Automatic Characterization of the Material Removal Rate in Laser Manufacturing of TiAl6V4 and Inconel 718

2009 ◽  
Author(s):  
Leonardo Orazi ◽  
Gabriele Cuccolini ◽  
Giovanni Tani
Keyword(s):  
Material Removal Rate ◽  
Inconel 718 ◽  
Material Removal ◽  
Numerical Models ◽  
Removal Rate ◽  
Industrial Applications ◽  
Milling Process ◽  
Laser Source ◽  
Automated Method ◽  
Laser Milling

In this paper a system for the automatic determination of the material removal rate during laser milling process is presented. “Laser milling” can be defined as an engraving process with a strictly controlled penetration depth. In industrial applications, when a new material have to be machined or a change in the system set-up occur the user has to perform a time-consuming experimental campaign in order to determine the correlation between the material removal rate and the process parameters. In these cases the numerical models present some limits due to the elevated calculation time requested to simulate the laser milling of industrial features. In the proposed system, based on a regression model approach, the empirical coefficients, that provide the material removal rate, are automatically generated by a specific software according to the different materials that have to be processed. A description of the automated method and the results obtained in engraving TiAl6V4 and Inconel 718 superalloy with a fiber laser are presented. The system can be adapted to every combination of material/laser source.

scholarly journals An integrated approach for the modelling of silicon carbide components laser milling process

2021 ◽  
Author(s):  
Claudio Leone ◽  
Silvio Genna ◽  
Vincenzo Tagliaferri
Keyword(s):  
Silicon Carbide ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Integrated Approach ◽  
Milling Process ◽  
Roughness Parameters ◽  
Laser Milling ◽  
Pulsed Fiber Laser

AbstractThe paper deals with characterisation and modelling of laser milling process on silicon carbide hard ceramic. To this end, a Yb:YAG pulsed fiber laser was adopted to mill silicon carbide bars. Square pockets, 5×5 mm2 in plane dimension, were machined at the maximum nominal average power (30W), under different laser process parameters: pulse frequency, scan speed, hatching distance, repetitions and scanning strategy. After machining, the achieved depth and the roughness parameters were measured by way of digital microscopy and 3D surface profiling, respectively. In addition, the material removal rate was calculated as the ratio between the removed volume/process time. Analysis of variance (ANOVA) was adopted to assess the effect of the process parameters on the achieved depth, the material removal rate (MRR) and roughness parameters, while response surface methodology (RSM) and artificial neuronal networks (ANNs) were adopted to model the process behaviours. Results show that both RSM and ANNs fault in MRR and RSm roughness parameters modelling. Thus, an integrated approach was developed to overcome the issue; the approach is based on the use of the RSM model to obtain a hybrid Training dataset for the ANNs. The results show that the approach can allow improvement in model accuracy.

scholarly journals An Integrated Approach for the Modelling of Silicon Carbide Components Laser Milling Process

2021 ◽  
Author(s):  
Claudio Leone ◽  
Silvio Genna ◽  
Vincenzo Tagliaferri
Keyword(s):  
Silicon Carbide ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Integrated Approach ◽  
Milling Process ◽  
Roughness Parameters ◽  
Laser Milling ◽  
Pulsed Fiber Laser

Abstract The paper deals with characterisation and modelling of laser milling process on Silicon Carbide hard ceramic. To this end, a Yb:YAG pulsed fiber laser was adopted to mill Silicon Carbide bars. Square pockets, 5x5 mm2 in plane dimension, were machined at the maximum nominal average power (30W), under different laser process parameters: pulse frequency, scan speed, hatching distance, repetitions and scanning strategy. After machining, the achieved depth and the roughness parameters were measured by way of digital microscopy and 3D surface profiling, respectively. In addition, the material removal rate was calculated as the ratio between the removed volume/process time. ANalysis Of VAriance (ANOVA) was adopted to assess the effect of the process parameters on the achieved depth, the material removal rate (MRR) and roughness parameters, while Response Surface Methodology (RSM) and Artificial Neuronal Networks (ANNs) were adopted to model the process behaviours. Results show that both RSM and ANNs fault in MRR and RSm roughness parameters modelling. Thus, an integrated approach was developed to overcome the issue; the approach is based on the use of the RSM model to obtain a hybrid Training dataset for the ANNs. The results show that the approach can allow improvement in model accuracy.

Modeling of Material Removal Mechanism in Micro Electric Discharge Milling of Ti-6Al-4V

2014 ◽  
Vol 592-594 ◽  
pp. 516-520 ◽  
Author(s):  
Basil Kuriachen ◽  
Jose Mathew
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Work Piece ◽  
Machining Parameters ◽  
Removal Mechanism ◽  
Material Removal Mechanism ◽  
Electric Discharge Milling

Micro EDM milling process is accruing a lot of importance in micro fabrication of difficult to machine materials. Any complex shape can be generated with the help of the controlled cylindrical tool in the pre determined path. Due to the complex material removal mechanism on the tool and the work piece, a detailed parametric study is required. In this study, the influence of various process parameters on material removal mechanism is investigated. Experiments were planned as per Response Surface Methodology (RSM) – Box Behnken design and performed under different cutting conditions of gap voltage, capacitance, electrode rotation speed and feed rate. Analysis of variance (ANOVA) was employed to identify the level of importance of machining parameters on the material removal rate. Maximum material removal rate was obtained at Voltage (115V), Capacitance (0.4μF), Electrode rotational Speed (1000rpm), and Feed rate (18mm/min). In addition, a mathematical model is created to predict the material removal

scholarly journals Application of EDAS, MARCOS, TOPSIS, MOORA and PIV Methods for Multi-Criteria Decision Making in Milling Process

2021 ◽  
Vol 71 (2) ◽  
pp. 69-84
Author(s):  
Do Duc Trung
Keyword(s):  
Decision Making ◽  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Milling Process ◽  
Multi Criteria Decision Making ◽  
Milling Method

Abstract Low surface roughness and high Material Removal Rate (MRR) are expected in most machining methods in general and milling method in particular. However, they sometimes do not occur, for example, the MRR is often small as the surface roughness is low. In this case, the decisions made should ensure that desires are simultaneously satisfied. This situation leads to a problem known as multi-criteria decision making (MCDM). In this study, five methods including EDAS, MARCOS, PIV, MOORA and TOPSIS are used together for the decision-making in the milling process. The purpose of the research is to determine the value of cutting parameters for both the low surface roughness and large MRR. The comparison of these methods for finding the best is carefully discussed as well.

scholarly journals Multi-Objective Parameter Optimization for Disc Milling Process of Titanium Alloy Blisk Channels

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 173
Author(s):  
Zhishan Li ◽  
Yaoyao Shi
Keyword(s):  
Residual Stress ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Cutter Life ◽  
Stress Layer ◽  
Grey Relational ◽  
Optimal Process Parameter

The blisk has been widely used in modern high performance aero-engines of high thrust-weight ratio. Disc milling process provides a reliable way to improve the efficiency of the blisk milling. The process parameters of disc milling have crucial effects on the milling efficiency and physical property of blisk. In this paper, material removal rate, cutter life and thickness of residual stress layer are regarded as optimization targets the key process parameters such as spindle speed, cutting depth and feed speed are optimized. Based on the grey relational analysis, the multi-objective optimization problem is transformed into a single objective optimization problem. At the same time, the problem of non-symmetry influence of key process parameters on optimization targets can be solved. And the influence weight of material removal rate, cutter life and thickness of residual stress layer on the grey relational grade (GRG) are calculated according to principal component analysis. The second order prediction model of GRA is developed by response surface method. On the basis of verifying the accuracy of the model, the influence mechanism of the process parameters coupling on the gray correlation degree is analyzed the optimal process parameter combination is obtained as spindle speed with 81.92 rpm, cutting depth with 5.88 mm and feed rate with 66.0823 mm/min. The experimental research show that the optimal process parameter combination can effectively improve the material removal rate and cutter life and reduce the thickness of residual stress layer.

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