scholarly journals Optimization of Process Parameter of Surface Grinding Process of Autenitic Stainless Steel (AISI 304) BY Taguchi Method

2019 ◽  
pp. 72-76
Author(s):  
M. A. Deore ◽  
R. S Shelke
Keyword(s):  
Taguchi Method ◽  
Feed Rate ◽  
Metal Removal ◽  
Removal Rate ◽  
Surface Grinding ◽  
Machining Process ◽  
Depth Of Cut ◽  
Work Piece ◽  
Grinding Process ◽  
Machining Processes

The manufacturing process of surface grinding has been established in the mass production of slim, rotationally symmetrical components. Due to the complex set-up, which results from the large sensitivity of this grinding process to a multiplicity of geometrical, kinematical and dynamical influence parameters, surface grinding is rarely applied within limited-lot production. The substantial characteristics of this grinding process are the simultaneous guidance and machining of the work piece on its periphery. Surface grinding is an essential process for final machining of components requiring smooth surfaces and precise tolerances. As compared with other machining processes, grinding is costly operation that should be utilized under optimal conditions. Although widely used in industry, grinding remains perhaps the least understood of all machining processes. The proposed work takes the following input processes parameters namely Work speed, feed rate and depth of cut. The main objective of this work is to predict the grinding behavior and achieve optimal operating processes parameters. a software package may be utilized which integrates these various models to simulate what happens during surface grinding processes. predictions from this simulation will be further analyzed by calibration with actual data. It involves several variables such as depth of cut, work speed, feed rate, chemical composition of work piece, etc. The main objective in any machining process is to maximize the Metal Removal Rate (MRR) and to minimize the surface roughness (Ra). In order to optimize these values Taguchi method, ANOVA and regression analysis is used.

scholarly journals Surface Grinding Parameters Optimization of Austenitic Stainless Steel (AISI 304)

2020 ◽  
pp. 511-515
Author(s):  
Tushar Khule ◽  
Rahul Naravade ◽  
Sagar Shelke
Keyword(s):  
Surface Roughness ◽  
Large Scale ◽  
Metal Removal ◽  
Removal Rate ◽  
Parameters Optimization ◽  
Surface Grinding ◽  
Machining Process ◽  
Project Work ◽  
Depth Of Cut ◽  
Set Up

The assembling procedure of surface grinding has been set up in the large scale manufacturing of thin, rotationally even parts. Due to the complex set-up and geometrical, kinematical, dynamical influence parameters, surface grinding is rarely applied within limited-lot production. Surface crushing is a basic procedure for last machining of parts requiring smooth surfaces and exact resiliences.As contrasted and other machining forms, crushing is exorbitant activity that ought to be used under ideal conditions.. Although widely used in industry. The project work takes the following input processes parameters namely Work speed, feed rate and depth of cut. The main objective of this work is to predict the grinding behaviour and achieve optimal operating processes parameters. A software package is utilized which integrates these various models to simulate what happens during surface grinding processes. Predictions from this simulation will be further analysed by calibration with actual data. The main objective in any machining process is to maximize the Metal Removal Rate (MRR) and to minimize the surface roughness (Ra). In order to optimize these values Taguchi method, ANOVA is used. The surface roughness (Ra) value and Material Removal Rate (MRR), obtained from experimentation and confirmation test, for this the optimum control parameters are analysed.

Optimization of MRR and Surface Roughness of AlMg3 (AA5754) Alloy in CNC Lathe Machine by Using Taguchi Method

2018 ◽  
Vol 877 ◽  
pp. 110-117 ◽  
Author(s):  
Poornesh Kumar Chaturvedi ◽  
Harendra Kumar Narang ◽  
Atul Kumar Sahu
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Metal Removal ◽  
Removal Rate ◽  
Surface Condition ◽  
Point Of View ◽  
Depth Of Cut ◽  
Metal Removal Rate ◽  
Cnc Lathe ◽  
Lathe Machine

Quality of the product is the major concern in manufacturing industries from customers as well as producers point of view. There are number of factors in the product such as surface condition, height, weight, length, width etc., which may be consider for the measurement of the quality. Surface roughness and Metal Removal Rate (MRR) are the two main outcomes on which numerous researchers have applied different approaches for several years to get optimum results. In this study, Taguchi Method is applied for getting optimum parameters settings for Surface roughness and Metal Removal Rate (MRR) in case of turning AlMg3 (AA5754) in CNC Lathe machine, which is an aluminum alloy having diameter 20 mm and length 100 mm. The three parameters i.e. spindle speed, feed rate and depth of cut with 3 levels are taken as the process variables and the working ranges of these parameters for conducting experiments are selected based on Taguchi’s L9 Orthogonal Array (OA) design. To analyze the significant process parameters; main effect plots for data means and for S/N ratio are generated using Minitab statistical software.

A Study on Edge Milling Operation of NEMA G11 GFRP Composites Based on Grey-Taguchi Method

2014 ◽  
Vol 592-594 ◽  
pp. 18-22
Author(s):  
Hari Vasudevan ◽  
Ramesh Rajguru ◽  
Naresh Deshpande
Keyword(s):  
Taguchi Method ◽  
Feed Rate ◽  
Spindle Speed ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Machining Processes ◽  
Milling Parameters ◽  
Response Table ◽  
Milling Operation ◽  
Grey Relational

Milling is one of the most practical machining processes for removing excess material to produce high quality surfaces. However, milling of composite materials is a rather complex task, owing to its heterogeneity and poor surface finish, which includes fibre pullout, matrix delamination, sub-surface damage and matrix polymer interface failure. In this study, an attempt has been made to optimize milling parameters with multiple performance characteristics in the edge milling operation, based on the Grey Relational Analysis coupled with Taguchi method. Taguchi’s L18 orthogonal array was used for the milling experiment. Milling parameters such as milling strategy, spindle speed, feed rate and depth of cut are optimised along with multiple performance characteristics, such as machining forces and delamination. Response table of grey relational grade for four process parameters is used for the analysis to produce the best output; the optimal combination of the parameters. From the response table of the average GRG, it is found that the largest value of the GRG is for down milling, spindle speed of 1000 rpm, feed rate of 150 mm/min and depth of cut 0.4 mm.

scholarly journals EFFECT OF MINIMUM QUANTITY LUBRICATION ON SURFACE ROUGHNESS IN TOOL-BASED MICROMILLING

2017 ◽  
Vol 18 (1) ◽  
pp. 147-154
Author(s):  
Mohammad Yeakub Ali ◽  
Wan Norsyazila Jailani ◽  
Mohamed Rahman ◽  
Muhammad Hasibul Hasan ◽  
Asfana Banu
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Spindle Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Microfluidic Channels ◽  
Machining Parameters ◽  
Machining Processes ◽  
Dry Cutting ◽  
Minimum Quantity

Cutting fluid plays an important role in machining processes to achieve dimensional accuracy in reducing tool wear and improving the tool life. Conventional flood cooling method in machining processes is not cost effective and consumption of huge amount of cutting fluids is not healthy and environmental friendly. In micromachining, flood cooling is not recommended to avoid possible damage of the microstructures. Therefore, one of the alternatives to overcome the environmental issues to use minimum quantity of lubrication (MQL) in machining process. MQL is eco-friendly and has economical advantage on manufacturing cost. However, there observed lack of study on MQL in improving machined surface roughness in micromilling. Study of the effects of MQL on surface roughness should be carried out because surface roughness is one of the important issues in micromachined parts such as microfluidic channels. This paper investigates and compares surface roughness with the presence of MQL and dry cutting in micromilling of aluminium alloy 1100 using DT-110 milling machine. The relationship among depth of cut, feed rate, and spindle speed on surface roughness is also analyzed. All three machining parameters identified as significant for surface roughness with dry cutting which are depth of cut, feed rate, and spindle speed. For surface roughness with MQL, it is found that spindle speed did not give much influence on surface roughness. The presence of MQL provides a better surface roughness by decreasing the friction between tool and workpiece.

scholarly journals Multi-Objective Process Parameter Optimization for Surface Roughness and Material Removal Rate in Face Milling of Al 6061 T6 Alloy

2019 ◽  
Vol 9 (2) ◽  
pp. 137-142
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Face Milling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Al 6061

This study uses Taguchi methodology and Gray Relational Analysis approach to explore the optimization of face milling process parameters for Al 6061 T6 alloy.Surface Roughness (Ra), Material Removal Rate (MRR) has been identified as the objective of performance and productivity.The tests were performed by selecting cutting speed (mm / min), feed rate (mm / rev) and cutting depth (mm) at three settings on the basis of Taguchi's L9 orthogonal series.The grey relational approach was being used to establish a multiobjective relationship between both the parameters of machining and the characteristics of results. To find the optimum values of parameters in the milling operation, the response list and plots are used and found to be Vc2-f1-d3. To order to justify the optimum results, the confirmation tests are performed.The machining process parameters for milling were thus optimized in this research to achieve the combined goals such as low surface roughness and high material removal rate on Aluminum 6061 t6.It was concluded that depth of cut is the most influencing parameter followed by feed rate and cutting velocity.

scholarly journals Experimental Study on The Effect of Cross Feed of Surface Grinding on the Vibration and the Surface Roughness of Hardened Tool Steel OCR12VM

2020 ◽  
Vol 11 (3) ◽  
pp. 313-322
Author(s):  
Chairul Anam ◽  
◽  
Khairul Muzaka ◽  
Dian Ridlo Pamuji
Keyword(s):  
Surface Roughness ◽  
Tool Steel ◽  
Dimensional Accuracy ◽  
Surface Grinding ◽  
Machining Process ◽  
Depth Of Cut ◽  
Grinding Process ◽  
Hardened Tool Steel ◽  
Stone Type ◽  
Grinding Stone

The grinding process is a machining process to obtain qualified surface roughness levels and high dimensional accuracy. There are two types of processes in the grinding process, namely the roughening and finishing processes. The vibration effect of the roughing process can damage and shorten the life of the tool/machine, while in the finishing process, the effect of vibration will reduce the dimensional accuracy, shape, and surface smoothness of the workpiece. This study aims to determine the effect of crossfeed on the amplitude of vibration and surface roughness of the workpiece on the surface grinding process. The materials used are hardened tool steel OCR12VM with a variety of grinding stone types A46QV and A80LV made of aluminum oxide. The Variables of process parameters are crossfeed (mm / step) and depth of cut (mm). The measurement of vibrations uses an accelerometer, which is processed by the math CAD program in the form of amplitude and frequency. For surface roughness measurements, it is used the MT-301 surface test with 5 sample points and a sample length of 0.8 mm. The results show that the greater the cross-feed value, the bigger the amplitude of the vibration level and the surface roughness of the workpiece. The magnitude of the amplitude of the vibration on the acceleration that occurs in the grinding stone type A46QV starts from 6,7369 -18.7525 g.rms, while the grinding stone type A80LV starts from 5.0904 g.rms to 18.2821 g.rms. The surface roughness achieved in both grit 46 and grit 80 is from N3 to N5.

Optimization of Multi-Responses in Hot Turning of Inconel 625 Alloy Using DEA-Taguchi Approach

2016 ◽  
Vol 24 ◽  
pp. 57-63 ◽  
Author(s):  
A.K. Parida ◽  
K.P. Maity
Keyword(s):  
Taguchi Method ◽  
Material Removal Rate ◽  
Surface Finish ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Machining Parameter ◽  
Hot Turning

In the present work DEA (data envelopment analysis) coupled with Taguchi method has used for optimization in process parameters of hot turning operation. An experimental investigation has been carried out to study the effect of cutting parameters such as speed, feed and depth of cut during. The material removal rate and surface finish, are to be studied with respect to machining at 450 temperature by heating Inconel 625. In order to achieve both quality and productivity, optimization of both is necessary simultaneously. DEA –Taguchi method can employed for solving in multi-response problem. LINGO software was used to find out the relative efficiency and converted to S/N ratio using MINITAB software. The optimization of the machining parameter found at 100 m/min cutting speed, 0.15 mm/rev feed rate and 1 mm depth of cut. Depth of cut is the most influencing parameter which affect both surface finish and material removal rate in the machining process.

Analysis and optimisation of machinability behaviour of CFRP composites using fuzzy logic

2015 ◽  
Vol 44 (1) ◽  
pp. 48-55 ◽  
Author(s):  
M.P. Jenarthanan ◽  
R. Jeyapaul
Keyword(s):  
Fuzzy Logic ◽  
Taguchi Method ◽  
Removal Rate ◽  
Performance Characteristics ◽  
Machining Process ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Content Type ◽  
Cfrp Composites

Purpose – The purpose of this paper is to analyse and optimise the machinability behaviour of Carbon Fibre Reinforced Polymer (CFRP) composites with multiple performance characteristics using the Taguchi method with fuzzy logic. Design/methodology/approach – A multi-response performance index (MRPI) was used for optimisation. The machining parameters, viz., tool geometry (helix angle of the endmill cutter), spindle speed, feed rate and depth of cut, were optimised with consideration of multiple performance characteristics, viz., machining force and material removal rate. Findings – The results from confirmation runs indicated that the determined optimal combination of machining parameters improved the performance of the machining process. Originality/value – The machinability behaviour of CFRP composites during milling of CFRP composites using Taguchi method with fuzzy logic has not been previously analysed.

Analysis and Validation of Erosion Process by Sea Sand as an Abrasive Material by Using Regression Model and Neural Network in Abrasive Jet Machining Process for Alumina

2014 ◽  
Vol 592-594 ◽  
pp. 854-858
Author(s):  
N.S. Pawar ◽  
R.R. Lakhe ◽  
R.L. Shrivastava
Keyword(s):  
Regression Model ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Variable Pressure ◽  
Work Piece ◽  
Abrasive Jet Machining ◽  
Mixing Chamber ◽  
Micro Grooving

According to the most of the studies dealing with micro grooving, cutting, leading to lower material removal Abrasive jet machining is traditional process. Invention was made to create those needs. A number of investigation or researches were carried out by imminent personality but no detailed information and design has provided about cylindrical vibrating chamber or mixing chamber. This change in shape gives better velocity to abrasive particles and non sticking characteristic gives the better effect of erosion of material on work piece and scattering of particle towards objects. The parameter stand off distance, variable pressure, material removal rate used for this experimental study has also moderate. The work carried out with Alumina nozzle. The abrasive powder feed rate is controlled by the amplitude of mixing chamber. The root mean square value is 0.988 in linear regression model. The estimated standard error is 0.00115 which is very less. The performance of sand gives the similar better model result as given by traditional using different parameter. The taper of cut is higher with this mixing particle and better feed rate.

Improving Milling Performance with High Pressure Waterjet Assisted Cooling / Lubrication

1995 ◽  
Vol 117 (3) ◽  
pp. 331-339 ◽  
Author(s):  
R. Kovacevic ◽  
C. Cherukuthota ◽  
R. Mohan
Keyword(s):  
High Pressure ◽  
Metal Removal ◽  
Removal Rate ◽  
Water Pressure ◽  
Surface Profile ◽  
Machining Process ◽  
Orifice Diameter ◽  
Machining Processes ◽  
Milling Performance ◽  
Metal Machining

During machining, due to relative motion between tool and workpiece, severe thermal/frictional conditions exist at the tool-chip interface. Metal machining processes can be more efficient in terms of increasing the metal removal rate and lengthening tool life, if the thermal/frictional conditions are controlled effectively. A high pressure waterjet assisted coolant/lubricant system that can be used in conjunction with rotary tools (e.g., face milling) is developed here. The performance of this system is evaluated in terms of cutting force, surface quality, tool wear, and chip shape. The improvement in the effectiveness of the developed system with increase in water pressure and orifice diameter is also investigated. Stochastic modeling of the surface profile is performed to obtain more information about the role of waterjet in the machining process.

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