scholarly journals Optimization of Surface Roughness of Turned Nano-Khorasan Based Madar Fiber Composites Using Response Surface Methodology

2019 ◽  
Vol 8 (10) ◽  
pp. 253-257
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Natural Fiber ◽  
Relative Effect ◽  
Experimental Result ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Fiber Reinforced ◽  
Reinforced Polymer

Now a day Nano based Natural Fiber Reinforced Polymer (NFRP) composite is important alternative material to conventional materials because of its superior characteristics. In general composite products are manufactured nearer to the required shape, but secondary operations like machining is necessary to obtain the required surface finish. Machining of NFRP composites is different than the machining of traditional materials. This paper focuses on the behavior and optimization of machining parameters on turning of Nano-Khorasan based madar fiber reinforced composites by using Response Surface Methodology (RSM) technique. The input factors studied are speed, feed, depth of cut and Nano-Khorasan mixing. The investigated output response was Average Surface Roughness (Ra). A Box- Behnken approach was employed to evaluate the optimum parameters to attain the minimum Ra. Based on this approach, a second order polynomial modal equation was generated for predicting response Ra. Also the relative effect of parameters on response Ra was studied by using ANOVA. The experimental result shows some interesting factors in context to the turning of Nano Khorasan based Madarfiber reinforced polymer composites

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization by Response Surface Methodology

2011 ◽  
Vol 189-193 ◽  
pp. 1376-1381
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou El Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Ceramic ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents the prediction of a statistically analyzed model for the surface roughness,R_a of end-milled Machinable glass ceramic (MGC). Response Surface Methodology (RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is found that cutting speed is the most significant factor contributing to the surface roughness value followed by the depth of cut and feed rate. The surface roughness value decreases for higher cutting speed along with lower feed and depth of cut. Additionally, the process optimization has also been done in terms of material removal rate (MRR) to the model’s response. Ideal combinations of machining parameters are then suggested for common goal to achieve lower surface roughness value and higher MRR.

scholarly journals Optimization of Machining Parameters of Aluminum Alloy BS-1474 2014 A using Response Surface Methodology

2020 ◽  
Author(s):  
waqas javaid ◽  
Tauqeer Iqbal ◽  
Ammar ul Hassan
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Aluminum Alloy ◽  
Response Surface ◽  
Removal Rate ◽  
Machining Process ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process

Abstract High surface quality, optimum Material Removal Rate (MRR) and Tool-Chip Interface temperature (T c ) have significant importance in machining process. Similarly, dimensional accuracy in machining process also relies heavily on machining parameters. In machining operations, there are a number of parameters which have direct or indirect effect on the Surface Roughness (Ra) and MRR of the product. The surface roughness and MRR in turning process are affected by spindle speed (SS), feed rate (FR) and depth of cut (DOC). The optimization of turning parameters will be very helpful in improving quality of manufacturing and machining cost. In order to have an improved product, extensive research has been carried out to optimize machining process. The current research is focused at Response Surface Methodology (RSM) of turning process of Aluminum alloy (BS-1474 2014 A) by using variable sets of machining parameters i.e., SS, FR and DOC with carbide tipped tool. Multiple experiments were performed on CNC Lathe machine by using different combinations of process parameters. Response surface methodology was applied to reach theoretical values of the responses parameters (i.e, Ra, MRR, T c ) and an agreement was observed between actual machining results and methodology values. Design Expert-7 was used as a statistical tool to come to a conclusion on whether achieved results are optimum for turning process or otherwise. For a close correlation, comparison between hypothetical and investigational data is also the part of this research. Significant agreement between theoretically optimized machining parameters and experimental data has been observed.

Investigating and Modeling the Machinability of Al 6061 Using Response Surface Methodology

2015 ◽  
Vol 761 ◽  
pp. 267-272
Author(s):  
Basim A. Khidhir ◽  
Ayad F. Shahab ◽  
Sadiq E. Abdullah ◽  
Barzan A. Saeed
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Effect Of Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process

Decreasing the effect of temperature, surface roughness and vibration amplitude during turning process will improve machinability. Mathematical model has been developed to predict responses of the surface roughness, temperature and vibration in relation to machining parameters such as the cutting speed, feed rate, and depth of cut. The Box-Behnken First order and second-order response surface methodology was employed to create a mathematical model, and the adequacy of the model was verified using analysis of variance. The experiments were conducted on aluminium 6061 by cemented carbide. The direct and interaction effect of the machining parameters with responses were analyzed. It was found that the feed rate, cutting speed, and depth of cut played a major role on the responses, such as the surface roughness and temperature when machining mild steel AISI 1018. This analysis helped to select the process parameters to improve machinability, which reduces cost and time of the turning process.

scholarly journals Modeling and optimization of finish diamond turning of spherical surfaces based on response surface methodology and cuckoo search algorithm

2021 ◽  
Vol 16 (3) ◽  
pp. 326-334
Author(s):  
D. Kramar ◽  
Dj. Cica
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Quality ◽  
Spherical Surface ◽  
Cuckoo Search ◽  
Diamond Turning ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Machining Parameters

Surface roughness is one of the most significant factors to indicate the product quality. Diamond turning is an efficient and highly accurate material removal process to improve the surface quality of the workpiece. In the present study, the arithmetic mean absolute roughness (Ra) and total height of profile (Rt) of spherical surface during finish turning of a commercial brass alloy CuZn40Pb2 were modeled using Response Surface Methodology (RSM). The experimental investigations were carried out using the Central Composite Design (CCD) under dry conditions. The effect of cutting parameters such as spindle speed, feed rate and depth of cut) on spherical surface quality was analyzed using analysis of variance (ANOVA). A cuckoo search (CS) algorithm was used to determine the optimum machining parameters to minimize the surface roughness. Finally, confirmation experiments were carried out to verify the adequacy of the considered optimization algorithm.

Investigation of Machining Parameters in CNC Turning of EN3 Low Carbon Steel Using Genetic Algorithm and Response Surface Methodology

2014 ◽  
Vol 592-594 ◽  
pp. 883-887
Author(s):  
R. Rave Kumar ◽  
M. Mohamed Abdul Hafeez ◽  
K. Velmanirajan ◽  
K. Nantha Kumar
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Carbon Steel ◽  
Response Surface ◽  
Low Carbon Steel ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Low Carbon

Burrs are bottleneck of precision machining and automation production. Burrs are formed in every edges and faces, during the turning process, which affects the quality level of surface roughness. In this paper the experimental study of EN3 low carbon steel were carried out to minimize the surface roughness using response surface methodology and genetic algorithm. Tungsten Carbide was used as a cutting tool for this turning operation. Machined samples are examined under Scanning Electron Microscope (SEM) for burr formation. A wide variety of analysis between cutting parameters have been shown graphically. The minimization of burr was achieved and hence better surface quality was obtained by optimizing the cutting parameters like cutting speed, feed, and depth of cut, with the aid of Genetic Algorithm (GA) & Response Surface Methodology (RSM) Techniques.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

Parameter Optimization of Ball End Milling Process on Inconel 718 Using RSM and TLBO Algorithm

2015 ◽  
Vol 15 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Integrity ◽  
Inconel 718 ◽  
Tool Path ◽  
End Milling ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Ball End Milling

AbstractThis paper presents the application of Response Surface Methodology (RSM) coupled with Teaching Learning Based Optimization Technique (TLBO) for optimizing surface integrity of thin cantilever type Inconel 718 workpiece in ball end milling. The machining and tool related parameters like spindle speed, milling feed, axial depth of cut and tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate. Mathematical relationship between process parameters and deflection, surface roughness and microhardness are found out by using response surface methodology. It is observed that after optimizing the process that at the spindle speed of 2,000 rpm, feed 0.05 mm/tooth/rev, plate thickness of 5.5 mm and 15° workpiece inclination with horizontal tool path gives favorable surface integrity.

scholarly journals Prediction of Machining Characteristics of Hybrid Composites Using Response Surface Methodology Approach

2018 ◽  
Vol 7 (3.1) ◽  
pp. 162 ◽  
Author(s):  
Ramanan. G ◽  
Rajesh Prabha.N ◽  
Diju Samuel.G ◽  
Jai Aultrin. K. S ◽  
M Ramachandran
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Hybrid Composites ◽  
Removal Rate ◽  
Cutting Speed ◽  
Chemical Properties ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimal Parameters ◽  
Rsm Technique

This manuscript presents the influencing parameters of CNC turning conditions to get high removal rate and minimal response of surface roughness in turning of AA7075-TiC-MoS2 composite by response surface method. These composites are particularly suited for applications that require higher strength, dimensional stability and enhanced structural rigidity. Composite materials are engineered materials made from at least two or more constituent materials having different physical or chemical properties. In this work seventeen turning experiments were conducted using response surface methodology. The machining parameters cutting speed, feed rate, and depth of cut are varied with respect to different machining conditions for each run. The optimal parameters were predicted by RSM technique. Turning process is studied by response surface methodology design of experiment. The optimal parameters were predicted by RSM technique. The most influencing process parameter predicted from RSM techniques in cutting speed and depth of cut.   

Sign in / Sign up

Export Citation Format

Share Document