scholarly journals Optimization of Power Consumption Associated with Surface Roughness in Ultrasonic Assisted Turning of Nimonic-90 Using Hybrid Particle Swarm-Simplex Method

Materials ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3418 ◽  
Author(s):  
Khanna ◽  
Airao ◽  
Gupta ◽  
Song ◽  
Liu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Fitness Function ◽  
Particle Swarm ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Hybrid Particle ◽  
Ultrasonic Assisted

These days, power consumption and energy related issues are very hot topics of research especially for machine tooling process industries because of the strict environmental regulations and policies. Hence, the present paper discusses the application of such an advanced machining process i.e., ultrasonic assisted turning (UAT) process with the collaboration of nature inspired algorithms to determine the ideal solution. The cutting speed, feed rate, depth of cut and frequency of cutting tool were considered as input variables and the machining performance of Nimonic-90 alloy in terms of surface roughness and power consumption has been investigated. Then, the experimentation was conducted as per the Taguchi L9 orthogonal array and the mono as well as bi-objective optimizations were performed with standard particle swarm and hybrid particle swarm with simplex methods (PSO-SM). Further, the statistical analysis was performed with well-known analysis of variance (ANOVA) test. After that, the regression equation along with selected boundary conditions was used for creation of fitness function in the subjected algorithms. The results showed that the UAT process was more preferable for the Nimconic-90 alloy as compared with conventional turning process. In addition, the hybrid PSO-SM gave the best results for obtaining the minimized values of selected responses.

Machining Apprenticeship Based on Experimental Training Practice

2011 ◽  
Vol 692 ◽  
pp. 83-92
Author(s):  
Pedro Jose Arrazola ◽  
A. Villar ◽  
R. Fernández ◽  
J. Aperribay
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Feed Rate ◽  
Cutting Forces ◽  
Theoretical Calculations ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Practical Training ◽  
Input Parameters

This article describes a practical machining training aiming that the students acquire the theoretical-practical knowledge of chip formation process. The training takes place after theoretical lessons of machining processes. Thus, this practice allows strengthening the knowledge gained during the lessons. The practical training lasts for five hours, and the student assisted by the teacher analyses the influence of some machining entry parameters (cutting speed, feed rate...) on exit parameters like: (I) cutting forces and power consumption, (II) surface roughness, and (III) chip typology. The practical session is carried out on an experimental set-up (Lathe CNC Danobar 65) equipped with sensors and devices to measure forces (sensor Kistler 9121) and power consumption. In addition, a portable rugosimeter (Hommelwerke) is employed to perform surface roughness measurements. No especial devices are needed for the chip typology analysis. In the case of cutting forces and power consumption, the following input parameters influences are analysed: feed rate, depth of cut and cutting speed. In the case of surface roughness analysis, the following input parameters influences are analysed: feed rate and nose radius of the cutting insert. Finally, regarding chip typology feed rate and depth of cut are examined. The experimental results are compared with model predictions (theoretical calculations) for the three issues studied. The students have to compare both results: theoretical an empirical and they need to explain the reasons when discrepancies appear. Results obtained during the last years demonstrate the student acquires better knowledge of the machining process, and at the same time realises of the process complexity.

Optimizing Multi Response Green Machining Using Taguchi Method Based on Grey Relational Analysis

2015 ◽  
Vol 747 ◽  
pp. 277-281 ◽  
Author(s):  
M. Imron Mustajib ◽  
Teguh Prasetyo ◽  
Heri Awalul Ilhamsah ◽  
Rudy Soenoko ◽  
Sugiono
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Power Consumption ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Control Factors ◽  
Green Machining ◽  
Early Survey ◽  
Grey Relational

This paper presents an optimization of multi response green machining of aluminum 6061 valve. The research is started with study literature and early survey to identify various factors that may likely influence in the green machining.The next step is investigating and collecting experiment data of the control factors (working in 3 levels) for depth of cut, feeding, and cutting speed factor on two responses; power consumption and surface roughness (Ra). The data were evaluated using Taguchi method based on grey relational anaylisis. Statistic tools coupled together with Taguchi design to process the output of the experiment. Finally, the research has successfully to deliver knowledges of the cutting speed and feeding factors have a dominant influence in power consumption and surface roughness of the green machining process

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%.

OPTIMISING CUTTING PARAMETERS FOR HOT TURNING ON EN31 MATERIAL

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Prof. Hemant k. Baitule ◽  
Satish Rahangdale ◽  
Vaibhav Kamane ◽  
Saurabh Yende
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Multiple Time ◽  
Turning Process ◽  
Workpiece Material ◽  
Hot Turning

In any type of machining process the surface roughness plays an important role. In these the product is judge on the basis of their (surface roughness) surface finish. In machining process there are four main cutting parameter i.e. cutting speed, feed rate, depth of cut, spindle speed. For obtaining good surface finish, we can use the hot turning process. In hot turning process we heat the workpiece material and perform turning process multiple time and obtain the reading. The taguchi method is design to perform an experiment and L18 experiment were performed. The result is analyzed by using the analysis of variance (ANOVA) method. The result Obtain by this method may be useful for many other researchers.

Improvement of Surface Roughness in End Milling of Ti6Al4V by Coupling RSM with Genetic Algorithm

2011 ◽  
Vol 264-265 ◽  
pp. 1154-1159
Author(s):  
Anayet Ullah Patwari ◽  
A.K.M. Nurul Amin ◽  
S. Alam
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Titanium Alloys ◽  
End Milling ◽  
Fitness Function ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Resistance Surface

Titanium alloys are being widely used in the aerospace, biomedical and automotive industries because of their good strength-to-weight ratio and superior corrosion resistance. Surface roughness is one of the most important requirements in machining of Titanium alloys. This paper describes mathematically the effect of cutting parameters on Surface roughness in end milling of Ti6Al4V. The mathematical model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). Central composite design was employed in developing the surface roughness models in relation to primary cutting parameters. The experimental results indicate that the proposed mathematical models suggested could adequately describe the performance indicators within the limits of the factors that are being investigated. The developed RSM is coupled as a fitness function with genetic algorithm to predict the optimum cutting conditions leading to the least surface roughness value. MATLAB 7.0 toolbox for GA is used to develop GA program. The predicted results are in good agreement with the experimental one and hence the model can be efficiently used to achieve the minimum surface roughness value.

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.

Performance Investigation of Modified Turning Tool Holder for MQL Application

2013 ◽  
Vol 465-466 ◽  
pp. 1114-1118
Author(s):  
Erween Abdul Rahim ◽  
Z.H. Samsudin ◽  
Muhammad Arif Abdul Rahim ◽  
Zazuli Mohid
Keyword(s):  
Single Channel ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Tool Holder ◽  
Dual Channel ◽  
Minimal Quantity Lubrication ◽  
Cutting Zone

Some machining process requires coolant to reduce the cutting temperature and helps to flush away the chips from the cutting zone. However, conventional flood coolant possesses some issues towards workers and the environment, regarding health and waste management. The implementation of Minimal Quantity Lubrication (MQL) as an alternative technique seems to be promising although the effectiveness of this technique were influenced by several factor. In turning process for instance, the distance of nozzle to the cutting zone contributes to the variation of machining performance. This study is to compare the effect on cutting performance between two internal MQL nozzle designs. The cutting tool holder were modified to have two internal MQL oil channel. The oil channel design were tested and the performance was evaluated in terms of cutting speed and cutting temperature for different cutting speed, feed rate and depth of cut. The result shows that the single channel performs better in terms of cutting force while dual channel significantly improve the cutting temperature.

Modelling and Optimization of Tool Chip Interface Temperature and Surface Roughness in CNC Dry Turning of EN 24 Steel

2016 ◽  
Vol 16 ◽  
pp. 7-15 ◽  
Author(s):  
Nirmal Kumar Mandal ◽  
Tanmoy Roy
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Machining Process ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Work Piece ◽  
Substantial Impact

Abstract. Kinetic energy of a machining process is converted into heat energy. The generated heat at cutting tool and work piece interface has substantial impact on cutting tool life and quality of the work piece. On the other hand, development of advanced cutting tool materials, coatings and designs, along with a variety of strategies for lubrication, cooling and chip removal, make it possible to achieve the same or better surface quality with dry or Minimum Quantity Lubrication (MQL) machining than traditional wet machining. In addition, dry and MQL machining is more economical and environment friendly. In this work, 20 no. of experiments were carried out under dry machining conditions with different combinations of cutting speed, feed rate and depth of cut and corresponding cutting temperature and surface roughness are measured. The no. of experiments is determined through Design of Experiments (DOE). Nonlinear regression methodology is used to model the process using Response Surface Methodology (RSM). Multi-objective optimization is carried using Genetic Algorithm which ensures high productivity with good product quality.

scholarly journals The Experimental Investigation of Surface Roughness After Dry Turning of Steel S235

2019 ◽  
Vol 26 (4) ◽  
pp. 179-184
Author(s):  
Justyna Molenda
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Scientific Work ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Workpiece Material ◽  
Important Indicator

AbstractNowadays lot of scientific work inspired by industry companies was done with the aim to avoid the use of cutting fluids in machining operations. The reasons were ecological and human health problems caused by the cutting fluid. The most logical solution, which can be taken to eliminate all of the problems associated with the use of cooling lubricant, is dry machining. In most cases, however, a machining operation without lubricant finds acceptance only when it is possible to guarantee that the part quality and machining times achieved in wet machining are equalled or surpassed. Surface finish has become an important indicator of quality and precision in manufacturing processes and it is considered as one of the most important parameter in industry. Today the quality of surface finish is a significant requirement for many workpieces. Thus, the choice of optimized cutting parameters is very important for controlling the required surface quality. In the present study, the influence of different machining parameters on surface roughness has been analysed. Experiments were conducted for turning, as it is the most frequently used machining process in machine industry. All these parameters have been studied in terms of depth of cut (ap), feed rate (f) and cutting speed (vc). As workpiece, material steel S235 has been selected. This work presents results of research done during turning realised on conventional lathe CDS 6250 BX-1000 with severe parameters. These demonstrate the necessity of further, more detailed research on turning process results.

scholarly journals Optimization of Atomized Spray Cutting Fluid Eco-Friendly Turning of Inconel 718 Alloy Using ARAS and CODAS Methods

2021 ◽  
Author(s):  
Vinothkumar Sivalingam ◽  
Ganeshkumar Poogavanam ◽  
Yuvaraj Natarajan ◽  
Jie Sun
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Tool Life ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Parameter Setting ◽  
Inconel 718 Alloy ◽  
Desirability Index

Abstract Atomized spray cutting fluid (ASCF) is a sophisticated machining technique that achieves higher productivity, enhanced surface quality, extended tool life, and cost benefits. This research aims to analyze the influence of cutting process parameters on Inconel 718 alloy turning in dry and ASCF cutting environments. The critical machining indices such as surface roughness, machining cost, power consumption, and tool life were analyzed concerning these two cooling environments. The cutting parameters were optimized using desirability functional analysis and two types of multicriteria decision making (MCDM) method, such as additive ratio assessment method (ARAS) and combinative distance-based assessment (CODAS) method, were investigated. The composite desirability index (CD) of optimum parameter setting(A2B1C2D2) is improved by 6.34 % compared to the initial parameter setting (A2B1C2D1). The optimum parameters from the MCDM technique are obtained as a cutting speed of 200 m/min, feed rate of 0.08 mm/rev, and depth of cut of 0.2 mm under ASCF environment. ASCF machining significantly minimize the surface roughness, machining cost and power consumption, maximize the tool life by about 16%, 51%, 17% and 48% respectively as compared with dry machining

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