Investigation of the effect of cutting parameters on the milling process of cryogenically treated aluminum alloy with cryogenically treated and untreated inserts, using the Taguchi and Gray Relational Analysis methods

2021 ◽  
Author(s):  
Gürcan Samtaş ◽  
Berat Serhat Bektaş
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
Gray Relational Analysis ◽  
Taguchi Optimization ◽  
Relational Analysis ◽  
Cutting Insert ◽  
Cutting Inserts

Abstract The aluminum 6061 alloy is commonly employed in the automotive industry in the manufacture of rims, panels and even the chasses of vehicles and has excellent machinability. In this study, the surface of the cryogenically processed aluminum 6061-T651 alloy was milled using both untreated and cryogenically treated TiN-TiCN-Al2O3-coated cutting inserts. The Taguchi L18 orthogonal array was chosen as the experimental design. As the cutting parameters in the experiments, two different cutting inserts (untreated and cryogenically treated, TiN-TiCN-Al2O3-coated), three different cutting speeds (250, 350 and 450 m/min) and three different feed rates (0.15, 0.30 and 0.45 mm/rev) were used. After each experiment, the surface roughness and wear values of the cutting inserts were measured, the latter after repeating the experiment five times. Wear and roughness values were optimized using the Taguchi method. Additionally, Gray Relational Analysis (GRA) was used for the combined optimization of wear and roughness values. The optimized findings determined using Taguchi optimization for minimum surface roughness were the cryogenically treated cutting insert, 250 m/min cutting speed and 0.45 mm/rev feed rate. The optimized findings for wear were the cryogenically treated cutting insert, 350 m/min cutting speed and 0.30 mm/rev feed rate. In the optimization with GRA, the common optimum parameters for surface roughness and wear were the cryogenically treated cutting insert, 250 m/min cutting speed and 0.15 mm/rev feed rate. According to the Taguchi and GRA results, the cryogenically treated cutting inserts performed the best in terms of minimum wear and surface roughness. The Gray-based Taguchi methodology proposed in this study was found to be effective in solving the decision-making problem in multi-specific results as wear and surface roughness.

OPTIMIZATION OF THE MACHINING PARAMETERS IN TURNING OF HARDENED HOT WORK TOOL STEEL USING CRYOGENICALLY TREATED TOOLS

2019 ◽  
Vol 27 (05) ◽  
pp. 1950177 ◽  
Author(s):  
ENGIN NAS ◽  
NURSEL ALTAN ÖZBEK
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Feed Rate ◽  
Flank Wear ◽  
Cutting Speed ◽  
Gray Relational Analysis ◽  
Dominant Factor ◽  
Relational Analysis ◽  
Hot Work Tool Steel

This paper addresses an approach based on the Taguchi method with gray relational analysis for optimizing the turning parameters of hardened DIN 1.2344 hot work tool steel (54 HRC) with multiple performance characteristics. A gray relational grade obtained from the gray relational analysis was used for the performance characteristic in the Taguchi method L[Formula: see text] (2[Formula: see text]. The optimal turning parameters for surface roughness and tool wear were determined using the parameter design proposed by the Taguchi method. Dry turning tests were carried out using cryogenically treated and untreated uncoated carbide cutting tools. The cutting tool (Untreated and Deep Cryogenic Treated), cutting speed (200, 250 and 300[Formula: see text]m/min) and feed rate (0.09, 0.12 and 0.15[Formula: see text]mm/rev) were selected as experiment parameters. The analysis results revealed that the feed rate (72.84%) was the dominant factor affecting surface roughness and the cutting speed (93.93%) was the dominant factor affecting flank wear. The optimum turning parameters for the lowest Ra values were A2B1C2 and for the lowest Vb values were A1B3C2. According to the results of gray relational analysis, the optimum parameters for minimum average surface roughness and minimum flank wear were A1B2C2.

scholarly journals Effect of Cutting Insert Type on Surface Roughness of Hardened AISI 420 Stainless Steel

2021 ◽  
Vol 4 (1) ◽  
pp. 171-185
Author(s):  
Anıl Berk Dalkıran ◽  
Furkan Yılmaz ◽  
Samet Emre Bilim
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Feed Rate ◽  
Cutting Speed ◽  
High Strength ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 420 ◽  
Cutting Insert ◽  
Coated Carbide

AISI 420 stainless steel is one of the alloys that can be used in various applications due to its malleability, high strength, and weldability. In this study, the effects of cutting parameters (feed rate, depth of cut, and cutting speed) on the surface roughness were investigated during the turning of AISI 420 under dry test conditions using coated carbide and ceramic cutting inserts. Response surface methodology, analysis of variance, and statistical methods of the main effect plot were applied to investigate the effects of input parameters on response values. The results of this study showed that feed rate followed by the depth of cut had the most significant effect on output parameters. According to the experimental data, as the feed rate and depth of cut increase, the surface roughness increases.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

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

scholarly journals Application of Gray Relation Analysis for Multi-Response Optimization of Plasma Heat Assisted Turning Performance

2018 ◽  
Vol 7 (2.32) ◽  
pp. 143
Author(s):  
Thella Babu Rao ◽  
Venu Pilli ◽  
Nallamotu Revanth Sai Venkat ◽  
Nagandla Pavan ◽  
Thalari Shiva Ram
Keyword(s):  
Surface Roughness ◽  
Plasma Heating ◽  
Cutting Speed ◽  
Gray Relational Analysis ◽  
Machining Performance ◽  
Relational Analysis ◽  
Gray Relation Analysis ◽  
Cutting Length ◽  
Response Optimization ◽  
Hardened En24

This paper presents optimization of plasma heat assisted turning process for machining hardened EN24 die steel (53HRC) by using gray relational analysis. Flank wear and surface roughness (Ra) are experimentally measured as the process performance characteristics under varying conditions of preheating temperature, cutting speed and cutting length. The plasma heating approach was implemented to preheat the workpiece. The machining experiments were conducted according to the L16 design of experiments. Since the chosen machining performance indicators are found with confliction for the chosen process variables, the problem is treated as multi-response optimization problem to minimize the tool wear and surface roughness simultaneously. Therefore, the problem was solved by implementing the gray relational analysis and the derived optimal machining conditions were analysed and reported.  

scholarly journals Investigations on Surface Roughness and Tool Wear Characteristics in Micro-Turning of Ti-6Al-4V Alloy

Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2998 ◽  
Author(s):  
Kubilay Aslantas ◽  
Mohd Danish ◽  
Ahmet Hasçelik ◽  
Mozammel Mia ◽  
Munish Gupta ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Removal Rate ◽  
Cutting Speed ◽  
Small Diameter ◽  
Cutting Parameters ◽  
Ti6al4v Alloy ◽  
Depth Of Cut ◽  
Turning Process ◽  
Micro Turning

Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.

A Prediction Model of Surface Roughness in Micro End Milling

2015 ◽  
Vol 727-728 ◽  
pp. 354-357
Author(s):  
Mei Xia Yuan ◽  
Xi Bin Wang ◽  
Li Jiao ◽  
Yan Li
Keyword(s):  
Surface Roughness ◽  
Prediction Model ◽  
Feed Rate ◽  
End Milling ◽  
Orthogonal Experiment ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Micro Milling ◽  
Cutting Depth ◽  
Micro End Milling

Micro-milling orthogonal experiment of micro plane was done in mesoscale. Probability statistics and multiple regression principle were used to establish the surface roughness prediction model about cutting speed, feed rate and cutting depth, and the significant test of regression equation was done. On the basis of successfully building the prediction model of surface roughness, the diagram of surface roughness and cutting parameters was intuitively built, and then the effect of the cutting speed, feed rate and cutting depth on the small structure surface roughness was obtained.

scholarly journals Experimental Investigation on Surface Roughness and Tool Wear in Dry Machining of TiC Reinforced Aluminium LM6 Composite

2013 ◽  
Vol 773-774 ◽  
pp. 339-347 ◽  
Author(s):  
Muhammad Yusuf ◽  
M.K.A. Ariffin ◽  
N. Ismail ◽  
S. Sulaiman
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Carbide Tool ◽  
Dry Machining ◽  
Workpiece Surface ◽  
High Cutting Speed

With increasing quantities of applications of Metal Matrix Composites (MMCs), the machinablity of these materials has become important for investigation. This paper presents an investigation of surface roughness and tool wear in dry machining of aluminium LM6-TiC composite using uncoated carbide tool. The experiments carried out consisted of different cutting models based on combination of cutting speed, feed rate and depth of cut as the parameters of cutting process. The cutting models designed based on the Design of Experiment Response Surface Methodology. The objective of this research is finding the optimum cutting parameters based on workpiece surface roughness and cutting tool wear. The results indicated that the optimum workpiece surface roughness was found at high cutting speed of 250 m min-1 with various feed rate within range of 0.05 to 0.2 mm rev-1, and depth of cut within range of 0.5 to 1.5 mm. Turning operation at high cutting speed of 250 m min-1 produced faster tool wear as compared to low cutting speed of 175 m min-1 and 100 m min-1. The wear minimum (VB = 42 μm ) was found at cutting speed of 100 m min-1, feet rate of 0.2 mm rev-1, and depth of cut of 1.0 mm until the length of cut reached 4050 mm. Based on the results of the workpiece surface roughness and the tool flank wear, recommended that turning of LM6 aluminium with 2 wt % TiC composite using uncoated carbide tool should be carried out at cutting speed higher than 175 m min-1 but at feed rate of less than 0.05 mm rev-1 and depth of cut less than 1.0 mm.

Studies Regarding the Influence on the Surface Roughness Material of the Cutting Regime during the Milling Processing

2015 ◽  
Vol 1128 ◽  
pp. 271-281 ◽  
Author(s):  
Mihai Demian ◽  
Luminita Grecu ◽  
Gabriela Demian
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Optimal Parameter ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Error Variance ◽  
Milling Process ◽  
Depth Of Cut ◽  
Low Level ◽  
First Case

The aim of the present paper is to establish the optimal parameter values of the cutting regime of a milling process. The paper presents a study regarding the influence of the cutting parameters on the surface roughness of the material and also on the vibration generated by their combinations, during a processing by milling. The studies are made on samples made from S355 JR steel with a metal milling machine FUS 25, which is used also for the experiments. The samples dimensions are 210x150x16mm. For the experiments there was used a cylindrical - frontal milling tool, with 32mm diameter and 10 tooth. Basic parameters of milling processing of materials we have considered in this paper are: feed rate [mm/min]; cutting speed RPM [rot/min]; depth of cut [mm]. For each of this parameters three levels were envisaged. For a 100% accurate experiment results at least 27 experiments must be done. Using an L9 orthogonal array, the number of experiments is reduced to nine and the accurate of the method is around 99.96%. The optimal process parameters values are obtained using Taguchi method considering three situations. In the first case the goal is to get only a fine roughness for the sample. The second studied case is focused on finding a low level for the vibration generated during the milling process. The aim of the last study is to find a fine roughness and also a low level of vibration for the process. The analysis of variance (ANOVA) is applied, in all cases, in order to estimate the error variance and to rank the process parameters according to their importance.

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