4

Cited by 42 publications

(14 citation statements)

References 29 publications

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“…Since thermal conductivity refers to the rate at which heat is removed from the cutting area, low thermal resistance increases heat dissipation, resulting in lower energy available to the machining and, consequently, higher energy consumption and loss of efficiency. Moreover, heat removal may result in cooling of the molten metal on the underside of the kerf, tapered edge and slag formation [18]. Furthermore, light reflective metals, such as aluminum alloys, may reduce the maximum cutting speed and require more power density to initiate the cut [5].…”

Section: Methodsmentioning

confidence: 99%

Experimental Investigation of Industrial Laser Cutting: The Effect of the Material Selection and the Process Parameters on the Kerf Quality

et al. 2020

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Laser beam cutting is a non-contact, production-flexible and highly productive technique that allows accurate profiling of a wide range of sheet materials. To these and further benefits, laser machining is increasingly being adopted by industry. This paper investigates the effect of material type, workpiece thickness, cutting speed and assistant gas pressure on cut quality for industrial-relevant applications using a CO2 laser. AlMg3 aluminum alloy, St37-2 low-carbon steel and AISI 304 stainless steel were selected to represent the most established materials in many industrial fields and gain insight into different processes (i.e., inert-assisted fusion cutting and oxygen cutting) and absorption behaviors with respect to CO2 laser wavelength. The aim was to enhance the understanding of the mechanisms through which laser cutting parameters and workpiece parameters interact in order to identify general criteria and well-optimized process parameters which guarantee the kerf quality. The quality of laser cut was analyzed in its basic terms: kerf geometry, surface roughness and cut edge quality. The experiments were performed by using a systematic experimental design approach based on Design of Experiments, and the results were validated via Analysis of Variance. Quality assessment was presented and discussed. The visual inspection of cut sections confirms good overall quality and limited presence of laser cut imperfections. The experimental investigation demonstrates that the different materials can be successfully processed within a wide range of the tested values. In addition, optimum cutting conditions which satisfy the straight requirement of the quality standard adopted are identified for each material. This study involves an analysis of both phenomenological and practical issues.

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Section: Methodsmentioning

confidence: 99%

Experimental Investigation of Industrial Laser Cutting: The Effect of the Material Selection and the Process Parameters on the Kerf Quality

et al. 2020

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“…Tadavani et al [14] reported that the laser cutting of the Inconel 718b superalloy improved the surface quality by 22%, in comparison to conventional machining. The interdependences between the Nd:YAG laser cutting control factors and the surface roughness and kerf geometry were investigated for the alloy Al 6061T6 [15]. The same responses were also analyzed for the pulsed CO 2 laser cutting in processing the composite material Al6061/Al2O3 [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Experimental Optimization of Nimonic 263 Laser Cutting Using a Particle Swarm Approach

Šibalija

Petronić²,

Milovanović

2019

Metals

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This paper presents an experimental study carried out on Nimonic 263 alloy sheets to determine the optimal combination of laser cutting control factors (assisted gas pressure, beam focus position, laser power, and cutting speed), with respect to multiple characteristics of the cut area. With the aim of designing laser cutting parameters that satisfy the specifications of multiple responses, an advanced multiresponse optimization methodology was used. After the processing of experimental data to develop the process measure using statistical methods, the functional relationship between cutting parameters and the process measure was determined by artificial neural networks (ANNs).Using the trained ANN model, particle swarm optimization (PSO) was employed to find the optimal values of laser cutting parameters. Since the effectiveness of PSO could be affected by its parameter tuning, the settings of PSO algorithm-specific parameters were analyzed in detail. The optimal laser cutting parameters proposed by PSO were implemented in the validation run, showing the superior cut characteristics produced by the optimized parameters and proving the efficacy of the suggested approach in practice. In particular, it is demonstrated that the quality of the Nimonic 263 cut area and the microstructure were significantly improved, as well as the mechanical characteristics.Parameters of the laser cutting process must be properly tuned in order to obtain the desired outputs. The laser power must be sufficient to enable the cutting; the cutting speed should be high enough to prevent the diffusion of heat in a material and to form a broad heat-affected zone (HAZ) [4]. The assisting gas is very important for producing a high-quality cut without a grate, since it does not permit molten material droplets' solidification onto the cut surface. The cutting speed must be balanced; if excessive speed is used the grate would remain, while, with a very low speed, the edge quality of the cut would be affected and a wide HAZ would form [5].The cutting control factors considered in this study are the assisting gas pressure, the position of the beam focus, the laser power, and the cutting speed. At the output, seven responses of the cut area are observed. Since the process is characterized by multiple parameters and responses, an advanced optimization methodology is needed to obtain the optimal cutting setting that satisfies the specifications for multiple, correlated responses. Simulated annealing (SA) and a genetic algorithm (GA) have been employed previously, and it has been demonstrated that SA outperformed GA in the proposed method [6]. Particle swarm optimization (PSO) is used in this study and benchmarked with SA in terms of the quality, i.e., the accuracy of the obtained optimum, the effects of the algorithm's parameters on the obtained optimum, and the convergence speed. Since metaheuristic algorithms must be adequately tuned to obtain the right solution, the setting of the major PSO algorithm's parameters is studied in detail to evaluate th...

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“…Thus, an increase of the absorbed energy by heat diffusion into the surrounding area of the worked material occurs, according to what observed in Refs. . The effect of the hatch distance is similar; when the Hd decreases, an increase of the released energy per unit area occurs; thus, Pd increases.…”

Section: Resultsmentioning

confidence: 83%

Multi‐response optimization of CFRP laser milling process based on response surface methodology

Genna

Tagliaferri

Papa

et al. 2017

Polymer Engineering & Sci

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In this study, ANalysis Of VAriance (ANOVA) and Response Surface Methodology were applied to characterize and optimize laser milling of Carbon Fiber Reinforced Polymer (CFRP) plates. The process was performed by means of a 30W Q-switched Yb:YAG fiber laser, working at the fundamental wavelength of 1064 nm. The machined material was a CFRP plate, 4 mm in thickness, obtained by autoclave cure. According to Design of Experiments (DoE) methodology and previous experiences, a Central Composite Design (CCD) was developed and applied. The investigated parameters were the scan speed, the pulse frequency, the number of repetitions of the geometric pattern and the hatch distance. The suitable milling conditions were obtained from the response surface model. The model allows to set the process parameters to obtain the desired depth with an error <3% and a MRR higher than 1.9 × 10−3g/s. POLYM. ENG. SCI., 57:595–605, 2017

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Influence of process parameters on kerf geometry and surface roughness in Nd:YAG laser cutting of Al 6061T6 alloy sheet

Cited by 42 publications

References 29 publications

Experimental Investigation of Industrial Laser Cutting: The Effect of the Material Selection and the Process Parameters on the Kerf Quality

Experimental Investigation of Industrial Laser Cutting: The Effect of the Material Selection and the Process Parameters on the Kerf Quality

Experimental Optimization of Nimonic 263 Laser Cutting Using a Particle Swarm Approach

Multi‐response optimization of CFRP laser milling process based on response surface methodology

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