Effect of Gel Chemistry on the Machinability of Green SiC Parts Produced by Gelcasting

2012 ◽  
Vol 727-728 ◽  
pp. 1596-1603
Author(s):  
André Marques Riviello ◽  
Fernando dos Santos Ortega
Keyword(s):  
Surface Roughness ◽  
Silicon Carbide ◽  
Statistical Analysis ◽  
Flexural Strength ◽  
Cutting Force ◽  
Complex Geometry ◽  
Automotive Components ◽  
Green Machining ◽  
Gelcasting Process

The growing interesting in the use of silicon carbide in automotive components, biomaterials, energy, among others, which demand the production of parts with complex geometry that are difficult to obtain by conventional compaction techniques, motivates the search for developing new conformation processes. Within this context, this paper investigates the production of pieces of silicon carbide through the gelcasting process and subsequent green machining of these parts. Three systems of monomers were studied: MAM-NVP-MBAM, MAM-PEG (DMA) and MAM-HMAM. The effect of the concentration of monomers, concentration of chemical initiator and the ratio of chain-forming and crosslinker monomers on the cutting force during machining and surface roughness were evaluated. These data are compared with values of flexural strength and hardness of samples produced under the same conditions. Through a statistical analysis it was determined the best formulation for the production of parts of SiC with favorable characteristics of green machining.

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. 

scholarly journals A Study on the Laser-Assisted Machining of Carbon Fiber Reinforced Silicon Carbide

Materials ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2061 ◽  
Author(s):  
Khulan Erdenechimeg ◽  
Ho-In Jeong ◽  
Choon-Man Lee
Keyword(s):  
Surface Roughness ◽  
Silicon Carbide ◽  
Carbon Fiber ◽  
Cutting Force ◽  
Ceramic Composites ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Fiber Reinforced ◽  
Laser Assisted Machining ◽  
Carbon Fiber Reinforced

In recent years, as replacements for traditional manufacturing materials, monolithic ceramics and carbon fiber reinforced silicon carbide (C/SiC) ceramic matrix composites have seen significantly increased usage due to their superior characteristics of relatively low density, lightweight, and good high temperature mechanical properties. Demand for difficult-to-cut materials is increasing in a variety of area such as the automotive and aerospace industries, but these materials are inherently difficult to process because of their high hardness and brittleness. When difficult-to-cut materials are processed by conventional machining, tool life and quality are reduced due to the high cutting force and temperatures. Laser-assisted machining (LAM) is a method of cutting a workpiece by preheating with a laser heat source and lowering the strength of the material. LAM has been studied by many researchers, but studies on LAM of carbon–ceramic composites have been carried out by only a few researchers. This paper focuses on deducing the optimal machining parameters in the LAM of C/SiC. In this study, the Taguchi method is used to obtain the major parameters for the analysis of cutting force and surface roughness under various machining conditions. Before machining experiments, finite element analysis is performed to determine the effective depth of the cut. The cutting parameters for the LAM operation are the depth of cut, preheating temperature, feed rate, and spindle speed. The signal to noise (S/N) ratio and variance analysis (ANOVA) of the cutting force and surface roughness are analyzed, and the response optimization method is used to suggest the optimal machining parameters.

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.

scholarly journals Simultaneous effects of rice husk silica and silicon carbide whiskers on the mechanical properties and morphology of sodium geopolymer

2020 ◽  
Vol 54 (29) ◽  
pp. 4611-4620 ◽  
Author(s):  
Akm Samsur Rahman ◽  
Chirag Shah ◽  
Nikhil Gupta
Keyword(s):  
Silicon Carbide ◽  
Compressive Strength ◽  
Flexural Strength ◽  
Silica Nanoparticles ◽  
Rice Husk ◽  
Silicon Carbide Whiskers ◽  
Short Beam ◽  
Spherical Silica ◽  
Beam Shear ◽  
Strength Improvement

The current research is focused on developing a geopolymer binder using rice husk ash–derived silica nanoparticles. Four types of rice husks were collected directly from various rice fields of Bangladesh in order to evaluate the pozzolanic activity and compatibility of the derived rice husk ashes with precursors of sodium-based geopolymers. Silicon carbide whiskers were introduced into sodium-based geopolymers in order to evaluate the response of silicon carbide whiskers to the interfacial bonding and strength of sodium-based geopolymers along with rice husk ashes. Compression, flexural and short beam shear tests were performed to investigate the synergistic effect of rice husk ashes–derived silica and commercially available silicon carbide whiskers. Results show that rice husk ashes–derived spherical silica nanoparticles reduced nano-porosity of the geopolymers by ∼20% and doubled the compressive strength. The simultaneous additions of rice husk ashes and silicon carbide whiskers resulted in flexural strength improvement by ∼27% and ∼97%, respectively. The increase in compressive strength due to the inclusion of silica nanoparticles is related to the reduction in porosity. The increase in flexural strength due to simultaneous inclusion of silica and silicon carbide whiskers suggest that silica particles are compatible with the metakaolin-based geopolymers, which is effective in consolidation. Finally, microscopy suggest that silicon carbide whiskers are effective in increasing bridged network and crack resistance.

scholarly journals Assessment of cutting force and surface roughness in LM6/SiC p using response surface methodology

2017 ◽  
Vol 15 (3) ◽  
pp. 283-296 ◽  
Author(s):  
Aezhisai Vallavi Muthusamy Subramanian ◽  
Mohan Das Gandhi Nachimuthu ◽  
Velmurugan Cinnasamy
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Cutting Force ◽  
Response Surface

Surface Roughness and Cutting Force Components Evaluation in Hard Turning by Differently Shaped Cutting Tools

2016 ◽  
Vol 862 ◽  
pp. 26-32 ◽  
Author(s):  
Michaela Samardžiová
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Hard Turning ◽  
Cutting Tool ◽  
Single Point ◽  
Machining Process ◽  
Tool Geometry ◽  
Machined Surface ◽  
Cutting Force Components ◽  
Force Components

There is a difference in machining by the cutting tool with defined geometry and undefined geometry. That is one of the reasons of implementation of hard turning into the machining process. In current manufacturing processes is hard turning many times used as a fine finish operation. It has many advantages – machining by single point cutting tool, high productivity, flexibility, ability to produce parts with complex shapes at one clamping. Very important is to solve machined surface quality. There is a possibility to use wiper geometry in hard turning process to achieve 3 – 4 times lower surface roughness values. Cutting parameters influence cutting process as well as cutting tool geometry. It is necessary to take into consideration cutting force components as well. Issue of the use of wiper geometry has been still insufficiently researched.

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%.

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