scholarly journals Application of response surface methodology and fuzzy logic based system for determining metal cutting temperature

2016 ◽  
Vol 64 (2) ◽  
pp. 435-445 ◽  
Author(s):  
D. Tanikić ◽  
V. Marinković ◽  
M. Manić ◽  
G. Devedžić ◽  
S. Ranđelović
Keyword(s):  
Response Surface Methodology ◽  
Fuzzy Logic ◽  
Response Surface ◽  
Metal Cutting ◽  
Single Point ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Cutting Regimes

Abstract The heat produced in metal cutting process has negative influence on the cutting tool and the machined part in many aspects. This paper deals with measurement of cutting temperature during single-point dry machining of the AISI 4140 steel, using an infrared camera. Various combinations of cutting parameters, i.e. cutting speed, feed rate and depth of cut lead to different values of the measured cutting temperature. Analysis of the measured data should explain the trends in temperature changes depending on changes in the cutting regimes. Furthermore, the temperature data is modelled using response surface methodology and fuzzy logic. The models obtained should determine the influence of cutting regimes on cutting temperature. The main objective is the reduction of cutting temperature, i.e. enabling metal cutting process in optimum conditions.

scholarly journals Optimization of Cutting Parameters on Turning Process Based on Surface Roughness Using Response Surface Methodology

2011 ◽  
Vol 117-119 ◽  
pp. 1561-1565
Author(s):  
Muhammad Yusuf ◽  
Mohd Khairol Anuar Ariffin ◽  
N. Ismail ◽  
S. Sulaiman
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting ◽  
Optimization Of Cutting Parameters

This paper describes effect of cutting parameters on surface roughness for turning of aluminium alloy 7050 using carbide cutting tool with dry cutting condition. The model is developed based on cutting speed, feed rate and depth of cut as the parameters of cutting process. The selection of cutting process was based on the design of experiments Response Surface Methodology (RSM). The objective of this research is finding the optimum cutting parameters based on surface roughness. The relation between cutting parameters and surface roughness were discussed.

Modeling and Optimization of Vibration Amplitude in Turning of Ti-6Al-4V Using Response Surface Methodology

2012 ◽  
Vol 217-219 ◽  
pp. 1567-1570
Author(s):  
A.K.M. Nurul Amin ◽  
Muammer Din Arif ◽  
Syidatul Akma Sulaiman
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Vibration Amplitude ◽  
Desirability Function ◽  
Cutting Speed ◽  
Vibration Sensor ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Work Piece ◽  
Inferior Surface

Chatter is detrimental to turning operations and leads to inferior surface topography, reduced productivity, dimensional accuracy, and shortened tool life. Avoidance of chatter has mostly been through reliance on heuristics such as: limiting material removal rates or selecting low spindle speeds and shallow depth of cuts. But, modern industries demand increased output and not steady operational limits. Various research efforts have therefore focused on developing mathematical models for chatter formation. However, as yet there is no existent model that meets all experimental verification. This research employed a novel technique based on the synergy of statistical modeling and experimental investigations in order to develop an effective empirical mathematical model for chatter amplitude and to subsequently find optimal machining conditions. Ti-6Al-4V, Titanium alloy, was used as the work-piece due to its increased popularity in applications related to aerospace, automotive, nuclear, medical, marine etc. A sequence of 15 experimental runs was conducted based on a small Central Composite Design (CCD) model in Response Surface Methodology (RSM). The primary (independent) parameters were: cutting speed, feed, and depth of cut. The tool overhang was kept constant at 70 mm. An engine lathe (Harrison M390) was employed for turning purposes. The data acquisition system comprised a vibration sensor (accelerometer) and a signal conditioning unit. The resultant vibrations were analyzed using the DASYLab 5.6 software. The best model was found to be quadratic which had a confidence level of 95% (ANOVA) and insignificant Lack of Fit (LOF) in Fit and Summary analyses. Desirability Function (DF) approach predicted minimum vibration amplitude of 0.0276 Volts and overlay plots identified two preferred machining regimes for optimal vibration amplitude.

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.   

Optimization of Surface Roughness in Turning of Ti-6Al-4V Using Response Surface Methodology and TLBO

2015 ◽  
Author(s):  
Neelesh Ku. Sahu ◽  
A. B. Andhare
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Titanium Alloys ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Maximum Error ◽  
Depth Of Cut ◽  
Interaction Variables ◽  
Teaching Learning

Surface roughness is an important surface integrity parameter for difficult to cut alloys such as Titanium alloys (Ti-6Al-4V). In the present work, initially a mathematical model is developed for predicting surface roughness for turning operation using Response Surface Methodology (RSM). Later, a recently developed advanced optimization algorithm named as Teaching Learning Based Optimization (TLBO) is used for further parameter optimization of the equation developed using RSM. The design of experiments was performed using central composite design (CCD). Analysis of variance (ANOVA) demonstrated the significant and non-significant parameters as well as validity of predicted model. RSM describes the effect of main and mixed (interaction) variables on the surface roughness of titanium alloys. RSM analysis over experimental results showed that surface roughness decreased as cutting speed increased whereas it increased with increase in feed rate. Depth of cut had no effect on surface roughness. By comparing the predicted and measured values of surface roughness the maximum error was found to be 7.447 %. It indicates that the developed model can be effectively used to predict the surface roughness. Further optimization of the roughness equation was carried out by TLBO method. It gave minimum surface roughness as 0.3120 μm at the cutting speed of 1704 RPM (171.217 m/min), feed rate of 55.6 mm/min (.033 mm/rev) and depth of cut of 0.7 mm. These results were confirmed by confirmation experiment and were better than that of RSM.

Prediction the Influence of Machining Parameters for CNC Turning of Aluminum Alloy Using RSM and ANN

2020 ◽  
Vol 38 (6A) ◽  
pp. 887-895
Author(s):  
Hind H. Abdulridha ◽  
Aseel J. Haleel ◽  
Ahmed A. Al-duroobi
Keyword(s):  
Response Surface Methodology ◽  
Aluminum Alloy ◽  
Prediction Model ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Rsm Model ◽  
Good Agreement

The main objective of this paper is to develop a prediction model using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) for the turning process of Aluminum alloy 6061 round rod. The turning experiments carried out based on the Central Composite Design (CCD) of Response Surface Methodology. The influence of three independent variables such as Cutting speed (150, 175 and 200 mm/ min), depth of cut (0.5, 1 and 1.5 mm) and feed rate (0.1, 0.2 and 0.3 mm/rev) on the Surface Roughness (Ra) were analyzed through analysis of variance (ANOVA). The response graphs from the Analysis of Variance (ANOVA) present that feed-rate has the strongest influence on Ra dependent on cutting speed and depth of cut. Surface response methodology developed between the machining parameters and response and confirmation experiments reveals that the good agreement with the regression models. The coefficient of determination value for RSM model is found to be high (R2 = 0.961). It indicates the goodness of fit for the model and high significance of the model. From the result, the maximum error between the experimental value and ANN model is less than the RSM model significantly. However, if the test patterns number will be increased then this error can be further minimized. The proposed RSM and ANN prediction model sufficiently predict Ra accurately. However, ANN prediction model is found to be better compared to RSM model. The artificial neutral network is applied to experimental results to find prediction results for two response parameters. The predicted results taken from ANN show a good agreement between experimental and predicted values with the mean squared error of training indices equal to (0.000) which produces flexibility to the manufacturing industries to select the best setting based on applications.

Finite Element Analysis of Ultrasonic Vibration Assisted Turning of Ferrous Metals

2013 ◽  
Vol 567 ◽  
pp. 33-38 ◽  
Author(s):  
Lai Zou ◽  
Ming Zhou
Keyword(s):  
Finite Element ◽  
Tool Wear ◽  
Ultrasonic Vibration ◽  
Single Point ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Diamond Turning ◽  
Depth Of Cut ◽  
Technological Parameters ◽  
Ferrous Metals

Ultrasonic vibration assisted turning has significant improvements in processing of intractable materials compared to conventional turning. This paper presents a theoretical investigation of tool wear in single point diamond turning of ferrous metals based on numerical simulation. Finite element modeling and simulation of ultrasonic vibration turning process were performed, aimed at optimizing a series of technological parameters in the process of machining, reducing tool wear and improving surface quality as much as possible. The results revealed that the cutting speed and depth of cut are two crucial factors for tool wear, unlike the other parameters of vibration frequency, amplitude and flank angle. Moreover, this technological measure has observably decreased the cutting force and cutting temperature, so as to obtain superior surface finish.

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.

A Fractal Analysis of Cutting Force in Simulation and Experiment

2013 ◽  
Vol 589-590 ◽  
pp. 122-127 ◽  
Author(s):  
Guang Ming Zheng ◽  
Jun Zhao ◽  
Xin Yu Song ◽  
Xiang Cheng
Keyword(s):  
Fractal Dimension ◽  
Cutting Force ◽  
Fractal Analysis ◽  
Metal Cutting ◽  
Cutting Speed ◽  
Element Model ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Practical Implementation ◽  
Mechanical Coupling

A 3D finite element model (FEM) of metal cutting was constructed based on the thermal-mechanical coupling theory. The cutting process of Sialon ceramic tools turning Inconel 718 was simulated and experimented. The effect of cutting speed, feed rate and depth of cut on the cutting force was analyzed. According to the correlation characteristics between the data points, the fractal characteristics of cutting forces in the cutting process were also investigated. The results showed that the cutting speed had a great effect on the fractal dimension of cutting force. The simulation results were in good agreement with the experimental findings. It was concluded that the minimum fractal dimension of cutting force was obtained at v=230 m/min under these experiment conditions. The fractal analysis is a simple and powerful tool for quantifying the stability of cutting process. The finding of this research is valuable for future practical implementation.

scholarly journals EFFECT OF CUTTING SPEED IN THE TURNING PROCESS OF AISI 1045 STEEL ON CUTTING FORCE AND BUILT-UP EDGE (BUE) CHARACTERISTICS OF CARBIDE CUTTING TOOL

SINERGI ◽  
2020 ◽  
Vol 24 (3) ◽  
pp. 171
Author(s):  
Sobron Yamin Lubis ◽  
Sofyan Djamil ◽  
Yehezkiel Kurniawan Zebua
Keyword(s):  
Cutting Force ◽  
Metal Cutting ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Aisi 1045 Steel ◽  
1045 Steel

In the machining of metal cutting, cutting tools are the main things that must be considered. Using improper cutting parameters can cause damage to the cutting tool. The damage is Built-Up Edge (BUE). The situation is undesirable in the metal cutting process because it can interfere with machining, and the surface roughness value of the workpiece becomes higher. This study aimed to determine the effect of cutting speed on BUE that occurred and the cutting strength caused. Five cutting speed variants are used. Observation of the BUE process is done visually, whereas to determine the size of BUE using a digital microscope. If a cutting tool occurs BUE, then the cutting process is stopped, and measurements are made. This study uses variations in cutting speed consisting of cutting speed 141, 142, 148, 157, 163, and 169 m/min, and depth of cut 0.4 mm. From the results of the study were obtained that the biggest feeding force is at cutting speed 141 m/min at 347 N, and the largest cutting force value is 239 N with the dimension of BUE length: 1.56 mm, width: 1.35 mm, high: 0.56mm.

scholarly journals MODELLING OF RESPONSES FROM ORTHOGONAL METAL CUTTING OF MILD STEEL USING CARBIDE INSERT TOOL

2016 ◽  
Vol 36 (1) ◽  
pp. 96-109
Author(s):  
MK Onifade ◽  
AC Igboanugo ◽  
JO Osarenmwinda
Keyword(s):  
Mild Steel ◽  
Representative Sample ◽  
Metal Cutting ◽  
Orthogonal Cutting ◽  
Cutting Speed ◽  
Industrial Applications ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Orthogonal Metal Cutting

The purpose of this research was to develop models for the prediction of responses from orthogonal metal cutting process that are responsible for the machinability ratings of this technological system. Mild steel work-piece material that is representative sample for various industrial applications was machined. The various industrial applications of this representative sample range from mechanical shafts to fasteners, screws and hydraulic jack. These machine elements require high degree of surface finish. A fifteen-run based Box-Behnken response surface design was created using widely established machining parameters, namely cutting speed, feed rate and depth of cut. The optimum predicted responses from the orthogonal cutting process for the optimal process parameters are 0.1742 micron, 0.4933 micron, 0.1845 micron, 0.3673 micron, 794.6839 seconds and 19.642 seconds for the Ra, Rz, Rq, Rt, TL and M/C time respectively. The associated desirabilities for these optimum responses are 1.000000, 1.000000, 1.000000, 1.000000, 0.524122, and 0.361858 respectively.   http://dx.doi.org/10.4314/njt.v36i1.13

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