scholarly journals Effects of Turning Parameters and Parametric Optimization of the Cutting Forces in Machining SiCp/Al 45 wt% Composite

Metals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 840 ◽  
Author(s):  
Rashid Ali Laghari ◽  
Jianguang Li ◽  
Mozammel Mia
Keyword(s):  
Mathematical Model ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Desirability Function ◽  
Interactive Effect ◽  
Cutting Speed ◽  
Experimental Results ◽  
Machining Process ◽  
Depth Of Cut

Cutting force in the machining process of SiCp/Al particle reinforced metal matrix composite is affected by several factors. Obtaining an effective mathematical model for the cutting force is challenging. In that respect, the second-order model of cutting force has been established by response surface methodology (RSM) in this study, with different cutting parameters, such as cutting speed, feed rate, and depth of cut. The optimized mathematical model has been developed to analyze the effect of actual processing conditions on the generation of cutting force for the turning process of SiCp/Al composite. The results show that the predicted parameters by the RSM are in close agreement with experimental results with minimal error percentage. Quantitative evaluation by using analysis of variance (ANOVA), main effects plot, interactive effect, residual analysis, and optimization of cutting forces using the desirability function was performed. It has been found that the higher depth of cut, followed by feed rate, increases the cutting force. Higher cutting speed shows a positive response by reducing the cutting force. The predicted and experimental results for the model of SiCp/Al components have been compared to the cutting force of SiCp/Al 45 wt%—the error has been found low showing a good agreement.

scholarly journals Modeling and optimization of cutting forces and effect of turning parameters on SiCp/Al 45% vs SiCp/Al 50% metal matrix composites: a comparative study

2021 ◽  
Vol 3 (7) ◽  
Author(s):  
Rashid Ali Laghari ◽  
Jianguang Li
Keyword(s):  
Mathematical Model ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Positive Response ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Force Model ◽  
Sic Particles

Abstract In this study, the proposed experimental and second-order model for the cutting forces were developed through several parameters, including cutting speed, feed rate, depth of cut, and two varying content of SiCp. Cutting force model was developed and optimized through RSM and compared for two different percentages of components SiCp/Al 45% and SiCp/Al 50%. ANOVA is used for Quantitative evaluation, the main effects plot along with the evaluation using different graphs and plots including residual analysis, contour plots, and desirability functions for cutting forces optimization. It provides the finding for choosing proper parameters for the machining process. The plots show that during increment with depth of cut in proportion with feed rate are able to cause increments in cutting forces. Higher cutting speed shows a positive response in both the weight percentage of SiCp by reducing the cutting force because of higher cutting speed increases. A very fractional increasing trend of cutting force was observed with increasing SiCp weight percentages. Both of the methods such as experiment and model-predicted results of SiCp/Al MMC materials were thoroughly evaluated for analyzing cutting forces of SiCp/Al 45%, and SiCp/Al 50%, as well as calculated the error percentages also found in an acceptable range with minimal error percentages. Article Highlights This study focuses on the effect of cutting parameters as well as different percentage of SiC particles on the cutting forces, while comparing the results of both SiC particles such as SiCp/Al 45%, and SiCp/Al 50% the result shows that there isn’t fractional amount of impact on the cutting force with nominal increasing percentages of SiC particles. Cutting speed in machining process of SiCp/Al shows positive response in reducing the cutting forces, however, increasing amount of depth of cut followed by increasing feed rate creates fluctuations in cutting force and thus increases the cutting force in the cutting process. The developed RSM mathematical model which is based on the box Behnken design show excellent competence for predicting and suggesting the machining parameters for both SiCp/Al 45%, and SiCp/Al 50% and the RSM mathematical model is feasible for optimization of the machining process with good agreement to experimental values.

Cutting Temperature and Cutting Forces Investigation Based on the Taguchi Design Method when High-Speed Milling of Titanium Matrix Composites with PCD Tool

2016 ◽  
Vol 836-837 ◽  
pp. 168-174 ◽  
Author(s):  
Ying Fei Ge ◽  
Hai Xiang Huan ◽  
Jiu Hua Xu
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
High Speed ◽  
Volume Fraction ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
High Speed Milling ◽  
Radial Depth

High-speed milling tests were performed on vol. (5%-8%) TiCp/TC4 composite in the speed range of 50-250 m/min using PCD tools to nvestigate the cutting temperature and the cutting forces. The results showed that radial depth of cut and cutting speed were the two significant influences that affected the cutting forces based on the Taguchi prediction. Increasing radial depth of cut and feed rate will increase the cutting force while increasing cutting speed will decrease the cutting force. Cutting force increased less than 5% when the reinforcement volume fraction in the composites increased from 0% to 8%. Radial depth of cut was the only significant influence factor on the cutting temperature. Cutting temperature increased with the increasing radial depth of cut, feed rate or cutting speed. The cutting temperature for the titanium composites was 40-90 °C higher than that for the TC4 matrix. However, the cutting temperature decreased by 4% when the reinforcement's volume fraction increased from 5% to 8%.

Machining Apprenticeship Based on Experimental Training Practice

2011 ◽  
Vol 692 ◽  
pp. 83-92
Author(s):  
Pedro Jose Arrazola ◽  
A. Villar ◽  
R. Fernández ◽  
J. Aperribay
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Feed Rate ◽  
Cutting Forces ◽  
Theoretical Calculations ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Practical Training ◽  
Input Parameters

This article describes a practical machining training aiming that the students acquire the theoretical-practical knowledge of chip formation process. The training takes place after theoretical lessons of machining processes. Thus, this practice allows strengthening the knowledge gained during the lessons. The practical training lasts for five hours, and the student assisted by the teacher analyses the influence of some machining entry parameters (cutting speed, feed rate...) on exit parameters like: (I) cutting forces and power consumption, (II) surface roughness, and (III) chip typology. The practical session is carried out on an experimental set-up (Lathe CNC Danobar 65) equipped with sensors and devices to measure forces (sensor Kistler 9121) and power consumption. In addition, a portable rugosimeter (Hommelwerke) is employed to perform surface roughness measurements. No especial devices are needed for the chip typology analysis. In the case of cutting forces and power consumption, the following input parameters influences are analysed: feed rate, depth of cut and cutting speed. In the case of surface roughness analysis, the following input parameters influences are analysed: feed rate and nose radius of the cutting insert. Finally, regarding chip typology feed rate and depth of cut are examined. The experimental results are compared with model predictions (theoretical calculations) for the three issues studied. The students have to compare both results: theoretical an empirical and they need to explain the reasons when discrepancies appear. Results obtained during the last years demonstrate the student acquires better knowledge of the machining process, and at the same time realises of the process complexity.

scholarly journals Validation and optimization of cutting parameters for Ti-6Al-4V turning operation using DEFORM 3D simulations and Taguchi method

2021 ◽  
Vol 8 ◽  
pp. 5
Author(s):  
Japheth Oirere Obiko ◽  
Fredrick Madaraka Mwema ◽  
Michael Oluwatosin Bodunrin
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Optimization Of Cutting Parameters ◽  
The Relationship

In this study, we show that optimising cutting forces as a machining response gave the most favourable conditions for turning of Ti-6Al-4V alloy. Using a combination of computational methods involving DEFORM simulations, Taguchi Design of Experiment (DOE) and analysis of variance (ANOVA), it was possible to minimise typical machining response such as the cutting force, cutting power and chip-tool interface temperature. The turning parameters that were varied in this study include cutting speed, depth of cut and feed rate. The optimum turning parameter combinations that would minimise the machining responses were established by using the “smaller the better” criterion and selecting the highest value of Signal to Noise Ratio. Confirmatory simulation revealed that using cutting speed of 120 m/min, 0.25 mm depth of cut and 0.1 mm/rev feed rate, the lowest cutting force of 88.21 N and chip-tool interface temperature of 387.24 °C can be obtained. Regression analysis indicated that the highest correlation coefficient of 0.97 was obtained between cutting forces and the turning parameters. The relationship between cutting forces and the turning parameters was linear since first-order regression model was sufficient.

Modeling and Analysis of Cutting Forces in Hard Turning T250 Steel Using CBN Tools

2010 ◽  
Vol 154-155 ◽  
pp. 694-700
Author(s):  
Yue Ding ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
Hao Yang
Keyword(s):  
Cutting Force ◽  
Analysis Of Variance ◽  
Feed Rate ◽  
Cutting Forces ◽  
Hard Turning ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Modeling And Analysis ◽  
Feed Force

The objective of this paper is to study the cutting forces in hard turning T250 steel with CBN tools. Experiments based on the Box-Behnken design were conducted to develop the cutting forces models by response surface methodology (RSM). Significance tests of the model are performed by the analysis of variance (ANOVA). It is also discussed the effects of cutting parameters (cutting speed, feed rate and depth of cut) on the cutting force components. The results show that the models can fit experimental data via analysis of variance. The most important cutting parameter is depth of cut, followed by feed rate, while the effect of cutting speed can be neglected. Compared to cutting force and feed force, thrust force is the largest. In addition, the cutting forces generated by the uncoated tool are smaller than by the coated one due to tool wear.

scholarly journals Assessment of Cutting Profile of AISI 1095 by Using Infrared Radiation Approach

2018 ◽  
Vol 7 (3.18) ◽  
pp. 79
Author(s):  
Mohammad Ashaari Kiprawi ◽  
Abdullah Yassin ◽  
Syed Tarmizi Syed Shazali ◽  
M Shahidul Islam ◽  
Mohd Azrin Mohd Said
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Infrared Radiation ◽  
Flank Wear ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Edge ◽  
Machining Process ◽  
Depth Of Cut ◽  
Edge Temperature

This research paper determines the relationship between cutting edge temperature, depth of cut, cutting speed, cutting forces and flank wear. The cutting edge temperature is determined by using a pyrometer consists of Indium Arsenide (InAs) and Indium Antimonide (InSb) photocells to detect infrared radiation that are released from cutting tool’s edge and cutting forces is measured by using a dynamometer. The machining process experiment is done by end milling the outer surface of AISI 1095 carbon steel. The output signal from the photocell and dynamometer is processed and recorded in the digital oscilloscope. Based on the results, the cutting edge temperature and cutting force increases as the depth of cut increases. Meanwhile, increasing cutting speed resulting in cutting edge temperature increases but decreasing in cutting force due to thermal deformation. Also, existence of progressive flank wear at cutting tool causes an increment in cutting edge temperature and cutting force proportionally.  

scholarly journals Dry turning of X2CrNi18-09 using coated carbide tools: modelling and optimization of multiple performance characteristics

Mechanika ◽  
2019 ◽  
Vol 25 (6) ◽  
pp. 487-500
Author(s):  
Septi Boucherit ◽  
Sofiane Berkani ◽  
Mohamed Athmane Yallese ◽  
Abdelkrim Haddad ◽  
Salim Belhadi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Work Piece ◽  
Machining Parameters ◽  
Coated Carbide

The present paper investigates the cutting parameters pertaining to the turning of X2CrNi18-09 austenitic stainless steel that are studied and optimized using both RSM and desirability approaches. The cutting tool inserts used are the CVD coated carbide. The cutting speed, the feed rate and the depth of cut represent the main machining parameters considered. Their influence on the surface roughness and the cutting force are further investigated using the ANOVA method. The results obtained lead to conclude that the feed rate is the surface roughness highest influencing parameter with a contribution of 89.69%.The depth of cut and the feed rate are further identified as the most important parameters affecting the cutting force with contributions of 46.46% and 39.04% respectively. The quadratic mathematical models presenting the progression of the surface roughness and the cutting force and based on the machining parameters considered (cutting speed, feed rate and depth of cut) were obtained through the application of the RSM method. They are presented and compared to the experimental results. Good agreement is found between the two sections of the investigation. Furthermore, the flank wear of the CVD-coated carbide tool (GC2015) is found to increase with both cutting speed and cutting time. A higher tool life represented by t=44min is observed at cutting speed, feed rate and depth of cut of 280m/min,0.08mm/rev and 0.2mm respectively. Moreover and at low cutting speeds, the formation of micro weld is noticed and leads to an alteration of the surface roughness of the work piece. Finally, optimizing the machining parameters with the objective of achieving an improved surface roughness was accomplished through the application of the Desirability Function approach. This enabled to finding out the optimal parameters for maximal material removal rate and best surface quality for a cutting speed of 350m/min, a feed rate of 0.088 mm/rev and a depth of cut of 0.9mm.  

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

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.

Predictive Modeling and Optimization of Cutting Forces Through RSM and Taguchi Techniques in the Turning of ASTM B574 (Hastelloy C-22)

2018 ◽  
pp. 398-417
Author(s):  
İsmail Kırbaş ◽  
Musa Peker ◽  
Gültekin Basmacı ◽  
Mustafa Ay
Keyword(s):  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Orthogonal Experimental Design ◽  
Depth Of Cut ◽  
Effective Parameters ◽  
Factors Affecting ◽  
The Impact

In this chapter, the impact of cutting parameters (depth of cut, cutting speed, feed, flow, rake angle, lead angle) on cutting forces in the turning process with regard to ASTM B574 (Hastelloy C-22) material has been investigated. Variance analysis has been applied in order to determine the factors affecting the cutting forces. The optimization of the parameters affecting the surface roughness has been obtained using response surface methodology (RSM) based on the Taguchi orthogonal experimental design. The accuracy of the developed models required for the estimation of the force values (Fx, Fy, Fz) is quite successful. In this study, where the R2 value has been used as the criterion/measure, accuracy values of 93.35%, 95.03%, and 95.09% have been achieved for Fx, Fy, and Fz, respectively. As a result of the ANOVA analysis, the most effective parameters for Fx at a 95% confidence interval are depth of cut, feed rate, flow, and rake angle. The most effective parameter for Fy is depth of cut, while the most effective parameters for Fz are depth of cut, feed rate, and flow, respectively.

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