scholarly journals Modelling Laser Milling of Microcavities for the Manufacturing of DES with Ensembles

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Pedro Santos ◽  
Daniel Teixidor ◽  
Jesus Maudes ◽  
Joaquim Ciurana
Keyword(s):  
Process Parameters ◽  
Nearest Neighbor ◽  
Laser System ◽  
Scanning Speed ◽  
Pulse Frequency ◽  
Milling Process ◽  
Support Vector ◽  
Average Value ◽  
Laser Milling ◽  
Relative Errors

A set of designed experiments, involving the use of a pulsed Nd:YAG laser system milling 316L Stainless Steel, serve to study the laser-milling process of microcavities in the manufacture of drug-eluting stents (DES). Diameter, depth, and volume error are considered to be optimized as functions of the process parameters, which include laser intensity, pulse frequency, and scanning speed. Two different DES shapes are studied that combine semispheres and cylinders. Process inputs and outputs are defined by considering the process parameters that can be changed under industrial conditions and the industrial requirements of this manufacturing process. In total, 162 different conditions are tested in a process that is modeled with the following state-of-the-art data-mining regression techniques: Support Vector Regression, Ensembles, Artificial Neural Networks, Linear Regression, and Nearest Neighbor Regression. Ensemble regression emerged as the most suitable technique for studying this industrial problem. Specifically, Iterated Bagging ensembles with unpruned model trees outperformed the other methods in the tests. This method can predict the geometrical dimensions of the machined microcavities with relative errors related to the main average value in the range of 3 to 23%, which are considered very accurate predictions, in view of the characteristics of this innovative industrial task.

scholarly journals Effect of Process Parameters and Material Properties on Laser Micromachining of Microchannels

Micromachines ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 123 ◽  
Author(s):  
Matthew Benton ◽  
Mohammad Hossan ◽  
Prashanth Konari ◽  
Sanjeewa Gamagedara
Keyword(s):  
Process Parameters ◽  
Laser System ◽  
Three Dimensional ◽  
Microfluidic Devices ◽  
Scanning Speed ◽  
Transient Heat Conduction ◽  
Laser Micromachining ◽  
Rapid Phase ◽  
Widespread Application ◽  
Optimization Of Process Parameters

Laser micromachining has emerged as a promising technique for mass production of microfluidic devices. However, control and optimization of process parameters, and design of substrate materials are still ongoing challenges for the widespread application of laser micromachining. This article reports a systematic study on the effect of laser system parameters and thermo-physical properties of substrate materials on laser micromachining. Three dimensional transient heat conduction equation with a Gaussian laser heat source was solved using finite element based Multiphysics software COMSOL 5.2a. Large heat convection coefficients were used to consider the rapid phase transition of the material during the laser treatment. The depth of the laser cut was measured by removing material at a pre-set temperature. The grid independent analysis was performed for ensuring the accuracy of the model. The results show that laser power and scanning speed have a strong effect on the channel depth, while the level of focus of the laser beam contributes in determining both the depth and width of the channel. Higher thermal conductivity results deeper in cuts, in contrast the higher specific heat produces shallower channels for a given condition. These findings can help in designing and optimizing process parameters for laser micromachining of microfluidic devices.

Experimental Analysis of Laser Micro-Machining Process Parameters

2012 ◽  
Vol 713 ◽  
pp. 67-72
Author(s):  
Daniel Teixidor ◽  
I. Ferrer ◽  
Joaquim de Ciurana
Keyword(s):  
Process Parameters ◽  
Laser System ◽  
Milling Process ◽  
Machining Process ◽  
Micro Milling ◽  
Surface Finishing ◽  
Features Selection ◽  
Operational Parameters ◽  
Micro Channels ◽  
Hardened Tool Steel

This paper reports the characterization of laser machining (milling) process to manufacture micro-channels in order to understand the incidence of process parameters on the final features. Selection of process operational parameters is highly critical for successful laser micromachining. A set of designed experiments is carried out in a pulsed Nd:YAG laser system using AISI H13 hardened tool steel as work material. Several micro-channels have been manufactured as micro-mold cavities varying different process parameter. Results are obtained by evaluating the dimensions and the surface finish of the micro-channel. The dimensions and shape of the micro-channels produced with laser-micro-milling process exhibit variations. In general the use of low scanning speeds increases the quality of the feature in both surface finishing and dimensional.

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.

scholarly journals Influence of Rapid Solidification and Optimized Process Parameters on the Microstructural Evolution of Additive Manufactured Titanium Alloy Grade 5 Composite

2021 ◽  
Vol 309 ◽  
pp. 01147
Author(s):  
O.S. Fatoba ◽  
S.A. Akinlabi ◽  
O.M. Ikumapayi ◽  
E.T. Akinlabi
Keyword(s):  
Process Parameters ◽  
Laser Scanning ◽  
Gas Flow ◽  
Laser System ◽  
Scanning Speed ◽  
Deposition Process ◽  
Cooling Rates ◽  
Grade 5 ◽  
Direct Laser ◽  
Columnar Grains

The study experimentally investigates the effects that Ytterbium Laser System process parameters, such as laser power, powder feed rate and traverse speed, has on the resultant microstructure of Ti- 6Al-4V grade 5 alloy. The deposition process was conducted employing a 3kW (CW) Ytterbium Laser System (YLS-2000-TR) machine, coaxial to the reinforcement powder. The laser scanning speed and power were varied between the intervals of 1-1.2 m/min and 900-1000 W. All other parameters kept constant where the rate of gas flow, the spot diameter, and the rate of powder flow. The microstructure was characterized by grain size and morphology by using Optical Microscopy (OM) and Scanning Electron Microscopy (SEM). The microstructural and mechanical properties were ascertained and the relationships with the process parameters were achieved. As a result of rapid cooling, the morphological features of α and α’ are distinctive and appear acicular. The structures appear coarsened. The metallurgy of the samples identifies with a morphology of multi-scale; with the coarsened alpha structures being reduced, plate-like, discrete and finer. The alpha grains closer to the fusion zone grew epitaxially, and the ones above these are acicular and lamellar. The results also indicated that slow traverse speeds increase the scale of columnar grains, while other process parameters were kept constant. Columnar microstructures became prevalent due to the dynamic temperature gradients/spikes, and sustainable cooling rates, pertaining to fabricating direct laser deposited Ti-6Al-4V grade 5 alloy. It was ascertained that by increasing the traverse speeds, the cooling rates increased, which resulted in a decrease in the width of the columnar grains.

Influence of Process Parameters on the Microstructure, and Geometrical Characteristics of Laser Additive Manufactured (LAM) Titanium Alloy Composite Coatings

2020 ◽  
Author(s):  
O. S. Fatoba ◽  
A. M. Lasisi ◽  
S. A. Akinlabi ◽  
E. T. Akinlabi ◽  
A. A. Adediran
Keyword(s):  
Process Parameters ◽  
Laser Power ◽  
Laser Scanning ◽  
Gas Flow ◽  
Composite Coatings ◽  
Laser System ◽  
Scanning Speed ◽  
Deposition Process ◽  
Beta Phase ◽  
Influence Of Process Parameters

Abstract The study experimentally investigates the effects of Ytterbium Laser System process parameters on the resultant microstructure of Ti-6Al-4V grade 5 alloy and reinforcement powders. The deposition process was conducted employing a 3 kW (CW) Ytterbium Laser System (YLS-2000-TR) machine, coaxial to the reinforcement powder. The laser scanning speed and power were varied between the intervals of 0.8–1.0 m/min and 900–1000 W. All other parameters kept constant were the rate of gas flow, the spot diameter, and the rate of powder flow. Metallurgical studies were conducted where all the samples microstructure was characterized by employing Scanning Electron Microscopy (SEM) and Optical Microscopy (OM). The results showed that a minimum porosity was achieved at high laser power complemented with low powder feed rate. The microstructure formed was dominated by columnar grains and martensitic needle-like structures with a formation of beta phase. It was observed that the microstructure was influenced significantly by the two laser speed modes, and the laser power. The grain size and phase structure were influenced significantly by the laser power; increasing it had resulted in larger grains, and a coarser microstructure. The results also showed that the residual stresses of the optimized specimens were compressive.

Experimental analysis of the laser milling process parameters

2007 ◽  
Vol 191 (1-3) ◽  
pp. 220-223 ◽  
Author(s):  
S.L. Campanelli ◽  
A.D. Ludovico ◽  
C. Bonserio ◽  
P. Cavalluzzi ◽  
M. Cinquepalmi
Keyword(s):  
Process Parameters ◽  
Experimental Analysis ◽  
Milling Process ◽  
Laser Milling

Optimizing Error Rate in Intrusion Detection System Using Artificial Neural Network Algorithm

2018 ◽  
Vol 6 (9) ◽  
pp. 152
Author(s):  
S. Vijaya Rani ◽  
G. N. K. Suresh Babu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Intrusion Detection ◽  
Error Rate ◽  
Learning Process ◽  
Nearest Neighbor ◽  
Detection System ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Artificial Neural

The illegal hackers  penetrate the servers and networks of corporate and financial institutions to gain money and extract vital information. The hacking varies from one computing system to many system. They gain access by sending malicious packets in the network through virus, worms, Trojan horses etc. The hackers scan a network through various tools and collect information of network and host. Hence it is very much essential to detect the attacks as they enter into a network. The methods  available for intrusion detection are Naive Bayes, Decision tree, Support Vector Machine, K-Nearest Neighbor, Artificial Neural Networks. A neural network consists of processing units in complex manner and able to store information and make it functional for use. It acts like human brain and takes knowledge from the environment through training and learning process. Many algorithms are available for learning process This work carry out research on analysis of malicious packets and predicting the error rate in detection of injured packets through artificial neural network algorithms.

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