Modeling and optimizing of cutting force and surface roughness in milling process of Inconel 738 using hybrid ANN and GA

2019 ◽  
Vol 234 (5) ◽  
pp. 920-932 ◽  
Author(s):  
Lila Imani ◽  
Ali Rahmani Henzaki ◽  
Reza Hamzeloo ◽  
Behnam Davoodi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Turbine Blades ◽  
Cutting Speed ◽  
Experimental Results ◽  
Input Parameters ◽  
Four Levels ◽  
Milling Forces ◽  
Axial Depth

Super-alloys have high thermal and mechanical strength and are widely used for heat exchangers, turbine blades, and other parts which work under severe creep conditions. Machinability of these alloys is directly affected by mechanical and physical properties. In addition, cutting force and surface roughness are two important factors in machinability of alloys. Hence, numerous studies have been conducted in order to illustrate their influences. However, among these alloys, the machining of Inconel 738 has been less studied. Milling parameters such as cutting speed, feed rate, the axial depth of cutting, and coolant have the most effects on machinability of nickel-based super-alloys. Therefore, in this research, they are considered as input parameters for investigation of milling of Inconel 738. The present study utilizes artificial intelligence as an effective method for predicting milling forces and surface roughness based on experimental results. To investigate the behavior of this alloy, four levels for the two former input parameters and two levels for the two other, totally 64 experiments, were fulfilled and studied. Based on the experimental results, the effect of input parameters on the outputs, that is, cutting force and surface roughness, was investigated, and then, neural network for modeling and predicting and genetic algorithm for the optimization of the outputs have been utilized. The optimized artificial network, which was obtained in this research, is useful for prediction of machining force and surface roughness of milling based on the values of cutting speed, feed rate, and the axial depth of cutting, for wet and dry milling of Inconel 738.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

Experimental Study of End Milling Force on Manganese Steel

2013 ◽  
Vol 718-720 ◽  
pp. 239-243
Author(s):  
Girma Seife Abebe ◽  
Ping Liu
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Second Order ◽  
Manganese Steel ◽  
Depth Of Cut ◽  
Machining Deformation ◽  
Radial Depth ◽  
Axial Depth

Cutting force is a key factor influencing the machining deformation of weak rigidity work pieces. In order to reduce the machining deformation and improve the process precision and the surface quality, it is necessary to study the factors influencing the cutting force and build the regression model of cutting forces. This paper discusses the development of the first and second order models for predicting the cutting force produced in end-milling operation of modified manganese steel. The first and second order cutting force equations are developed using the response surface methodology (RSM) to study the effect of four input cutting parameters (cutting speed, feed rate, radial depth and axial depth of cut) on cutting force. The separate effect of individual input factors and the interaction between these factors are also investigated in this study. The received second order equation shows, based on the variance analysis, that the most influential input parameter was the feed rate followed by axial depth, and radial depth of cut. It was found that the interaction of feed with axial depth was extremely strong. In addition, the interactions of feed with radial depth; and feed rate with radial depth of cut were observed to be quite significant. The predictive models in this study are believed to produce values of the longitudinal component of the cutting force close to those readings recorded experimentally with a 95% confident interval.

Taguchi Method Based Experiments of Titanium TC11 Flank Milling Parameters

2009 ◽  
Vol 407-408 ◽  
pp. 608-611 ◽  
Author(s):  
Chang Yi Liu ◽  
Cheng Long Chu ◽  
Wen Hui Zhou ◽  
Jun Jie Yi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Flank Milling ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Mill Machining

Taguchi design methodology is applied to experiments of flank mill machining parameters of titanium alloy TC11 (Ti6.5A13.5Mo2Zr0.35Si) in conventional and high speed regimes. This study includes three factors, cutting speed, feed rate and depth of cut, about two types of tools. Experimental runs are conducted using an orthogonal array of L9(33), with measurement of cutting force, cutting temperature and surface roughness. The analysis of result shows that the factors combination for good surface roughness, low cutting temperature and low resultant cutting force are high cutting speed, low feed rate and low depth of cut.

Investigation of Chip and Surface Roughness when Milling AISI304 Stainless Steel

2017 ◽  
Vol 889 ◽  
pp. 152-158
Author(s):  
K. Kadirgama ◽  
K. Abou-El-Hossein
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Feed Rate ◽  
Prediction Models ◽  
Cutting Speed ◽  
Experimental Result ◽  
Quadratic Model ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Axial Depth

Stainless steel was used for many engineering applications. The optimum parameters needs to be identify to save the cutting tool usage and increase productivity. The purpose of this study is to develop the surface roughness mathematical model for AISI 304 stainless steel when milling using TiN (CVD) carbide tool. The milling process was done under various cutting condition which is cutting speed (1500, 2000 and 2500 rpm), feed rate (0.02, 0.03 and 0.04 mm/tooth) and axial depth (0.1, 0.2 and 0.3 mm). The first order model and quadratic model have been developed using Response Surface Method (RSM) with confident level 95%. The prediction models were comparing with the actual experimental results. It is found that quadratic model much fit the experimental result compare to linear model. In general, the results obtained from the mathematical models were in good agreement with those obtained from the machining experiments. Besides that, it is shown that the influence of cutting speed and feed rate are much higher on surface roughness compare to depth of cut. The optimum cutting speed, feed rate and axial depth is 2500 rpm, 0.0212 mm/tooth and 0.3mm respectively. Besides that, continues chip is produced at cutting speed 2500 rpm meanwhile discontinues chip produced at cutting speed 1500 rpm.

scholarly journals Multi-objective optimization of SKD11 Steel Milling Process by Reference Ideal Method

2021 ◽  
Vol 15 ◽  
pp. 1-16
Author(s):  
Do Duc Trung
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Milling Process ◽  
Multi Objective Optimization ◽  
Small Surface ◽  
Multi Objective ◽  
Input Parameters ◽  
Machining Productivity ◽  
Ideal Method

For all machining cutting methods, surface roughness is a parameter that greatly affects the working ability and life of machine elements. Cutting force is a parameter that not only affects the quality of the machining surface but also affects the durability of cutter and the level of energy consumed during machining. Besides, material removal rate (MRR) is a parameter that reflects machining productivity. Workpiece surface machining with small surface roughness, small cutting force and large MRR is desirable of most machining methods. This article presents a study of multi-objective optimization of milling process using a face milling cutter. The experimental material used in this study is SKD11 steel. Taguchi method has been applied to design an orthogonal experimental matrix with 27 experiments (L27). In which, five parameters have been selected as the input parameters of the experimental process including insert material, tool nose radius, cutting speed, feed rate and cutting depth. Reference Ideal Method (RIM) is applied to determine the value of input parameters to ensure minimum surface roughness, minimum cutting force and maximum MRR. Influence of the input parameters on output parameters is also discussed in this study.

scholarly journals Analysis and Optimization of Cutting Tool Coating Effects on Surface Roughness and Cutting Forces on Turning of AA 6061 Alloy

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mahir Akgün ◽  
Fuat Kara
Keyword(s):  
Surface Roughness ◽  
Mathematical Models ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Dry Cutting ◽  
Machined Surface ◽  
Tool Coating ◽  
Cutting Inserts

The present work has been focused on cutting force (Fc) and analysis of machined surface in turning of AA 6061 alloy with uncoated and PVD-TiB2 coated cutting inserts. Turning tests have been conducted on a CNC turning under dry cutting conditions based on Taguchi L18 (21 × 33) array. Kistler 9257A type dynamometer and equipment have been used in measuring the main cutting force (Fc) in turning experiments. Analysis of variance (ANOVA) has been applied to define the effect levels of the turning parameters on Fc and Ra. Moreover, the mathematical models for Fc and Ra have been developed via linear and quadratic regression models. The results indicated that the best performance in terms of Fc and Ra was obtained at an uncoated insert, cutting speed of 350 m/min, feed rate of 0.1 mm/rev, and depth of cut of 1 mm. Moreover, the feed rate is the most influential parameter on Ra and Fc, with 64.28% and 54.9%, respectively. The developed mathematical models for cutting force (Fc) and surface roughness (Ra) present reliable results with coefficients of determination (R2) of 96.04% and 92.15%, respectively.

scholarly journals Effects of Turning Parameters and Parametric Optimization of the Cutting Forces in Machining SiCp/Al 45 wt% Composite

Metals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 840 ◽  
Author(s):  
Rashid Ali Laghari ◽  
Jianguang Li ◽  
Mozammel Mia
Keyword(s):  
Mathematical Model ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Desirability Function ◽  
Interactive Effect ◽  
Cutting Speed ◽  
Experimental Results ◽  
Machining Process ◽  
Depth Of Cut

Cutting force in the machining process of SiCp/Al particle reinforced metal matrix composite is affected by several factors. Obtaining an effective mathematical model for the cutting force is challenging. In that respect, the second-order model of cutting force has been established by response surface methodology (RSM) in this study, with different cutting parameters, such as cutting speed, feed rate, and depth of cut. The optimized mathematical model has been developed to analyze the effect of actual processing conditions on the generation of cutting force for the turning process of SiCp/Al composite. The results show that the predicted parameters by the RSM are in close agreement with experimental results with minimal error percentage. Quantitative evaluation by using analysis of variance (ANOVA), main effects plot, interactive effect, residual analysis, and optimization of cutting forces using the desirability function was performed. It has been found that the higher depth of cut, followed by feed rate, increases the cutting force. Higher cutting speed shows a positive response by reducing the cutting force. The predicted and experimental results for the model of SiCp/Al components have been compared to the cutting force of SiCp/Al 45 wt%—the error has been found low showing a good agreement.

Influence of process variables on machining characteristics in turning of novel AM alloy

2020 ◽  
pp. 095440542097809
Author(s):  
Sunil Dutta ◽  
Suresh Kumar Reddy Narala
Keyword(s):  
Cutting Force ◽  
Tool Life ◽  
Flank Wear ◽  
Surface Condition ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Experimental Results ◽  
Depth Of Cut ◽  
Input Parameters ◽  
Response Variables

In this paper, the machinability of a fabricated AM alloy (Mg-7 wt%Al-0.9 wt%Mn) has been examined. The novel AM alloy was subjected to turning using a systemized CNC setup. The input turning variables: feed ( f), cutting speed ( v), and depth of cut (DOC) were suitably altered to analyze effects on response variables such as cutting force ( Fc), cutting temperature ( T), and tool life ( TL). Subsequently, the microstructure characterization of the machined surface was done for validating the experimental results. The experimental results established the influence of input parameters on response variables. The cutting force was mostly dominated by DOC, and the cutting temperature was predominantly influenced by cutting speed. The SEM images exhibited the adverse effect of higher values of input parameters on the surface condition. The finest surface was observed at f: 0.1 mm/rev, DOC: 0.5 mm, and v: 115 m/min. Further, the analysis of tool life was done by assessing the flank wear; the measured data showed the significant influence of cutting speed on flank wear. The maximum tool life of 51 min was achieved at the lowest levels of three input parameters.

Experimental Study on the Relationship between Surface Roughness and Cutting Parameters when Face Milling High Strength Steel

2010 ◽  
Vol 139-141 ◽  
pp. 782-787
Author(s):  
Yue Ding ◽  
Wei Liu ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
Jun Han
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
High Strength Steel ◽  
Cutting Speed ◽  
High Strength ◽  
Face Milling ◽  
Depth Of Cut ◽  
Radial Depth ◽  
The Relationship ◽  
Axial Depth

In this study, surface roughness generated by face milling of 38CrSi high-strength steel is discussed. Experiments based on 24 factorial design and Box-Behnken design method are conducted to investigate the effects of milling parameters (cutting speed, axial depth of cut and radial depth of cut and feed rate) on surface roughness, and a second-order model of surface roughness is established by using surface response methodology (RSM); Significance tests of the model are carried out by the analysis of variance (ANOVA). The results show that the most important cutting parameter is feed rate, followed by radial depth of cut, cutting speed and axial depth of cut. Moreover, it is verified that the predictive model possesses highly significance by the variance examination at a level of confidence of 99%. And the relationship between surface roughness and the important interaction terms is nonlinear.

Multi-Objective Optimization Using Box-Behken of Response Surface Methodology for High-Speed Machining of Inconel 718

2014 ◽  
Vol 629 ◽  
pp. 487-492 ◽  
Author(s):  
Mohd Shahir Kasim ◽  
Che Hassan Che Haron ◽  
Jaharah Abd Ghani ◽  
E. Mohamad ◽  
Raja Izamshah ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Cutting Force ◽  
Response Surface ◽  
Tool Life ◽  
Feed Rate ◽  
Inconel 718 ◽  
High Speed ◽  
Cutting Speed ◽  
High Speed Milling

This study was carried out to investigate how the high-speed milling of Inconel 718 using ball nose end mill could enhance the productivity and quality of the finish parts. The experimental work was carried out through Response Surface Methodology via Box-Behnken design. The effect of prominent milling parameters, namely cutting speed, feed rate, depth of cut (DOC), and width of cut (WOC) were studied to evaluate their effects on tool life, surface roughness and cutting force. In this study, the cutting speed, feed rate, DOC, and WOC were in the range of 100 - 140 m/min, 0.1 - 0.2 mm/tooth, 0.5 - 1.0 mm and 0.2 - 1.8 mm, respectively. In order to reduce the effect of heat generated during the high speed milling operation, minimum quantity lubrication of 50 ml/hr was used. The effect of input factors on the responds was identified by mean of ANOVA. The response of tool life, surface roughness and cutting force together with calculated material removal rate were then simultaneously optimized and further described by perturbation graph. Interaction between WOC with other factors was found to be the most dominating factor of all responds. The optimum cutting parameter which obtained the longest tool life of 60 mins, minimum surface roughness of 0.262 μm and resultant force of 221 N was at cutting speed of 100 m/min, feed rate of 0.15 mm/tooth, DOC 0.5 m and WOC 0.66 mm.

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