scholarly journals Modeling of Cutting Parameters and Tool Geometry for Multi-Criteria Optimization of Surface Roughness and Vibration via Response Surface Methodology in Turning of AISI 5140 Steel

Materials ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 4242 ◽  
Author(s):  
Mustafa Kuntoğlu ◽  
Abdullah Aslan ◽  
Danil Yurievich Pimenov ◽  
Khaled Giasin ◽  
Tadeusz Mikolajczyk ◽  
...  

AISI 5140 is a steel alloy used for manufacturing parts of medium speed and medium load such as gears and shafts mainly used in automotive applications. Parts made from AISI 5140 steel require machining processes such as turning and milling to achieve the final part shape. Limited research has been reported on the machining vibration and surface roughness during turning of AISI 5140 in the open literature. Therefore, the main aim of this paper is to conduct a systematic study to determine the optimum cutting conditions, analysis of vibration and surface roughness under different cutting speeds, feed rates and cutting edge angles using response surface methodology (RSM). Prediction models were developed and optimum turning parameters were obtained for averaged surface roughness (Ra) and three components of vibration (axial, radial and tangential) using RSM. The results demonstrated that the feed rate was the most affecting parameter in increasing the surface roughness (69.4%) and axial vibration (65.8%) while cutting edge angle and cutting speed were dominant on radial vibration (75.5%) and tangential vibration (64.7%), respectively. In order to obtain minimum vibration for all components and surface roughness, the optimum parameters were determined as Vc = 190 m/min, f = 0.06 mm/rev, κ = 60° with high reliability (composite desirability = 90.5%). A good agreement between predicted and measured values was obtained with the developed model to predict surface roughness and vibration during turning of AISI 5140 within a 10% error range.

This paper presents the optimization in machining processes on the cutting parameters for the S45C in turning process using the response surface method (RSM). The experimental work conducted investigates the influence of cutting parameters on statistical analysis of signals and surface quality. The paper also presents a statistical analysis of signal processing. The cutting force was measured during machining using the Kistler 9129AA dynamometer to monitor the force signals and the data was analyzed using the I-kazTM method of statistical analysis. This statistical analysis was used to assess the effect of force signals during the machining process. The RSM models for Ra and Rz, and Ideveloped with ANOVA and multiple regression equations. The models also were compared and validated with the predicted and measured of Ra and Rz values, and I-kaz coefficients. The optimal configuration of cutting parameters was observed at 200 m/min, 0.1 mm/rev and 0.521 mm with desirability of 95.9%. It is observed that the models developed are suggested to be utilized for predicting surface roughness values and I-kaz coefficients for the machining of S45C steel.


2016 ◽  
Vol 686 ◽  
pp. 19-26 ◽  
Author(s):  
Ildikó Maňková ◽  
Marek Vrabeľ ◽  
Jozef Beňo ◽  
Mária Franková

Experimental research and modeling in the field of turning hardened bearing steel with hardness of 62 HRC using TiN coated mixed oxide ceramic inserts is presented. The main objective of the article is investigation the relationship between cutting parameters (cutting speed and feed rate) and output machining variables (surface roughness and cutting force components) through the response surface methodology (RSM). The mathematical model of the effect of process parameters on the cutting force components and surface roughness is presented. Moreover, the influence of TiN coating on above mentioned variables was monitored. The design of experiment according to Taguchi L9 orthogonal matrix (32) was applied for trials. Pearson´s correlation matrix was used to examine the dependence between the factors (f, vc) and the machining variables (surface roughness and cutting force components). The results show how much surface roughness and cutting force components is influenced by cutting speed and feed in hard turning with coated ceramics.


2011 ◽  
Vol 117-119 ◽  
pp. 1561-1565
Author(s):  
Muhammad Yusuf ◽  
Mohd Khairol Anuar Ariffin ◽  
N. Ismail ◽  
S. Sulaiman

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.


2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ekhaesomi A Agbonoga ◽  
Oyewole Adedipe ◽  
Uzoma G Okoro ◽  
Fidelis J Usman ◽  
Kafayat T Obanimomo ◽  
...  

This study investigated the effects of process parameters of plasma arc cutting (PAC) of low carbon steel material using analysis of variance. Three process parameters, cutting speed, cutting current and gas pressure were considered and experiments were conducted based on response surface methodology (RSM) via the box-Behnken approach. Process responses viz. surface roughness (Ra) and kerf width of cut surface were measured for each experimental run. Analysis of Variance (ANOVA) was performed to get the contribution of process parameters on responses. Cutting current has the most significant effect of 33.43% on the surface roughness and gas pressure has the most significant effect on  kerf width of  41.99% . For minimum surface roughness and minimum kerf width, process parameters were optimized using the RSM. Keywords: Cutting speed, cutting current, gas pressure,   surface roughness, kerf width


Author(s):  
János Farkas ◽  
Etele Csanády ◽  
Levente Csóka

A number of equations are available for predicting the output of machining processes. These equations are most commonly used for the prediction of surface roughness after tooling. Surface roughness can be influenced by many factors, including cutting parameters, tool geometry and environmental factors such as the coolant used. It is difficult to create a universally applicable equation for all machining because of the variations in different materials' behaviours (e.g. metal, wood, plastic, composite, ceramic). There are also many differences between the various types of machining process such as the machining tools, rotational or translational movements, cutting speeds, cutting methods, etc. The large number of parameters required would make such an equation unusable, and difficult to apply quickly. The goal is thus to create a simple formulation with three or four inputs to predict the final surface roughness of the machined part within adequate tolerances. The two main equations used for this purpose are the Bauer and Brammertz formulas, both of which need to be optimised for a given material. In this paper, the turning of thermoplastics was investigated, with the aim of tuning the Bauer formula for use with thermoplastics. Eleven different plastics were used to develop a material-dependent surface roughness equation. Only new tooling inserts were used to eliminate the effects of tool wear.


2010 ◽  
Vol 135 ◽  
pp. 243-248 ◽  
Author(s):  
Shu Han ◽  
Qing Long An ◽  
Ming Chen ◽  
Gang Liu ◽  
Yun Shan Zhang

The purpose of this study was to analyze the effects of cutting parameters on the surface roughness (Ra) when turning of alloy cast iron using uncoated carbide insert under dry cutting condition. The mathematical model for the surface roughness was developed by response surface methodology (RSM).Response surface contours were constructed and used for determining the optimum cutting conditions to reduce machining time without increasing the surface roughness.


Author(s):  
Neelesh Ku. Sahu ◽  
A. B. Andhare

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.


2016 ◽  
Vol 16 (2) ◽  
pp. 75-88 ◽  
Author(s):  
Munish Kumar Gupta ◽  
P. K. Sood ◽  
Vishal S. Sharma

AbstractIn the present work, an attempt has been made to establish the accurate surface roughness (Ra, Rq and Rz) prediction model using response surface methodology with Box–Cox transformation in turning of Titanium (Grade-II) under minimum quantity lubrication (MQL) conditions. This surface roughness model has been developed in terms of machining parameters such as cutting speed, feed rate and approach angle. Firstly, some experiments are designed and conducted to determine the optimal MQL parameters of lubricant flow rate, input pressure and compressed air flow rate. After analyzing the MQL parameter, the final experiments are performed with cubic boron nitride (CBN) tool to optimize the machining parameters for surface roughness values i. e., Ra, Rq and Rz using desirability analysis. The outcomes demonstrate that the feed rate is the most influencing factor in the surface roughness values as compared to cutting speed and approach angle. The predicted results are fairly close to experimental values and hence, the developed models using Box-Cox transformation can be used for prediction satisfactorily.


2015 ◽  
Vol 1119 ◽  
pp. 622-627 ◽  
Author(s):  
Chye Lih Tan ◽  
Azwan Iskandar Azmi ◽  
Noorhafiza Muhammad

Drilling is an essential secondary process for near net-shape of hybrid composite as to achieve the required dimensional tolerances prior to final application. Dimensional tolerance is often influenced by the surface integrity or surface roughness of the workpart. Thus, this paper aims to employ the Taguchi and response surface methodologies in minimizing the surface roughness of drilled carbon-glass hybrid fibre reinforced polymer (CGCG) using tungsten carbide, K20 drill bits. The effects of spindle speed, feed rate and tool geometry on surface roughness were evaluated and optimum cutting conditions for minimizing the aforementioned response was determined. Subsequently, response surface methodology (RSM) was utilised in finding the empirical relationships between experimental parameters and surface roughness based on the Taguchi results. The experimental analyses reveal that surface roughness is greatly influenced by feed rate and tool geometry rather than the spindle speed. This is due to the increment of feed that attributed to the increased strain rate and hence, deteriorated the surface roughness of the hybrid composite. The predicted results (via regression model) and theoretical results (via additivity law) were in good agreement with experiment results. This indicates that the regression model from response surface methodology (RSM) can be used to predict the surface roughness in machining of CGCG hybrid composite.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gökhan Sur ◽  
Ömer Erkan

Purpose Drilling of carbon fiber reinforced plastic (CFRP) composite plates with high surface quality are of great importance for assembly operations. The article aims to optimize the drill geometry and cutting parameters to improve the surface quality of CFRP composite material. In this study, CFRP plates were drilled with uncoated carbide drill bits with standard and step geometry. Thus, the effects of standard and step drill bits on surface quality have been examined comparatively. In addition, optimum output parameters were determined by Taguchi, ANOVA and multiple decision-making methods. Design/methodology/approach Drill bit point angles were selected as 90°, 110° and 130°. In cutting parameters, three different cutting speeds (25, 50 and 75 m/min) and three different feeds (0.1, 0.15 and 0.2 mm/rev) were determined. L18 orthogonal sequence was used with Taguchi experimental design. Three important output parameters affecting the surface quality are determined as thrust force, surface roughness and delamination factor. For each output parameter, the effects of drill geometry and cutting parameters were evaluated. Input parameters affecting output parameters were analyzed using the ANOVA method. Output parameters were estimated by creating regression equations. Weights were determined using the analytic hierarchy process (AHP) method, and multiple output parameters were optimized using technique for order preference by Similarity to An ideal solution (TOPSIS). Findings It has been determined from the experimental results that step drills generate smaller thrust forces than standard drills. However, it has been determined that it creates greater surface roughness and delamination factor. From the Taguchi analysis, the optimum input parameters for Fz step tool geometry, 90° point angle, 75 m/min cutting speed and 0.1 mm/rev feed. For Fd, are standard tool geometry, 90° point angle, 25 m/min cutting speed and 0.1 mm/rev feed and for Ra, are standard tool geometry, 130° point angle, 25 m/min cutting speed and 0.1 mm/rev feed. ANOVA analysis determined that the most important parameter on Fd is the tip angle, with 56.33%. The most important parameter on Ra and Fz was found to be 40.53% and 77.06% tool geometry, respectively. As a result of the optimization with multiple criteria decision-making methods, the test order that gave the best surface quality was found as 4–1-9–5-8–17-2–13-6–16-18–15-11–10-3–12-14. The results of the test number 4, which gives the best surface quality, namely, the thrust force is 91.86 N, the surface roughness is 0.75 µm and the delamination factor is 1.043. As a result of experiment number 14, which gave the worst surface quality, the thrust force was 149.88 N, the surface roughness was 3.03 µm and the delamination factor was 1.163. Practical implications Surface quality is an essential parameter in the drilling of CFRP plates. Cutting tool geometry comes first among the parameters affecting this. Therefore, different cutting tool geometries are preferred. A comparison of these cutting tools is discussed in detail. On the other hand, thrust force, delamination factor and surface roughness, which are the output parameters that determine the surface quality, have been optimized using the TOPSIS and AHP method. In this way, this situation, which seems complicated, is presented in a plain and understandable form. Originality/value In the experiments, cutting tools with different geometries are included. Comparatively, its effects on surface quality were examined. The hole damage mechanism affecting the surface quality is discussed in detail. The results were optimized by evaluating Taguchi, ANOVA, TOPSIS and AHP methods together.


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