Experimentation and Prediction of Temperature Rise in Turning Process using Response Surface Methodology

Nickel-based Inconel X-750 superalloy is widely applied in aerospace industry and manufacturing of gas turbine blades, power generators and heat exchangers due to its exclusive properties. As a consequence of low heat transfer coefficient and work-hardening properties, this alloy is known as a poorly machinable alloy. In this work, effect of machining parameters (cutting speed, feed rate and depth of cut) on cutting forces and surface roughness was investigated during turning of Inconel alloy X-750 with coated carbide tool. In order to meet the demands of the environment-friendly cutting processes and human health, biodegradable vegetable oil (BioCut 4600) was selected as the cutting fluid. The results were analyzed using response surface methodology and statistical analysis of variance, and mathematical models for cutting forces and surface roughness were proposed. Results indicated that feed rate and cutting speed were the most effective parameters on the surface roughness. However, depth of cut was the most effective parameter on cutting forces in comparison with cutting speed and feed rate. Eventually, in order to achieve the main aims of industrial production in large amounts and green manufacturing, the ranges for the best cutting conditions were presented.

The present paper investigates the cutting parameters pertaining to the turning of X2CrNi18-09 austenitic stainless steel that are studied and optimized using both RSM and desirability approaches. The cutting tool inserts used are the CVD coated carbide. The cutting speed, the feed rate and the depth of cut represent the main machining parameters considered. Their influence on the surface roughness and the cutting force are further investigated using the ANOVA method. The results obtained lead to conclude that the feed rate is the surface roughness highest influencing parameter with a contribution of 89.69%.The depth of cut and the feed rate are further identified as the most important parameters affecting the cutting force with contributions of 46.46% and 39.04% respectively. The quadratic mathematical models presenting the progression of the surface roughness and the cutting force and based on the machining parameters considered (cutting speed, feed rate and depth of cut) were obtained through the application of the RSM method. They are presented and compared to the experimental results. Good agreement is found between the two sections of the investigation. Furthermore, the flank wear of the CVD-coated carbide tool (GC2015) is found to increase with both cutting speed and cutting time. A higher tool life represented by t=44min is observed at cutting speed, feed rate and depth of cut of 280m/min,0.08mm/rev and 0.2mm respectively. Moreover and at low cutting speeds, the formation of micro weld is noticed and leads to an alteration of the surface roughness of the work piece. Finally, optimizing the machining parameters with the objective of achieving an improved surface roughness was accomplished through the application of the Desirability Function approach. This enabled to finding out the optimal parameters for maximal material removal rate and best surface quality for a cutting speed of 350m/min, a feed rate of 0.088 mm/rev and a depth of cut of 0.9mm.

The surface roughness model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radius under different cutting conditions. The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels.The established equation and graphs show that the feed rate and cutting speed were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut, but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant. However, it could be seen that the first-order affect of feed rate was significant while cutting speed and depth of cut was insignificant.The predicted surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.

Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN250 steel

Introduction: Among alloys of medium-carbon and high-strength steel, EN 24 steel is characterised by its nickel-chromium-molybdenum composition. EN 24 steel is highly suitable for application in heavy-duty projects due to its notable resilience to damage, especially when exposed to low temperatures. With the objective of minimising surface irregularities, this research endeavours to enhance the milling process of EN 24 steel by employing coated tungsten carbide (WC) tool inserts.Methods: Feed rate, cutting speed, depth of cut, and cutting fluid are all crucial process factors in the experimental investigation. Four distinct levels are applied to each factor. The research utilises the Design of Experiments (DOE)-based Central Composite Design of Response Surface Methodology. To predict output parameters, mathematical models are developed utilising analysis of variance (ANOVA) for optimisation purposes.Results and discussions: Through the utilisation of multi-objective optimisation, the optimal combination for tungsten carbide inserts was determined, which provided surface irregularities of 0.301 µm. Cutting speed (CS) of 149.507 m/min, feed rate (FR) of 340.27 mm/min, depth of cut (DOC) of 0.599 mm, and cutting fluid (CF) of 12.50 L/min are the optimal parameters. The surface morphologies of the machined workpiece at particular parameter values can be discerned through scanning electron microscope (SEM) analysis, yielding significant insights. The optimal parameters that have been identified provide practical recommendations for improving the milling method of EN 24 steel when tungsten carbide inserts are utilised. Understanding the milling process in its entirety is facilitated by SEM analysis of surface morphologies and microstructures under particular cutting conditions. The morphology and surface irregularities of the machined workpiece are evaluated using profilometry, which provides additional insight into surface integrity. The discourse investigates the potential applications and implications of the results, as well as suggests directions for further study concerning the enhancement of milling processes for similar steel alloys.

The aim of this research is to study the machinability aspects of hardened AISI 4340 High Strength Low Alloy (HSLA) steel (50 ± 2 HRC (Hardness Rockwell C)). The experimental investigation using coated carbide inserts is carried out during the dry hard milling process in a sustainable environment. The input parameters in the study are speed, feed rate and depth of cut and the responses are Average surface Roughness (Ra) and Material Removal Rate (MRR) that are selected through screening. Central Composite Design (CCD) in response surface methodology has been utilized as the experimental design technique with twenty experiments. Analysis of variance has been employed to examine the momentous machining parameters and responses. A mathematical model has been developed to optimize the surface roughness and material removal rate. It has been observed that the most significant factor for Ra is feed rate while for MRR depth of cut is the most significant factor. The results show that the minimum value of Ra ~ 0.098 μm is achieved at speed ~ 1000 RPM, feed rate ~ 300 mm/min and depth of cut ~ 0.2 mm while the maximum value of MRR ~ 6.35 cm3/min is attained at feed rate ~ 500mm/min and depth of cut ~ 0.4 mm regarding less or no effect of speed ~ 500-1000 RPM. The average forecast error for the validation information has been observed to be 3.35%. for Ra and 3.2% for MRR. Further, it is investigated that good surface finish like grinding and dimensional accuracy can be achieved with coated carbide tools.

This article presents the tool life study of two different grades of Inconel 718. Tool life of ball nose cutting tools were investigated by considering the numerical parameters of cutting speed, feed rate, depth of cut and width of cut. The categorical factor is material grade. Two sets of different cutting parameters that were previously using design of experiment (DOE) approaches were combined and analysed using historical data of response surface methodology (RSM). This method can be used to determine the dominant factors to identify the interaction between cutting parameter and tool life. ANOVA result shows that the type of material with different grade is not significant in contributing to tool life compared to width of cut, cutting speed, feed rate, and depth of cut. The best combination for untreated Inconel 718 is Vc = 102 m/min, fz = 0.11 mm/tooth, ap = 0.52 mm and ae = 0.28 mm in order to obtain predicted too life of 127 min, whereas the best combination of double aging is Vc = 114 m/min, fz 0.11 mm/tooth, ap 0.61 and ae 0.21 to obtain 113 min of tool life. The study shows that Historical Data method is suitable for finding the optimization condition from different DOE approaches.

Optimization of cutting temperature and surface roughness in CNC turning of Ti-6Al-4V alloy using response surface methodology

Because of its high corrosion resistance and ability to preserve mechanical qualities at high temperatures, Stainless steels are used in a variety of applications, including automotive, aerospace, and marine. In metal turning, cutting speed, feed rate, and depth of cut are all essential machining parameters . The settings of these parameters determine the quality of the final turning results. The goal of this research is to see how changing these parameters affects the output factor (Surface Roughness). In addition, the behavior of stainless steel 440 C in dry turning conditions is being investigated for purpose to improve cutting conditions. In response surface methodology (RSM), the box-behnken design (BBD) technique is used, the surface roughness was modeled as a result to the parameters of cutting. The 17 trial runs were built using Design Expert (v12) to develop and test the empirical surface roughness mathematical model. The results indicated that the roughness is strongly affected by the feed rate, followed by cutting speed and depth of cut.

The quality of machined parts and the productivity of machining that leads to economic sustainability. These factors are also vital for machinability improvement for materials, as well as, for economically sustainable manufacturing. Due to their poor machinability titanium alloys (Ti-alloys) are categorised as difficult-to-machine materials. For the same reason products made of Ti-alloys are highly expensive and are used only in strategic and sophisticated industries. A series of real-life experimental investigations was carried out to reveal the economic optimal zones of machining parameters that can produce the best possible surface roughness in machining Ti-6Al-4V alloy, using the coated carbide cutting tools, in shortest period of operation time. As the output of the research, for using the coated carbide tools for machining the investigated Ti-alloy, optimal zones of cutting speed, feed rate and depth of cut have been proposed and presented in graphical format. The current research revealed that all three groups (with nose radius Nr = 0.4, 0.8, and 1.2 mm) of coated carbide tools are capable to produce best surface finish, ranging between Ra = 0.5 - 1.0 µm, with cutting speed starting at V = 60 m/min and beyond at least up to V = 250 m/min while keeping the feed rate and depth of cut as constants as f = 0.1 mm/rev and d = 0.5 mm. The data on the graphs may help researchers, engineers and manufacturers to select optimal economic cutting speed, feed rate and depth of cut to achieve a certain level of surface roughness of machined components as assigned by the product designer on the part drawing. This reduces the production cost substantially, reduces number of defect products and improves product quality for machined parts.

This research presents the performance of Aluminum nitride ceramic in end milling using using TiAlN and TiN coated carbide tool insert under dry machining. The surface roughness of the work piece and tool wear was analyzed in this. The design of experiments (DOE) approach using Response surface methodology was implemented to optimize the cutting parameters of a computer numerical control (CNC) end milling machine. The analysis of variance (ANOVA) was adapted to identify the most influential factors on the CNC end milling process. The mathematical predictive model developed for surface roughness and tool wear in terms of cutting speed, feed rate, and depth of cut. The cutting speed is found to be the most significant factor affecting the surface roughness of work piece and tool wear in end milling process.

Design of Experiments is employed to study the stimulus of cutting parameters such as feed rate, spindle speed, depth of cut in the turning operation of AISI-310 and optimizing the value of those parameters for getting the higher material removal rate (MRR) and minimal surface roughness. A prediction model has been developed by using the above influencing parameters. For the purpose of parameters optimization we investigate the parameters using Response Surface Methodology (RSM). It is shown that feed rate is the main parameter in influencing the surface roughness, which is being followed by spindle speed and depth of cut. It is found that surface roughness and feed rate were directly proportional to each other for some extent. The confirmation tests were carried out to with the optimum set of parameters and are verified with test results. The comparison of above two results were found to be good with maximum error within 5% on comparing it with the predicted model.

The present research investigates the effect of turning environments and parameters on surface integrity induced by turning of AA6061-T6. Specifically, the evolution of turning parameters of cutting speed, feed rate, and depth of cut was studied under dry, minimum quantity lubrication (MQL), and wet environments and their impact on surface roughness and residual stresses, as critical parameters for surface integrity, were quantified. Machining tests were carried out using a design of experiment (DoE) based on central composite design (CCD) under the three turning environments. The most effective turning parameters were identified for each environment using analysis of variance (ANOVA). Response surface method (RSM) was used to predict effective regression models for each turning environment for the average arithmetic surface roughness, the height peak from the valley, the axial surface residual stress, and the hoop surface residual stress. Then, using the predictive regression models, a multi-objective optimization study was performed to determine optimal turning parameters in each environment for improved surface integrity in low speed turning (LST) and high speed turning (HST) of AA6061-T6. The results showed that feed rate and cutting speed were the most effective parameters on surface integrity. It was also found that better surface integrity and higher material removal rate (MRR) were achieved using MQL mode, which is an environmental friendly and cost-saving turning environment.

Machining of bone: Analysis of cutting force and surface roughness by turning process.

Titanium alloys find wide applications in aerospace, defence, and surgical industries due to their unique high strength- to- weight ratio which is maintained even at high temperatures and also their exceptional corrosion resistance. The machining of these materials is a thermally dominant process. At high temperature, they become chemically active and tend to react with tool materials. In the present study an attempt has been made to investigate the effect of cutting parameters (cutting speed, feed rate and depth of cut) on surface roughness in turning a Ti6Al4V Titanium alloy with a medium temperature chemical vapor deposition tool insert. Experiments have been conducted using Taguchi’s experimental design technique. Optimum cutting parameters for minimizing surface roughness have been determined by using the desirability function based approach. A second order model has been established between the cutting parameters and the surface roughness, using the response surface methodology. Predicted values and measured values fairly tally and it indicates that the developed model can be effectively used to predict the surface roughness in the machining of Ti6Al4V Titanium alloy. Experimental results reveal that among the cutting parameters, the feed rate is the most significant machining parameter for surface roughness, followed by depth of cut and cutting speed.