Optimization of milling process parameters for energy saving and surface roughness

2019 ◽  
Vol 70 (3) ◽  
pp. 173-183
Author(s):  
Pham, Quoc-Hoang ◽  
Dang Xuan-Phuong ◽  
Doan, Tat-Khoa ◽  
Le Xuan-Hung ◽  
Thi Lan-Huong Luong ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Hybrid Approach ◽  
Optimal Solution ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
H13 Steel ◽  
Technical Parameters ◽  
Desirability Approach ◽  
Aisi H13

Improving the technical parameters of the machining process is an effective solution to save manufacturing costs. The purpose of this work is to decrease energy consumption (EC) and average surface roughness(ASR) for the milling process of AISI H13 steel. The spindle speed (S), depth of cut (a), and feed rate (f) were the processing inputs. The milling runs were performed using the experimental plan generated by the Box-Behnken method approach. The relationships between inputs and outputs were established using the response surface models (RSM). The desirability approach (DA) was used to observe the optimal values. The results showed that the reductions of EC and ASR are approximately 33.75% and 40.58%, respectively, as compared to the initial parameter setting. In addition, a hybrid approach using RSM and DA can be considered as a powerful solution to model the milling process and obtain a reliable optimal solution.

scholarly journals Optimization of milling process parameters for energy saving and surface roughness

2019 ◽  
Vol 70 (3) ◽  
pp. 173-183
Author(s):  
Pham, Quoc-Hoang ◽  
Dang Xuan-Phuong ◽  
Doan, Tat-Khoa ◽  
Le Xuan-Hung ◽  
Thi Lan-Huong Luong ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Hybrid Approach ◽  
Optimal Solution ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
H13 Steel ◽  
Technical Parameters ◽  
Desirability Approach ◽  
Aisi H13

Improving the technical parameters of the machining process is an effective solution to save manufacturing costs. The purpose of this work is to decrease energy consumption (EC) and average surface roughness(ASR) for the milling process of AISI H13 steel. The spindle speed (S), depth of cut (a), and feed rate (f) were the processing inputs. The milling runs were performed using the experimental plan generated by the Box-Behnken method approach. The relationships between inputs and outputs were established using the response surface models (RSM). The desirability approach (DA) was used to observe the optimal values. The results showed that the reductions of EC and ASR are approximately 33.75% and 40.58%, respectively, as compared to the initial parameter setting. In addition, a hybrid approach using RSM and DA can be considered as a powerful solution to model the milling process and obtain a reliable optimal solution.

Optimization of Process Parameters for Cutting Force for Aluminium 7010 in CNC End Milling Process

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
M. Kishanth ◽  
P. Rajkamal ◽  
D. Karthikeyan ◽  
K. Anand
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Optimization Of Process Parameters ◽  
Cnc End Milling ◽  
End Milling Process

In this paper CNC end milling process have been optimized in cutting force and surface roughness based on the three process parameters (i.e.) speed, feed rate and depth of cut. Since the end milling process is used for abrading the wear caused is very high, in order to reduce the wear caused by high cutting force and to decrease the surface roughness, the optimization is much needed for this process. Especially for materials like aluminium 7010, this kind of study is important for further improvement in machining process and also it will improve the stability of the machine.

Effect Analysis and ANN Prediction of Surface Roughness in End Milling AISI H13 Steel

2014 ◽  
Vol 800-801 ◽  
pp. 590-595
Author(s):  
Qing Zhang ◽  
Song Zhang ◽  
Jia Man ◽  
Bin Zhao
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Experimental Results ◽  
Depth Of Cut ◽  
H13 Steel ◽  
Aisi H13 Steel ◽  
Radial Depth ◽  
Aisi H13

Surface roughness has a significant effect on the performance of machined components. In the present study, a total of 49 end milling experiments on AISI H13 steel are conducted. Based on the experimental results, the signal-to-noise (S/N) ratio is employed to study the effects of cutting parameters (axial depth of cut, cutting speed, feed per tooth and radial depth of cut) on surface roughness. An ANN predicting model for surface roughness versus cutting parameters is developed based on the experimental results. The testing results show that the proposed model can be used as a satisfactory prediction for surface roughness.

Optimization of Cutting Parameters for Improving Surface Roughness during Hard Milling of AISI H13 Steel

2020 ◽  
Vol 831 ◽  
pp. 35-39 ◽  
Author(s):  
The Vinh Do ◽  
Quoc Manh Nguyen ◽  
Minh Tan Pham
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
H13 Steel ◽  
Hard Milling ◽  
Aisi H13 Steel ◽  
Cooling Conditions ◽  
Aisi H13

In metal cutting, surface roughness plays an important role in assessing the quality of processed products. The roughness depends greatly on the selection of machining parameters such as cooling conditions and cutting parameters. For this purpose, cooling conditions including dry, MQL, and Silica-based nanofluid MQL as well as cutting parameters including cutting speed, depth-of-cut and feed-rate were investigated to determine their influence on machining roughness during hard milling of AISI H13 steel. The DOE method developed by G. Taguchi was used to design the experiments. An analysis of the signal-to-noise response and ANOVA were carried to obtain the optimal values of cutting parameters for minimizing surface roughness. The results of the present study show that Silica-based nanofluid MQL, minimum feed-rate, minimum depth-of-cut, and maximum cutting speed is an optimal cutting condition for reducing machining roughness.

Optimization of Cutting Parameters for Desirable Surface Roughness in End-Milling Hardened AISI H13 Steel under a Certain Metal Removal Rate

2011 ◽  
Vol 188 ◽  
pp. 307-313 ◽  
Author(s):  
Tong Chao Ding ◽  
Song Zhang ◽  
Z.M. Li ◽  
Yuan Wei Wang
Keyword(s):  
Surface Roughness ◽  
Metal Removal ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Metal Removal Rate ◽  
H13 Steel ◽  
Orthogonal Experiments ◽  
Aisi H13

In this paper, the orthogonal experiments and the optimization experiments with the same metal removal rate are designed to investigate the main effects and primary interaction of cutting parameters on surface roughness and to search the optimal cutting parameter under a certain removal rate when end-milling hardened AISI H13 steel with the PVD coated carbide insert. The empirical model for surface roughness based on the orthogonal experiments and the optimization experiments with the same metal removal rate and the optimal cutting parameter were all verified. Under a certain metal removal rate, the combination of high cutting speed, small axial depth of cut and high feed, small radial depth of cut generates the best surface roughness in hard milling of AISI H13.

Studying The Effect of a New Mixed Cutting Fluid on Surface Roughness

2020 ◽  
Vol 38 (11A) ◽  
pp. 1593-1601
Author(s):  
Mohammed H. Shaker ◽  
Salah K. Jawad ◽  
Maan A. Tawfiq
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Machining Processes ◽  
Dry Cutting ◽  
Cutting Speeds

This research studied the influence of cutting fluids and cutting parameters on the surface roughness for stainless steel worked by turning machine in dry and wet cutting cases. The work was done with different cutting speeds, and feed rates with a fixed depth of cutting. During the machining process, heat was generated and effects of higher surface roughness of work material. In this study, the effects of some cutting fluids, and dry cutting on surface roughness have been examined in turning of AISI316 stainless steel material. Sodium Lauryl Ether Sulfate (SLES) instead of other soluble oils has been used and compared to dry machining processes. Experiments have been performed at four cutting speeds (60, 95, 155, 240) m/min, feed rates (0.065, 0.08, 0.096, 0.114) mm/rev. and constant depth of cut (0.5) mm. The amount of decrease in Ra after the used suggested mixture arrived at (0.21µm), while Ra exceeded (1µm) in case of soluble oils This means the suggested mixture gave the best results of lubricating properties than other cases.

OPTIMISING CUTTING PARAMETERS FOR HOT TURNING ON EN31 MATERIAL

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Prof. Hemant k. Baitule ◽  
Satish Rahangdale ◽  
Vaibhav Kamane ◽  
Saurabh Yende
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Multiple Time ◽  
Turning Process ◽  
Workpiece Material ◽  
Hot Turning

In any type of machining process the surface roughness plays an important role. In these the product is judge on the basis of their (surface roughness) surface finish. In machining process there are four main cutting parameter i.e. cutting speed, feed rate, depth of cut, spindle speed. For obtaining good surface finish, we can use the hot turning process. In hot turning process we heat the workpiece material and perform turning process multiple time and obtain the reading. The taguchi method is design to perform an experiment and L18 experiment were performed. The result is analyzed by using the analysis of variance (ANOVA) method. The result Obtain by this method may be useful for many other researchers.

Low Cost Vibration Measurement and Optimization during Turning Process

2018 ◽  
Vol 1148 ◽  
pp. 103-108 ◽  
Author(s):  
N.V.S. Shankar ◽  
A. Gopi Chand ◽  
K. Hanumantha Rao ◽  
K. Prem Sai
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Low Cost ◽  
Machining Process ◽  
Vibration Measurement ◽  
Depth Of Cut ◽  
Turning Process ◽  
Taguchi Analysis ◽  
Series Of Experiments

During machining any material, vibrations play a major role in deciding the life of the cutting tool as well as machine tool. The magnitude acceleration of vibrations is directly proportional to the cutting forces. In other words, if we are able to measure the acceleration experienced by the tool during machining, we can get a sense of force. There are many commercially available, pre-calibrated accelerometer sensors available off the shelf. In the current work, an attempt has been made to measure vibrations using ADXL335 accelerometer. This accelerometer is interfaced to computer using Arduino. The measured values are then used to optimize the machining process. Experiments are performed on Brass. During machining, it is better to have lower acceleration values. Thus, the first objective of the work is to minimize the vibrations. Surface roughness is another major factor which criterion “lower is the better” applies. In order to optimize the values, a series of experiments are conducted with three factors, namely, tool type (2 levels), Depth of cut (3 levels) and Feed are considered (3 levels). Mixed level optimization is performed using Taguchi analysis with L18 orthogonal array. Detailed discussion of the parameters shall be given in the article.

Characterisation, Performance and Optimisation of Nanocellulose Metalworking Fluid (MWF) for Green Machining Process

2021 ◽  
Vol 18 (4) ◽  
pp. 9188-9207
Author(s):  
Mahendran Samykano ◽  
J. Kananathan ◽  
K. Kadirgama ◽  
A. K. Amirruddin ◽  
D. Ramasamy ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Alumina Nanoparticles ◽  
Working Fluid ◽  
Depth Of Cut ◽  
Nanoparticle Concentration

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour.

scholarly journals Optimization of Power Consumption Associated with Surface Roughness in Ultrasonic Assisted Turning of Nimonic-90 Using Hybrid Particle Swarm-Simplex Method

Materials ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3418 ◽  
Author(s):  
Khanna ◽  
Airao ◽  
Gupta ◽  
Song ◽  
Liu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Fitness Function ◽  
Particle Swarm ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Hybrid Particle ◽  
Ultrasonic Assisted

These days, power consumption and energy related issues are very hot topics of research especially for machine tooling process industries because of the strict environmental regulations and policies. Hence, the present paper discusses the application of such an advanced machining process i.e., ultrasonic assisted turning (UAT) process with the collaboration of nature inspired algorithms to determine the ideal solution. The cutting speed, feed rate, depth of cut and frequency of cutting tool were considered as input variables and the machining performance of Nimonic-90 alloy in terms of surface roughness and power consumption has been investigated. Then, the experimentation was conducted as per the Taguchi L9 orthogonal array and the mono as well as bi-objective optimizations were performed with standard particle swarm and hybrid particle swarm with simplex methods (PSO-SM). Further, the statistical analysis was performed with well-known analysis of variance (ANOVA) test. After that, the regression equation along with selected boundary conditions was used for creation of fitness function in the subjected algorithms. The results showed that the UAT process was more preferable for the Nimconic-90 alloy as compared with conventional turning process. In addition, the hybrid PSO-SM gave the best results for obtaining the minimized values of selected responses.

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