scholarly journals Process Parameters Optimization Using Taguchi-Based Grey Relational Analysis in Laser-Assisted Machining of Si3N4

Materials ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 529
Author(s):  
Yezhuang Pu ◽  
Yugang Zhao ◽  
Jianbing Meng ◽  
Guoyong Zhao ◽  
Haiyun Zhang ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Work Hardening ◽  
Laser Power ◽  
Material Removal ◽  
Ceramic Materials ◽  
Machining Parameters ◽  
Cutting Depth ◽  
Relational Analysis ◽  
Material Removal Mode ◽  
Grey Relational

Despite extensive research over the past three decades proving that laser-assisted machining (LAM) is effective for machining ceramic materials, which are affected by many machining parameters, there has been no systematic study of the effects of process parameters on surface quality in LAM ceramic materials. In this paper, the effects and optimization of laser power, spindle speed, feed rate, and cutting depth on surface roughness and work hardening of LAM Si3N4 were systematically studied, using grey relational analysis coupled with the Taguchi method. The results show that the combination of machining parameters determines the material removal mode at the material removal location, and then affects the surface quality. In ductile material removal mode, both the value of surface roughness and work hardening degree are smaller. Decreased surface roughness and work hardening degree can be obtained with smaller cutting depth and higher laser power.

Study on Surface Roughness in Ultrasonic Vibration Mill-Grinding Hot-Pressed Silicon Nitride

2012 ◽  
Vol 500 ◽  
pp. 269-274 ◽  
Author(s):  
Guo Chao Qiao ◽  
Ming Zhou ◽  
Ming Wang
Keyword(s):  
Surface Roughness ◽  
Ultrasonic Vibration ◽  
Material Removal ◽  
Machining Parameters ◽  
Cutting Depth ◽  
Abrasive Grain ◽  
Feeding Speed ◽  
Material Removal Mode ◽  
Amplitude Decrease ◽  
Vibration Mill

In order to investigate the influences of machining parameters on surface roughness in ultrasonic vibration mill-grinding, the motion of abrasive grain is analyzed. The analysis indicates that grain and workpiece separate periodically which are beneficial for coolant entering into grinding zone to reduce grinding temperature and grinding force and improve surface quality. Experiments are carried out and detected by SEM and roughmeter, the results indicate that influences of spindle rate, feeding speed, cutting depth and amplitude decrease in turn. Through regression analysis, an empirical formula is obtained. The experiments indicate that material removal mode dominates surface roughness.

Performance analysis of process parameters on machining α–β titanium alloy in electrochemical micromachining process

2016 ◽  
Vol 232 (9) ◽  
pp. 1577-1589 ◽  
Author(s):  
T Geethapriyan ◽  
K Kalaichelvan ◽  
T Muthuramalingam ◽  
A Rajadurai
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Grey Relational Analysis ◽  
Material Removal ◽  
Electrolyte Concentration ◽  
Removal Rate ◽  
Electrochemical Micromachining ◽  
Relational Analysis ◽  
Micro Tool ◽  
Grey Relational

Due to inherent properties of Ti-6Al-4V alloy, it is being used in the application of fuel injector nozzle for diesel engine, aerospace and marine industries. Since the electrochemical micromachining process involves the no heat-affected zone, no tool wear, stress- and burr-free process compared to other micromachining processes, it is widely used in the manufacturing field to fabricate complex shape and die. Hence, it is highly important to compute the optimum input parameters for enhancing the machining characteristics in such machining process. In this study, an attempt has been made to find the influence of the process parameters and optimize the parameters on machining α–β titanium alloy using Taguchi-grey relational analysis. Since applied voltage, micro-tool feed rate, electrolyte concentration and duty cycle have vital role in the process, these parameters have been chosen as the input parameters to evaluate the performance measures such as material removal rate, surface roughness and overcut in this study. From the experimental results, it has been found that micro-tool feed rate has more influence due to its importance in maintaining inter electrode gap to avoid micro-spark generation. It has also been found that lower electrolyte concentration with lower duty cycle produces lower surface roughness with better circularity on machining α–β titanium alloy. The optimum combination has been found using Taguchi-grey relational analysis and verified from confirmation test. It has also been inferred that the multi-response characteristics such as material removal rate, surface roughness and overcut can be effectively improved through the grey relational analysis.

scholarly journals A Study on Work Hardening in the Laser-Assisted Machining of Si3N4 Ceramics under Different Material Removal Modes

Metals ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 432
Author(s):  
Yezhuang Pu ◽  
Yugang Zhao ◽  
Guoyong Zhao ◽  
Jianbing Meng ◽  
Haiyun Zhang ◽  
...  
Keyword(s):  
Work Hardening ◽  
Laser Power ◽  
Material Removal ◽  
Single Factor ◽  
Cutting Depth ◽  
Laser Assisted Machining ◽  
Cutting Deformation ◽  
Si3n4 Ceramics

In order to understand the work hardening phenomenon and mechanism of laser-assisted machining (LAM) of Si3N4 ceramics, the work hardening degree of LAM Si3N4 under different material removal modes was studied. Two sets of single-factor experiments were performed in which the laser power and the cutting depth were changed respectively. The results show that work hardening is the result of the combination of heat and cutting deformation during cutting. The work hardening degree decreases with the increase of material softening degree. When the material is removed plastically, the work hardening degree is 110–115%.

Modelling and Optimization of Machining parameters for Turning Automotive Shafts using RSM and Grey Relational Analysis

2020 ◽  
Vol 12 (4) ◽  
Author(s):  
S. Dinesh ◽  
K. Rajaguru ◽  
K. Saravanan ◽  
R. Yokeswaran ◽  
V. Vijayan
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational ◽  
Central Composite ◽  
Modelling And Optimization

Automotive shafts require maximum strength with regard to axial, bending and torsional loading to transmit power to various parts of a vehicle. Hence, it is very critical to analyse the manufacturing process and its governing parameters to exercise control over the surface properties of the shaft as it needs to be precisely manufactured in terms of dimensions and the surface roughness. The effect of three input parameters over two responses are considered as two major criteria's for production of shaft. The input parameters are speed, feed and depth of cut whereas the responses are material removal rate and surface roughness. Central Composite design was used and experimental results were analysed with Response Surface Methodology. ANOVA analysis was carried out to identify the most contributing parameter for MRR and SR. Grey Relational Analysis was adopted to identify the most feasible combination of machining parameters for turning process. The optimized parameter is identified as speed of 1000 rpm, 0.15 mm of feed and 0.35 mm of depth of cut using Grey Relational Analysis.

scholarly journals OPTIMASI PARAMETER MESIN LASER CUTTING TERHADAP KEKASARAN DAN LAJU PEMOTONGAN PADA SUS 316L MENGGUNAKAN TAGUCHI GREY RELATIONAL ANALYSIS METHOD

2016 ◽  
Vol 11 (2) ◽  
pp. 97
Author(s):  
Rakasita R ◽  
Karuniawan BW ◽  
Anda Iviana Juniani
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Laser Cutting ◽  
Cutting Speed ◽  
Cutting Process ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Cutting Rate ◽  
Grey Relational

Optimasi parameter adalah teknik yang digunakan pada proses manufaktur untuk menghasilkan produk terbaik. Penelitian ini bertujuan untuk mengoptimasi parameter CNC laser cutting, yaitu titik fokus sinar laser, tekanan gas cutting dan cutting speed untuk mengurangi variasi terhadap respon kekasaran dan laju pemotongan pada material SUS 316L. Masing-masing parameter memiliki 3 level dan pada penelitian ini menggunakan matriks orthogonal L9 (34). Metode ANOVA dan Taguchi digunakan untuk menganalisis data hasil percobaan. Optimasi kekasaran minimum permukaan dan laju pemotongan maksimum pada proses laser cutting dilakukan dengan menggunakan Grey relational analysis. Eksperimen konfirmasi digunakan untuk membuktikan hasil optimal yang telah didapatkan dari metode Taguchi Grey relational analysis. Hasil eksperimen menunjukkan bahwa Taguchi Grey relational analysis efektif digunakan untuk mengoptimasi parameter pemesinan pada laser cutting dengan multi respon. AbstractParameter optimization is used in manufacturing as an indicator to produce the best manufacturing product. This paper studies an optimization parameters of CNC laser cutting such as focus of laser beam, pressure cutting gases and cutting speed for reducing variation of surface roughness and cutting rate on material SUS 316L. Based on L9(34) orthogonal array parameters, it is analized using ANOVA based on Taguchi method. In order to optimaze the minimum surface roughness and maximum cutting rate in laser cutting process, it is used Grey relational analysis. The confirmation experiments used to validate the optimal results that has done by Taguchi method. The results show that the Taguchi Grey relational analysis is being effective to optimize the machining parameters for laser cutting process with two responses.

Parametric Study of Pulsed CO2 Laser Surface Treatment of Alumina Ceramics

2015 ◽  
Vol 15 (3) ◽  
pp. 301-308
Author(s):  
A. Bharatish ◽  
H. N. Narasimha Murthy ◽  
Ajithkumar Radder ◽  
V. Mamatha ◽  
B. Anand ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Laser Power ◽  
Material Removal ◽  
Removal Rate ◽  
Scanning Speed ◽  
Pulse Frequency ◽  
Alumina Ceramics ◽  
Laser Surface Treatment ◽  
Grey Relational

AbstractThis paper focuses on investigating the influence of laser power, pulse frequency and scanning speed on material removal rate and surface roughness during CO2 laser surface treatment of alumina ceramics. Pulse frequency and laser power were the significant factors influencing the material removal rate and surface roughness, respectively. Adequate response surface models were established to correlate the laser parameters and the measured responses. Grey relational analysis predicted the optimal responses at 90 W laser power, 5 kHz pulse frequency and 400 mm/s scanning speed. Desirability function based Multi objective optimization results indicated that minimum material removal rate (0.5117 mm3/s) and surface roughness (0.5968 µm) are achieved at 90 W laser power, 5 kHz pulse frequency and 337.37 mm/s scanning speed which were in close agreement with Grey Relational results. Increase in homogeneity and smoothness of the laser treated alumina surface along with formation of micro recast particles away from the laser traverse path were evidenced by the SEM micrographs.

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