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.

Optimization of flank wear and surface roughness during turning of AISI 304 stainless steel using the Taguchi method

2020 ◽  
Vol 62 (9) ◽  
pp. 957-961
Author(s):  
Nursel Altan Özbek ◽  
Metin İbrahim Karadag ◽  
Onur Özbek
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Taguchi Method ◽  
Feed Rate ◽  
Flank Wear ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
304 Stainless Steel ◽  
Aisi 304 Stainless Steel ◽  
Aisi 304

Abstract This paper presents the effect of cutting tool, cutting speed and feed rate on the flank wear and surface roughness of austenitic stainless steel (AISI 304) during wet turning. Turning tests were designed based on the Taguchi method (L18). An orthogonal array, the signal-to-noise ratio (S/N) and the ANOVA were used to investigate the machinability of AISI 304 stainless steel with PVD and CVD coated tungsten carbide inserts. As a result of ANOVA, it was found that the feed rate was the most effective parameter on both flank wear and surface roughness.

scholarly journals Optimization of Cutting Speed and Feed Rate on Surface Roughness and Vibration using Taguchi Method: A Review

2020 ◽  
Vol 1 (2) ◽  
pp. 43
Author(s):  
Mohammad Ilham ◽  
Suparjon Suparjon ◽  
Yudistira Sanjiwani
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Feed Rate ◽  
Machine Tools ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Dominant Factor ◽  
Workpiece Surface ◽  
Material Hardness ◽  
Machining Operations

<span lang="EN-ID">The result of a turning process is strongly influenced by the process parameters that could result in the product to be unacceptable. The cutting parameters may be determined according to the material hardness and roughness of the workpiece surface. The purpose of this paper is to investigate the effects of cutting speed and feed rate on surface roughness and vibration. In Taguchi method, the number of experiments is reduced by orthogonal arrays while  the effects of uncontrollable factors are also also reduced. The Taguchi method is used to reduce track, experimental time and production cost. Simple and precise are the most benefits of this method. Unstable vibrations in machining operations, known as chats, can cause damage to tools, workpieces, and machine tools. Cutting force is found to be the most dominant factor affecting surface roughness.</span>

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 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%.

scholarly journals Flank Wear Modelling in High Speed Hard Milling of AISI D2 Steel

2020 ◽  
Vol 5 (2) ◽  
pp. 50-54
Author(s):  
Muataz Al Hazza ◽  
Khadijah Muhammad
Keyword(s):  
Statistical Analysis ◽  
Wear Rate ◽  
Taguchi Method ◽  
Feed Rate ◽  
High Speed ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
High Speed Machining ◽  
Aisi D2

High speed machining has many advantages in reducing time to the market by increasing the material removal rate. However, final surface quality is one of the main challenges for manufacturers in high speed machining due to the increasing of flank wear rate. In high speed machining, the cutting zone is under high pressure associated with high temperature that lead to increasing of the flank wear rate in which affect the final quality of the machined surface. Therefore, one of the main concerns to the manufacturer is to predict the flank wear to estimate and predict the surface roughness as one of the main outputs of the machining processes. The aim of this study is to determine experimentally the optimum cutting parameters: depth of cut, cutting speed (Vc) and feed rate (f) that maintaining low flank wear (Vb). Taguchi method has been applied in this experiment. The Taguchi method has been universally used in engineering analysis.  JMP statistical analysis software is used to analyse statically the development of flank wear rate during high speed milling of hardened steel AISI D2 to 60 HRD. The experiment was conducted in the following boundaries: cutting speed 200-400 m/min, feed rate of 0.01-0.05 mm/tooth and depth of cut of 0.1-0.2 mm. Analysis of variance ANOVA was conducted as one of important tool for statistical analysis. The result showed that cutting speed is the most influential input factors with 70.04% contribution on flank wear.

scholarly journals Technics Research on Polycrystalline Cubic Boron Nitride Cutting Tools Dry Turning Ti-6AL-4V Alloy Based on Orthogonal Experimental Design

2018 ◽  
Vol 142 ◽  
pp. 03002
Author(s):  
Yunhai Jia ◽  
Lixin Zhu
Keyword(s):  
Surface Roughness ◽  
Experimental Design ◽  
Boron Nitride ◽  
Feed Rate ◽  
Flank Wear ◽  
Cubic Boron Nitride ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Orthogonal Experimental Design ◽  
Polycrystalline Cubic Boron Nitride

Ti-6Al-4V components are the most widely used titanium alloy products not only in the aerospace industry, but also for bio-medical applications. The machine-ability of titanium alloys is impaired by their high temperature chemical reactivity, low thermal conductivity and low modulus of elasticity. Polycrystalline cubic boron nitride represents a substitute tool material for turning titanium alloys due to its high hardness, wear resistance, thermal stability and hot red hardness. For determination of suitable cutting parameters in dry turning Ti-6AL-4V alloy by Polycrystalline cubic boron nitride cutting tools, the samples, 300mm in length and 100mm in diameter, were dry machined in a lathe. The turning suitable parameters, such as cutting speed, feed rate and cut depth were determined according to workpieces surface roughness and tools flank wear based on orthogonal experimental design. The experiment showed that the cutting speed in the range of 160~180 m/min, the feed rate is 0.15 mm/rev and the depth of cut is 0.20mm, ideal workpiece surface roughness and little cutting tools flank wear can be obtained.

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 Analysis and Optimization of Ceramic Cutting Tool In Hard Turning of EN-31 Using Factorial Design

2012 ◽  
pp. 53-58
Author(s):  
Chetan Darshan ◽  
Lakhvir Singh ◽  
APS Sethi
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Analysis Of Variance ◽  
Feed Rate ◽  
Hard Turning ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Good Surface ◽  
En 31

Manufacturers around the globe persistently looking for the cheapest and quality manufactured machined components to compete in the market. Good surface quality is desired for the proper functioning of the produced parts. The surface quality is influenced by cutting speed, feed rate and depth of cut and many other parameters. In the present study attempt has been made to evaluate the performance of ceramic inserts during hard turning of EN-31 steel. The analysis of variance is applied to study the effect of cutting speed, feed rate and depth of cut on Flank wear and surface roughness. Model is found to be statically significant using regression model, while feed and depth of cut are the factor affecting Flank wear and feed is dominating factors for surface roughness. The analysis of variance was used to analyze the input parameters and there interactions during machining. The developed model predicted response factor at 95% confidence level.

Wear Performance of The Zirconia Toughened Alumina Added With TiO2 and Cr2O3 Ceramic Cutting Tool

2021 ◽  
Author(s):  
Raqibah Najwa Mudzaffar ◽  
Mohamad Faiz Izzat Bahauddin ◽  
Hanisah Manshor ◽  
Ahmad Zahirani Ahmad Azhar ◽  
Nik Akmar Rejab ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tool ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Crater Wear ◽  
Machined Surface ◽  
Ceramic Cutting Tool ◽  
Zirconia Toughened Alumina

Abstract The zirconia toughened alumina enhanced with titania and chromia (ZTA-TiO2-Cr2O3) ceramic cutting tool is a new cutting tool that possesses good hardness and fracture toughness. However, the performance of the ZTA-TiO2-Cr2O3 cutting tool continues to remain unknown and therefore requires further study. In this research, the wearing of the ZTA-TiO2-Cr2O3 cutting tool and the surface roughness of the machined surface of stainless steel 316L was investigated. The experiments were conducted where the cutting speeds range between 314 to 455 m/min, a feed rate from 0.1 to 0.15 mm/rev, and a depth of cut of 0.2 mm. A CNC lathe machine was utilised to conduct the turning operation for the experiment. Additionally, analysis of the flank wear and crater wear was undertaken using an optical microscope, while the chipping area was observed via scanning electron microscopy (SEM). The surface roughness of the machined surface was measured via portable surface roughness. The lowest value of flank wear, crater wear and surface roughness obtained are 0.044 mm, 0.45 mm2, and 0.50 µm, respectively at the highest cutting speed of 455 m/min and the highest feed rate of 0.15 mm/rev. The chipping area became smaller with the increase of feed rate from 0.10 to 0.15 mm/rev and larger when the feed rate decrease. This was due to the reduced vibrations at the higher spindle speed resulting in a more stable cutting operation, thereby reducing the value of tool wear, surface roughness, and the chipping area.

scholarly journals OPTIMASI PARAMETER MESIN LASER CUTTING TERHADAP KEKASARAN DAN LAJU PEMOTONGAN PADA SUS 316L MENGGUNAKAN TAGUCHI GREY RELATIONAL ANALYSIS METHOD

2016 ◽  
Vol 11 (2) ◽  
pp. 97
Author(s):  
Rakasita R ◽  
Karuniawan BW ◽  
Anda Iviana Juniani
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Laser Cutting ◽  
Cutting Speed ◽  
Cutting Process ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Cutting Rate ◽  
Grey Relational

Optimasi parameter adalah teknik yang digunakan pada proses manufaktur untuk menghasilkan produk terbaik. Penelitian ini bertujuan untuk mengoptimasi parameter CNC laser cutting, yaitu titik fokus sinar laser, tekanan gas cutting dan cutting speed untuk mengurangi variasi terhadap respon kekasaran dan laju pemotongan pada material SUS 316L. Masing-masing parameter memiliki 3 level dan pada penelitian ini menggunakan matriks orthogonal L9 (34). Metode ANOVA dan Taguchi digunakan untuk menganalisis data hasil percobaan. Optimasi kekasaran minimum permukaan dan laju pemotongan maksimum pada proses laser cutting dilakukan dengan menggunakan Grey relational analysis. Eksperimen konfirmasi digunakan untuk membuktikan hasil optimal yang telah didapatkan dari metode Taguchi Grey relational analysis. Hasil eksperimen menunjukkan bahwa Taguchi Grey relational analysis efektif digunakan untuk mengoptimasi parameter pemesinan pada laser cutting dengan multi respon. AbstractParameter optimization is used in manufacturing as an indicator to produce the best manufacturing product. This paper studies an optimization parameters of CNC laser cutting such as focus of laser beam, pressure cutting gases and cutting speed for reducing variation of surface roughness and cutting rate on material SUS 316L. Based on L9(34) orthogonal array parameters, it is analized using ANOVA based on Taguchi method. In order to optimaze the minimum surface roughness and maximum cutting rate in laser cutting process, it is used Grey relational analysis. The confirmation experiments used to validate the optimal results that has done by Taguchi method. The results show that the Taguchi Grey relational analysis is being effective to optimize the machining parameters for laser cutting process with two responses.

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