scholarly journals Modeling and optimization of flank wear and surface roughness of Monel-400 during hot turning using artificial intelligence techniques

10.30544/473 ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 57-69
Author(s):  
M. Hanief ◽  
M. S. Charoo
Keyword(s):  
Surface Roughness ◽  
Power Law ◽  
Close Agreement ◽  
Flank Wear ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Power Law Model ◽  
Objective Functions ◽  
Monel 400 ◽  
Hot Turning

This work aims to model and investigate the effect of cutting speed, feed rate, depth of cut and the workpiece temperature on surface roughness and flank wear (responses) of Monel-400 during turning operation. It also aims to optimize the machining parameters of the above operation. A power-law model is developed for this purpose and is corroborated by comparing the results with the artificial neural network (ANN) model. Based on the coefficient of determination (R2), mean square error (MSE), and mean absolute percentage error (MAPE) the results of the power-law model are found to be in close agreement with that of ANN. Also, the proposed power law and ANN models for surface roughness and flank wear are in close agreement with the experiment results. For the power-law model R2, MSE, and MAPE were found to be 99.83%, 9.9×10-4, and 3.32×10-2, and that of ANN were found to be 99.91%, 5.4×10-4, and 5.96×10-2, respectively for surface roughness and flank wear. An error of 0.0642% (minimum) and 8.7346% (maximum) for surface roughness and 0.0261% (minimum) and 4.6073% (maximum) for flank wear were recorded between the observed and experimental results, respectively. In order to optimize the objective functions obtained from power-law models of the surface roughness and flank wear, GA (genetic algorithm) was used to determine the optimal values of the operating parameters and objective functions thereof. The optimal value of 2.1973 µm and 0.256 mm were found for surface roughness and flank wear, respectively.

Machining characteristics of Inconel 718 under several cutting conditions based on Taguchi method

2012 ◽  
Vol 227 (9) ◽  
pp. 1889-1897 ◽  
Author(s):  
R Thirumalai ◽  
JS Senthilkumaar ◽  
P Selvarani ◽  
S Ramesh
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
Flank Wear ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machining Parameters ◽  
Dry Machining ◽  
Noise Factors

Extensive researchers have conducted several experiments in the past for selecting the optimum parameters in machining nickel based alloy – Inconel 718. These experiments conducted so far are dealt with dry machining and flooded coolant machining of nickel alloy Inconel 718. In this research study, the usage of refrigerated coolant is also dealt with and it is compared with dry machining and flooded coolant machining. Cutting speed, feed and depth of cut are considered as the machining parameters. The effectiveness of the refrigerated coolant in machining the heat resistant super alloy material Inconel 718 with respect to these machining parameters are described in this article. The machinability studies parameters were generated with surface roughness and flank wear. The performance of uncoated carbide cutting tool was investigated at various cutting condition under dry, flooded coolant and refrigerated coolant machining. The relationship between the machining parameters and the performance measures were established and using analysis of variance significant machining parameters determined. This article made an attempt to Taguchi optimization technique to study the machinability performances of Inconel 718. Taguchi approach is an efficient and effective experimental method in which a response variable can be optimized, given various control and noise factors, using fewer experiments than a factorial design. Taguchi’s optimization analysis indicates that the factors level, its significance to influence the surface roughness and flank wear for the machining processes. Confirmation tests were conducted at an optimal condition to make a comparison between the experimental results foreseen from the mentioned correlations.

Machinability Investigation of HSLA Steel in Hard Turning with Coated Ceramic Tool: Assessment, Modeling, Optimization and Economic Aspects

2019 ◽  
Vol 18 (04) ◽  
pp. 625-655 ◽  
Author(s):  
Asutosh Panda ◽  
Sudhansu Ranjan Das ◽  
Debabrata Dhupal
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Hard Turning ◽  
Flank Wear ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Ceramic Tool ◽  
Life Estimation

The present study addresses the machinability investigation in finish dry hard turning of high strength low alloy steel with coated ceramic tool by considering cutting speed, feed and depth of cut as machining parameters. The technological parameters like surface roughness, flank wear, chip morphology and economical feasibility have been considered to investigate the machinability performances. Twenty seven set of trials according to full factorial design of experiments are performed and analysis of variance, multiple regression method, Taguchi method, desirability function approach and finally Gilbert’s approach are subsequently applied for parametric influence study, mathematical modeling, multi-response optimization, tool life estimation and economic analysis. Results indicated that feed and cutting speed are the most significant controlled as well as dominant factors for hard turning operation if the minimization of the machined surface roughness and tool flank wear is considered. Abrasions, adhesion followed by plastic deformation have been observed to be the principal wear mechanism for tool life estimation and observed tool life for coated ceramic insert is 47[Formula: see text]min under optimum cutting conditions. The total machining cost per part is ensued to be lower ($0.29 only) as a consequence of higher tool life, reduction in downtime and enhancement in savings, which finds economical benefits in hard turning. The current work demonstrates the substitution of conventional, expensive and slow cylindrical grinding process, and proposes the most expensive CBN tool alternative using coated ceramic tools in hard turning process considering techno-economical and ecological aspects.

scholarly journals Fuzzy-MOORA Based Optimization of Machining Parameters for Machinability Enhancement of Titanium

2021 ◽  
Vol 8 (2) ◽  
pp. 189-198
Author(s):  
Durwesh Jhodkar ◽  
Akhtar Khan ◽  
Kapil Gupta
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Tool Flank Wear ◽  
Moora Method ◽  
Fuzzy Moora

The aim of this study is to determine the optimal combination of process parameters when machining commercially pure titanium grade 2. The unification of Multi objective optimization based on ratio analysis (MOORA) and fuzzy approach has applied to optimize the process parameters. Three process parameters i.e. cutting speed, tool overhang, and microhardness have been varied at three levels each and a total of twenty seven experiments have been conducted based on Taguchi’s L27 design of experiment technique. Cutting force, tool flank wear, and average surface roughness have been considered a machinability indicators to measure the process performance. Feed rate and depth of cut have been kept constant. Successful optimization is done and results show that machining titanium at higher cutting speed (140 m/min) and higher tool overhang length (65 mm) with medium hardness (1934 HV) results in lower cutting force, tool flank wear, and surface roughness. Outcomes of the present work reveal that the hybrid fuzzy-MOORA method is convincing enough to obtain the best process parameter combination for the best machinability while machining titanium type difficult-to-machine materials.

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.

Application of Taguchi Technique to Surface-Grinding of Mold Steel

2016 ◽  
Vol 689 ◽  
pp. 7-11 ◽  
Author(s):  
Y. Şahin ◽  
Senai Yalcinkaya
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Quality Characteristics ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Grinding Process ◽  
Machining Parameters ◽  
Taguchi Technique ◽  
Fluid Environment ◽  
Selection Of

The selection of optimum machining parameters plays a significant role for the quality characteristics of products and its costs for grinding. This study describes the optimization of the grinding process for an optimal parametric combination to yield a surface roughness using the Taguchi method. An orthogonal array and analysis of variance are employed to investigate the effects of cutting environment (A), depth of cut (B) and feed rate (C) on the surface roughness characteristics of mold steels. Confirmation experiments were conducted to verify the optimal testing parameters. The experimental results indicated that the surface finish decreased with cutting-fluid and depth of cut, but decreased with increasing feed rate. It is revealed that the cutting fluid environment had highest physical as well as statistical influence on the surface roughness (71.38%), followed by depth of cut (25.54%), but the least effect was exhibited by feed rate (1.62%).

Research on Prediction Model of Surface Roughness in Ultrasonic Polishing Nano-ZrO2 Ceramics

2009 ◽  
Vol 69-70 ◽  
pp. 128-132
Author(s):  
Ming Li Zhao ◽  
Bo Zhao ◽  
Yu Qing Wang ◽  
Guo Fu Gao
Keyword(s):  
Surface Roughness ◽  
Orthogonal Test ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Machining Parameters ◽  
Test Results ◽  
Work Situation ◽  
Table Speed ◽  
Abrasive Size ◽  
Regressive Analysis

The orthogonal test of surface roughness in ultrasonic polishing nano-ZrO2 ceramics was carried out in the present paper. Through the test, the influence of machining parameters on the surface roughness was investigated. The test results showed that the influence of abrasive size on surface roughness is the most remarkable, and the other important factors are the depth of cut, on/off work situation of ultrasonic generator, axial feed speed, and working table speed in turns. Furthermore, through the regressive analysis of test data, an empirical formula of surface roughness was established to select reasonable polishing parameters.

Effect of machining parameters on the surface finish of a metal matrix composite under dry cutting conditions

2015 ◽  
Vol 231 (6) ◽  
pp. 913-923 ◽  
Author(s):  
Brian Boswell ◽  
Mohammad Nazrul Islam ◽  
Ian J Davies ◽  
Alokesh Pramanik
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composite ◽  
Tool Life ◽  
Surface Finish ◽  
Feed Rate ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting

The machining of aerospace materials, such as metal matrix composites, introduces an additional challenge compared with traditional machining operations because of the presence of a reinforcement phase (e.g. ceramic particles or whiskers). This reinforcement phase decreases the thermal conductivity of the workpiece, thus, increasing the tool interface temperature and, consequently, reducing the tool life. Determining the optimum machining parameters is vital to maximising tool life and producing parts with the desired quality. By measuring the surface finish, the authors investigated the influence that the three major cutting parameters (cutting speed (50–150 m/min), feed rate (0.10–0.30 mm/rev) and depth of cut (1.0–2.0 mm)) have on tool life. End milling of a boron carbide particle-reinforced aluminium alloy was conducted under dry cutting conditions. The main result showed that contrary to the expectations for traditional machined alloys, the surface finish of the metal matrix composite examined in this work generally improved with increasing feed rate. The resulting surface roughness (arithmetic average) varied between 1.15 and 5.64 μm, with the minimum surface roughness achieved with the machining conditions of a cutting speed of 100 m/min, feed rate of 0.30 mm/rev and depth of cut of 1.0 mm. Another important result was the presence of surface microcracks in all specimens examined by electron microscopy irrespective of the machining condition or surface roughness.

EXPERIMENTAL INVESTIGATION OF COCONUT OIL WITH NANOBORIC ACID DURING MILLING OF INCONEL 625 USING TAGUCHI-GREY RELATIONAL ANALYSIS

2020 ◽  
pp. 2150008
Author(s):  
T. MOHANRAJ ◽  
P. RAGAV ◽  
E. S. GOKUL ◽  
P. SENTHIL ◽  
K. S. RAGHUL ANANDH
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Flank Wear ◽  
Coconut Oil ◽  
Inconel 625 ◽  
Depth Of Cut ◽  
Individual Response ◽  
Relational Analysis ◽  
Grey Relational ◽  
Taguchi’S Design Of Experiments

This study is based on Taguchi’s design of experiments along with grey relational analysis (GRA) to optimize the milling parameters to minimize surface roughness, tool wear, and vibration during machining of Inconel-625 while using coconut oil as cutting fluid (CF). The experiments were conducted based on Taguchi’s L9 orthogonal array (OA). Taguchi’s S/N was used for identifying the optimal cutting parameter for individual response. Analysis of variance (ANOVA) was employed to analyze the outcome of individual parameters on responses. The surface roughness was mostly influenced by feed. Flank wear was influenced by speed and the vibration was mostly influenced by the depth of cut as well as speed. The multi-response optimization was done through GRA. From GRA, the optimal parameters were identified. Further, nanoboric acid of 0.5 and 0.9[Formula: see text]wt.% was mixed with coconut oil to enhance lubricant properties. Coconut oil with 0.5[Formula: see text]wt.% of nanoboric acid minimizes the surface roughness and flank wear by 3.92% and 6.28% and reduces the vibration in the [Formula: see text]-axis by 4.85%. The coconut oil with 0.5[Formula: see text]wt.% of nanoboric acid performs better than coconut oil with 0.9[Formula: see text]wt.% of nano boric acid and base oil.

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