Development of Hybrid Composites (Al-SiC-C) Through Stir Casting: Machinability Studies

2017 ◽  
Author(s):  
Satyanarayana Kosaraju ◽  
Venu Gopal Anne ◽  
Swapnil Gosavi
Keyword(s):  
Surface Roughness ◽  
Composite Materials ◽  
Cutting Force ◽  
Hybrid Composite ◽  
Hybrid Composites ◽  
Soft Materials ◽  
Graphite Powder ◽  
Stir Casting ◽  
Depth Of Cut ◽  
Grey Relational

Composite materials are important engineering materials due to their outstanding mechanical properties. Composite materials offer superior properties to conventional alloys for various applications as they have high stiffness, strength and wear resistance. The high cost and difficulty of processing these composites restricted their application and led to the development of reinforced composites. In the last two decades, wear studies on Particulate Metal Matrix Composites (PMMCs) reinforced with various reinforcements ranging from very soft materials like graphite, talc etc., to high hardened ceramic particulates like SiCp, Al2O3 etc., have been reported to be superior to their respective unreinforced alloys. Therefore, present work focused on the study of machinability of Al based binary composites reinforced with 8.5% SiC and Al based Hybrid composite reinforced with 8.5% SiC, 2% and 4% Graphite powder (Solid lubricant) have been studied by considering the effect of process parameters such as speed, feed, depth of cut and composition of material. Binary and hybrid composite materials have been casted by stir casting methodology. Experiments have been conducted using Design of Experiments approach to reduce the number of experiments and time. The cutting force and surface roughness in turning of both the binary and hybrid materials have been measured using cutting force dynamometer (4 component kistler dynamometer) and the roughness has been measured using surface roughness tester (Marsurf M400) simultaneously. The multi objective optimization has been carried out using Grey relational based Taguchi method. It was observed that feed was the most influencing factor compared to others factors and also results shown that the performance characteristics cutting force and the surface roughness are greatly enhanced by using Grey relational Analysis.

Nature instigated Grey wolf algorithm for parametric optimization during machining (Milling) of polymer nanocomposites

2021 ◽  
pp. 089270572199320
Author(s):  
Prakhar Kumar Kharwar ◽  
Rajesh Kumar Verma
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Polymer Nanocomposites ◽  
Feed Rate ◽  
Fitness Function ◽  
Depth Of Cut ◽  
Multiwall Carbon Nanotube ◽  
Grey Wolf ◽  
Milling Characteristics ◽  
The Impact

The new era of engineering society focuses on the utilization of the potential advantage of carbon nanomaterials. The machinability facets of nanocarbon materials are passing through an initial stage. This article emphasizes the machinability evaluation and optimization of Milling performances, namely Surface roughness (Ra), Cutting force (Fc), and Material removal rate (MRR) using a recently developed Grey wolf optimization algorithm (GWOA). The Taguchi theory-based L27 orthogonal array (OA) was employed for the Machining (Milling) of polymer nanocomposites reinforced by Multiwall carbon nanotube (MWCNT). The second-order polynomial equation was intended for the analysis of the model. These mathematical models were used as a fitness function in the GWOA to predict machining performances. The ANOVA outcomes efficiently explore the impact of machine parameters on Milling characteristics. The optimal combination for lower surface roughness value is 1.5 MWCNT wt.%, 1500 rpm of spindle speed, 50 mm/min of feed rate, and 3 mm depth of cut. For lower cutting force, 1.0 wt.%, 1500 rpm, 90 mm/min feed rate and 1 mm depth of cut and the maximize MRR was acquired at 0.5 wt.%, 500 rpm, 150 mm/min feed rate and 3 mm depth of cut. The deviation of the predicted value from the experimental value of Ra, Fc, and MRR are found as 2.5, 6.5 and 5.9%, respectively. The convergence plot of all Milling characteristics suggests the application potential of the GWO algorithm for quality improvement in a manufacturing environment.

OPTIMIZATION OF PROCESS PARAMETERS AFFECTING CUTTING FORCE, POWER CONSUMPTION AND SURFACE ROUGHNESS USING TAGUCHI-BASED GRAY RELATIONAL ANALYSIS IN TURNING AISI 1040 STEEL

2021 ◽  
Author(s):  
MAHIR AKGÜN
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Cutting Force ◽  
Cutting Speed ◽  
System Optimization ◽  
Gray Relational Analysis ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Significance Level ◽  
Relational Analysis

This study focuses on optimization of cutting conditions and modeling of cutting force ([Formula: see text]), power consumption ([Formula: see text]), and surface roughness ([Formula: see text]) in machining AISI 1040 steel using cutting tools with 0.4[Formula: see text]mm and 0.8[Formula: see text]mm nose radius. The turning experiments have been performed in CNC turning machining at three different cutting speeds [Formula: see text] (150, 210 and 270[Formula: see text]m/min), three different feed rates [Formula: see text] (0.12 0.18 and 0.24[Formula: see text]mm/rev), and constant depth of cut (1[Formula: see text]mm) according to Taguchi L18 orthogonal array. Kistler 9257A type dynamometer and equipment’s have been used in measuring the main cutting force ([Formula: see text]) in turning experiments. Taguchi-based gray relational analysis (GRA) was also applied to simultaneously optimize the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]). Moreover, analysis of variance (ANOVA) has been performed to determine the effect levels of the turning parameters on [Formula: see text], [Formula: see text] and [Formula: see text]. Then, the mathematical models for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) have been developed using linear and quadratic regression models. The analysis results indicate that the feed rate is the most important factor affecting [Formula: see text] and [Formula: see text], whereas the cutting speed is the most important factor affecting [Formula: see text]. Moreover, the validation tests indicate that the system optimization for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) is successfully completed with the Taguchi method at a significance level of 95%.

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

Evaluation of Cutting Force and Surface Roughness in Turning of GFRP Using Coated Carbide Insert

2015 ◽  
Vol 813-814 ◽  
pp. 317-321 ◽  
Author(s):  
C. Ramesh Kannan ◽  
P. Padmanabhan ◽  
K.P. Vasanthakumar
Keyword(s):  
Surface Roughness ◽  
Glass Fiber ◽  
Cutting Force ◽  
Chemical Vapour ◽  
Deposition Process ◽  
Depth Of Cut ◽  
Reinforced Plastics ◽  
Coated Carbide ◽  
Machining Parameter ◽  
Carbide Insert

This paper is to evaluate the cutting force and surface roughness in turning of Glass fiber reinforced plastics (E-glass fiber) using coated carbide insert. The comparison of the results with uncoated carbide inserts. The carbide insert is coated by multilayer chemical vapour deposition process, the coating elements are TiN/Al2O3/TiCN. The experiment is carried out in the conventional lathe machine under dry condition by varying the three cutting parameter such as speed, feed and depth of cut. The cutting force is measured using a lathe tool dynamometer and surface roughness are measured by using surf tester.The result of the experiment shows the effect of machining parameter on cutting force and surface roughness. The results have confirmed that the coated carbide insert has better results than uncoated and tool life is increased.

In-Process Prediction of Surface Roughness in Grinding Process by Monitoring of Cutting Force Ratio

2014 ◽  
Vol 627 ◽  
pp. 29-34 ◽  
Author(s):  
Vichaya Thammasing ◽  
Somkiat Tangjitsitcharoen
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Spindle Speed ◽  
Least Square ◽  
Depth Of Cut ◽  
Grinding Process ◽  
Average Surface Roughness ◽  
Average Surface ◽  
Developed Surface ◽  
Force Ratio

The purpose of this research is to develop the models to predict the average surface roughness and the surface roughness during the in-process grinding by monitoring the cutting force ratio. The proposed models are developed based on the experimentally obtained results by employing the exponential function with four factors, which are the spindle speed, the feed rate, the depth of cut, and the cutting force ratio. The experimentally obtained results showed that the dimensionless cutting force ratio is usable to predict the surface roughness during the grinding process, which can be calculated and obtained by taking the ratio of the corresponding time records of the cutting force Fy in the spindle speed direction to that of the cutting force Fz in the radial wheel direction. The multiple regression analysis is utilized to calculate the regression coefficients with the use of the least square method at 95% confident level. The experimentally obtained models have been verified by the new cutting tests. It is proved that the developed surface roughness models can be used to predict the in-process surface roughness with the high accuracy of 93.9% for the average surface roughness and 92.8% for the surface roughness.

scholarly journals Experimental investigation of bending characteristics of hybrid composites fabricated by hand layup method

2021 ◽  
Vol 2089 (1) ◽  
pp. 012033
Author(s):  
M Sadashiva ◽  
S Praveen Kumar ◽  
M K Yathish ◽  
V T Satish ◽  
MR Srinivasa ◽  
...  
Keyword(s):  
Composite Materials ◽  
Hybrid Composite ◽  
Polyester Resin ◽  
Hybrid Composites ◽  
Bending Test ◽  
Environment Friendly ◽  
Longitudinal Fiber ◽  
Develop Environment ◽  
The One ◽  
Better Than

Abstract The extensive applications of hybrid composite materials in the field of transportation and structural domine provide prominent advantages in the order of stiffness, strength even cost. However extend the advantages of hybrid campsites in several field such as aviation and marine even more additional properties should be inculcate in them. During production of such profitable composites poses some problems at time at decompose and processing. It’s better to develop environment friendly and reusable composites, bio hybrid composite materials such of the one. In this paper, focused on development of Eco-friendly hybrid bio composites with the ingredients of drumstick fibers, glass fiber along with polyester resin. This hybrid bio composites subjected to bending test and evaluate the characteristics of bending properties, this research evident that bending characteristics of hybrid composites with longitudinal fiber orientation better than transverse.

EXPERIMENTAL INVESTIGATION OF COCONUT OIL WITH NANOBORIC ACID DURING MILLING OF INCONEL 625 USING TAGUCHI-GREY RELATIONAL ANALYSIS

2020 ◽  
pp. 2150008
Author(s):  
T. MOHANRAJ ◽  
P. RAGAV ◽  
E. S. GOKUL ◽  
P. SENTHIL ◽  
K. S. RAGHUL ANANDH
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Flank Wear ◽  
Coconut Oil ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Individual Response ◽  
Relational Analysis ◽  
Grey Relational ◽  
Taguchi’S Design Of Experiments

This study is based on Taguchi’s design of experiments along with grey relational analysis (GRA) to optimize the milling parameters to minimize surface roughness, tool wear, and vibration during machining of Inconel-625 while using coconut oil as cutting fluid (CF). The experiments were conducted based on Taguchi’s L9 orthogonal array (OA). Taguchi’s S/N was used for identifying the optimal cutting parameter for individual response. Analysis of variance (ANOVA) was employed to analyze the outcome of individual parameters on responses. The surface roughness was mostly influenced by feed. Flank wear was influenced by speed and the vibration was mostly influenced by the depth of cut as well as speed. The multi-response optimization was done through GRA. From GRA, the optimal parameters were identified. Further, nanoboric acid of 0.5 and 0.9[Formula: see text]wt.% was mixed with coconut oil to enhance lubricant properties. Coconut oil with 0.5[Formula: see text]wt.% of nanoboric acid minimizes the surface roughness and flank wear by 3.92% and 6.28% and reduces the vibration in the [Formula: see text]-axis by 4.85%. The coconut oil with 0.5[Formula: see text]wt.% of nanoboric acid performs better than coconut oil with 0.9[Formula: see text]wt.% of nano boric acid and base oil.

scholarly journals OPTIMUM PERFORMANCE OF GREEN MACHINING ON THIN WALLED TI6AL4V USING RSM AND ANN IN TERMS OF CUTTING FORCE AND SURFACE ROUGHNESS

2019 ◽  
Vol 81 (6) ◽  
Author(s):  
Muhammad Yanis ◽  
Amrifan Saladin Mohruni ◽  
Safian Sharif ◽  
Irsyadi Yani
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Ann Model ◽  
Green Machining ◽  
Radial Depth ◽  
Thin Walled

Thin walled titanium alloys are mostly applied in the aerospace industry owing to their favorable characteristic such as high strength-to-weight ratio. Besides vibration, the friction at the cutting zone in milling of thin-walled Ti6Al4V will create inconsistencies in the cutting force and increase the surface roughness. Previous researchers reported the use of vegetable oils in machining metal as an effort towards green machining in reducing the undesirable cutting friction. Machining experiments were conducted under Minimum Quantity Lubrication (MQL) using coconut oil as cutting fluid, which has better oxidative stability than other vegetable oil. Uncoated carbide tools were used in this milling experiment. The influence of cutting speed, feed and depth of cut on cutting force and surface roughness were modeled using response surface methodology (RSM) and artificial neural network (ANN). Experimental machining results indicated that ANN model prediction was more accurate compared to the RSM model. The maximum cutting force and surface roughness values recorded are 14.89 N, and 0.161 µm under machining conditions of 125 m/min cutting speed, 0.04 mm/tooth feed, 0.25 mm radial depth of cut (DOC) and 5 mm axial DOC. 

Multi Objective Optimization of Cutting Parameters in Machining Cellulose Based Hybrid Composites

2015 ◽  
Vol 761 ◽  
pp. 287-292
Author(s):  
Raja Izamshah ◽  
Zainudin Zuraidah ◽  
Mohd Shahir Kasim ◽  
M. Hadzley ◽  
M. Amran
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Hybrid Composites ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Machining Performance ◽  
Machined Surface ◽  
Multi Objective ◽  
Optimization Of Cutting Parameters

Cellulose based hybrid composites are gaining popularity in the growing green communities. With extensive studies and increasing applications for future advancement, the need for an accurate and reliable guidance in machining this type of composites has increased enormously. Smooth and defect free machined surface are always the ultimate objectives. The present work deals with the study of machining parameters (i.e. spindle speed, feed rate and depth of cut) and their effects on machining performance (i.e. surface roughness and delamination) to establish an optimized setup of machining parameters in achieving multi objective machining performance. Cellulose based hybrid composites consist of jute (a bast fiber) and glass fiber embedded in polyester resins. Response Surface Methodology (RSM) using Box-Behnken Design (BBD) was chosen as the design of experiment approach for this study. Based on that experimental approach, 17 experimental runs were conducted. Mathematical model for each response was developed based on the experimental data. Adequacy of the models were analyzed statistically using Analysis of Variance (ANOVA) in determining the significant input variables and possible interactions. The multi objective optimization was performed through numerical optimization, and the predicted results were validated. The agreement between the experimental and selected solution was found to be strong, between 95% to 96%, thus validating the solution as the optimal machining condition. The findings suggest that feed rate was the main factor affecting surface roughness and delamination .

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.

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