Experimental Investigation of Effects of Feed Rate and Cutting Speed on Surface Roughness and Cutting Tool Wear in Drilling of AISI 4140 Steel Workpieces Hardened up to 30 HRC using Solid Carbide Drills

2020 ◽  
Author(s):  
Ömer ŞAHİN ◽  
Erdinç KALUÇ
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cooling Water ◽  
Measurement Instrument ◽  
Cutting Tool Wear ◽  
Aisi 4140 ◽  
Solid Carbide

Abstract In this study, effects of feed rate and cutting speed on surface roughness and cutting tool wear were investigated in drilling of AISI 4140 tempered steel workpieces with internally cooled, Ø14 mm diameter solid carbide drills on a CNC lathe. Although there are various literature on this subject, since there is no information on the experimental parameters that the study has been done, the contribution and originality of the study to the literature is to be qualitative.The experimental study was conducted using cooling water and with cutting speeds of 50, 60, 70, and 80 m/min and feed rate parameters of 0.10, 0.15, 0.20, and 0.25 mm/rev. At the end of the experiment, wear of the used drills was monitored with a material microscope and wear values were determined. Surface roughness of the holes was measured with Mitutoyo branded surface roughness measurement instrument. The longest drill life was obtained at 50 m/min cutting speed and 0.10 mm/rev feed rate. Surface roughness of the samples with drilled holes was measured, and these values were found to vary in the range of 0.270–2.480 µm. At 0.10 mm/rev feed rate and 50 m/min cutting speed, the lowest cutting tool wear was measured as 1222393.74 µm2, while the highest wear was measured as 4532811.14 µm2. For the best surface quality and lowest cutting tool wear, 50 m/min cutting speed and 0.10 mm/rev feed rate were determined to be the optimum parameters.

scholarly journals Milling Inconel 718 Workpiece With Cryogenically Treated And Untreated Cutting Tools

2021 ◽  
Author(s):  
Hüseyin Gürbüz ◽  
Şehmus Baday
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Abrasive Wear ◽  
Inconel 718 ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Tool Wear ◽  
Feed Force

Abstract Although Inconel 718 is an important material for modern aircraft and aerospace, it is a kind material, which is known to have low machinability. Especially, while these types of materials are machined, high cutting temperatures, BUE on cutting tool, high cutting forces and work hardening occur. Therefore, in recent years, instead of producing new cutting tools that can withstand these difficult conditions, cryogenic process, which is a heat treatment method to increase the wear resistance and hardness of the cutting tool, has been applied. In this experimental study, feed force, surface roughness, vibration, cutting tool wear, hardness and abrasive wear values that occurred as a result of milling of Inconel 718 material by means of cryogenically treated and untreated cutting tools were investigated. Three different cutting speeds (35-45-55 m/min) and three different feed rates (0.02-0.03-0.04 mm/tooth) at constant depth of cut (0.2 mm) were used as cutting parameters in the experiments. As a result of the experiments, lower feed forces, surface roughness, vibration and cutting tool wear were obtained with cryogenically treated cutting tools. As the feed rate and cutting speed were increased, it was seen that surface roughness, vibration and feed force values increased. At the end of the experiments, it was established that there was a significant relation between vibration and surface roughness. However, there appeared an inverse proportion between abrasive wear and hardness values. While BUE did not occur during cryogenically treated cutting tools, it was observed that BUE occurred in cutting tools which were not cryogenically treated.

scholarly journals Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6106
Author(s):  
Waleed Ahmed ◽  
Hussien Hegab ◽  
Atef Mohany ◽  
Hossam Kishawy
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Inclination Angle ◽  
Feed Rate ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Hardened Steel ◽  
Machining Process ◽  
Aisi 4140 ◽  
Steel Aisi

It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle were the selected design variables, while the tool wear, surface roughness, and material removal rate (MRR) were the studied outputs. The optimal surface roughness was obtained at a cutting speed of 240 m/min, an inclination angle of 20°, and a feed rate of 0.1 mm/rev. In addition, the minimum flank tool wear was observed at a cutting speed of 70 m/min, an inclination angle of 10°, and a feed rate of 0.15 mm/rev. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer’s interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140 within the selected ranges.

scholarly journals System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8431
Author(s):  
Arturo Yosimar Jaen-Cuellar ◽  
Roque Alfredo Osornio-Ríos ◽  
Miguel Trejo-Hernández ◽  
Israel Zamudio-Ramírez ◽  
Geovanni Díaz-Saldaña ◽  
...  
Keyword(s):  
Tool Wear ◽  
Condition Monitoring ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Economic Benefits ◽  
Numerical Control ◽  
Cnc Machines ◽  
Cutting Tool Wear

The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is essential for the economic development of many countries. Current high quality production standards, along with the requirement for maximum economic benefits, demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wear. Current TCM methodologies mainly rely on vibration signals, cutting force signals, and acoustic emission (AE) signals, which have the common drawback of requiring the installation of sensors near the working area, a factor that limits their application in practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variety of cutting parameters. This paper proposes a novel non-invasive method capable of automatically diagnosing cutting tool wear in CNC machines under the variation of cutting speed and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA); a feed-forward neural network is then used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wear levels and different cutting speed and feed rate values.

scholarly journals Optimisation of Cutting Tool and Cutting Parameters in Face Milling of Custom 450 through the Taguchi Method

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Harun Gokce
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Tool Wear ◽  
Taguchi Method ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Tool Wear ◽  
Wide Range

Stainless steels with unique corrosion resistance are used in applications with a wide range of fields, especially in the medical, food, and chemical sectors, to maritime and nuclear power plants. The low heat conduction coefficient and the high mechanical properties make the workability of stainless steel materials difficult and cause these materials to be in the class of hard-to-process materials. In this study, suitable cutting tools and cutting parameters were determined by the Taguchi method taking surface roughness and cutting tool wear into milling of Custom 450 martensitic stainless steel. Four different carbide cutting tools, with 40, 80, 120, and 160 m/min cutting speeds and 0.05, 0.1, 0.15, and 0.2 mm/rev feed rates, were selected as cutting parameters for the experiments. Surface roughness values and cutting tool wear amount were determined as a result of the empirical studies. ANOVA was performed to determine the significance levels of the cutting parameters on the measured values. According to ANOVA, while the most effective cutting parameter on surface roughness was the feed rate (% 50.38), the cutting speed (% 81.15) for tool wear was calculated.

Effects of Cutting Speed and Feed Rate on Surface Roughness in Hard Turning of AISI 4140 with Mixed Ceramic Cutting Tool

2018 ◽  
Vol 779 ◽  
pp. 153-158
Author(s):  
Phacharadit Paengchit ◽  
Charnnarong Saikaew
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Hard Turning ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Machined Surface ◽  
Data Set ◽  
Ceramic Cutting Tool ◽  
Aisi 4140 ◽  
Mixed Ceramic

This work investigated the influences of cutting speed and feed rate on surface roughness in hard turning of AISI 4140 chromium molybdenum steel bar using mixed ceramic inserts Al2O3+TiC under dry condition for automotive industry applications. Turning experiments were conducted by varying cutting speed ranging from 150 to 220 m/min and feed rate ranging from 0.06 to 1 mm/rev. General factorial design was used to analyze the data set of surface roughness and determine statistically significant process factors based on analysis of variance results. The results showed that average surface roughness was significantly affected by feed rate and interaction between cutting speed and feed rate at the level of significance of 0.05. An optimal operating condition for hard turning of AISI 4140 with the ceramic cutting tool that produced a minimum machined surface roughness was obtained at cutting speed of 220 m/min and 0.06 mm/rev.

Characterisation, Performance and Optimisation of Nanocellulose Metalworking Fluid (MWF) for Green Machining Process

2021 ◽  
Vol 18 (4) ◽  
pp. 9188-9207
Author(s):  
Mahendran Samykano ◽  
J. Kananathan ◽  
K. Kadirgama ◽  
A. K. Amirruddin ◽  
D. Ramasamy ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Alumina Nanoparticles ◽  
Working Fluid ◽  
Depth Of Cut ◽  
Nanoparticle Concentration

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour.

Optimization of Surface Roughness by Using Different Cutting Tools for Aluminum Alloy 6063

2020 ◽  
Vol 17 (2) ◽  
pp. 961-966
Author(s):  
Allina Abdullah ◽  
Afiqah Azman ◽  
B. M. Khirulrizwan
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Optimum Condition ◽  
Feed Rate ◽  
Optimum Parameter ◽  
Cutting Tool ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Numerical Control ◽  
Depth Of Cut

This research outlines an experimental study to determine the optimum parameter of cutting tool for the best surface roughness (Ra) of Aluminum Alloy (AA) 6063. For the experiment in this research, cutting parameters such as cutting speed, depth of cut and feed rate are used to identify the effect of both cutting tools which are tungsten carbide and cermet towards the surface roughness (Ra) of material AA6063. The machining operation involved to cut the material is turning process by using Computer Numerical Control (CNC) Lathe machine. The experimental design was designed by Full Factorial. The experiment that had been conducted by the researcher is 33 with 2 replications. The total number of the experiments that had been run is 54 runs for each cutting tool. Thus, the total number of experiments for both cutting tools is 108 runs. ANOVA analysis had been analyzed to identify the significant factor that affect the Ra result. The significant factors that affect the Ra result of AA6063 are feed rate and cutting speed. The researcher used main effect plot to determine the factor that most influenced the surface roughness of AA6063, the optimum condition of surface roughness and the optimum parameter of cutting tool. The factor that most influenced the surface roughness of AA6063 is feed rate. The optimum condition of surface roughness is at the feed rate of 0.05 mm/rev, cutting speed of 600 rpm and depth of cut of 0.10 mm. While the optimum parameter of cutting tool is cermet insert with the lowest value of surface roughness (Ra) result which is 0.650 μm.

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.

Effects of Random Aspects of Cutting Tool Wear on Surface Roughness and Tool Life

2006 ◽  
Vol 15 (5) ◽  
pp. 519-524 ◽  
Author(s):  
Ben Fredj Nabil ◽  
Mohamed Mabrouk
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Tool Life ◽  
Cutting Tool ◽  
Cutting Tool Wear
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