Determination of Optimal Parameters for SKD11 CNC Turning Process

Many difficult to machine materials, such as Inconel 625Ni-based super alloy, are uncommon class of metallic materials with exceptional combination of greater thermal strength, toughness and resistance to deterioration. They have extensive applications in the manufacturing of new aero-engines, besides its enormous uses in marine, chemical and oil & petrochemical industries. In the context of its wide range of applications, there is a need for efficiently processing better methods in the manufacturing of such difficult to machine materials. This study consists of the turning operation of Ni-based super alloy Inconel 625 without coolant, carried out by physical vapour deposition (PVD) coated carbide inserts. The response parameters, such as surface roughness and material removal rate were evaluated in terms of cutting speed, feed rate and depth of cut. Sixteen experiments were carried out, based on Taguchi's Design of Experiments using orthogonal array. The resulting analysis was done based on response graph. The experimental results revealed that the feed rate was the most influential factor, followed by the depth of cut and cutting speed. The optimal parameters achieved were cutting speed of 90 m/min, the feed rate of 0.35 mm/rev and the depth of cut 0.2 mm.

This study focuses on optimizing cutting parameters based on the Taguchi method to minimize surface roughness in turning of studs manufactured from AISI 5140 steel. The Taguchi method, which is a powerful tool for designing optimized quality, is used to find the optimum surface roughness in turning operations. Rotational speed, feed rate and depth of cut were considered as control factors for the surface roughness, and L9 orthogonal array was determined for experiment trials. An orthogonal array, a signal-to-noise ratio, and an analysis of variance were employed to investigate the surface roughness characteristics of AISI 5140 steel. Minimum surface roughness was obtained at 2000 rpm rotational speed, 0.2 mm × rev−1 feed rate and 0.5 mm depth of cut. Optimal surface roughness was calculated as 1.70 μm by using optimal level of design parameters. Confirmation test showed that Taguchi method can be used precisely for optimizing the cutting parameters in turning of AISI 5140 steel. Through this study, it is possible to not only obtained the optimum surface roughness for turning operations, but also the main cutting parameters affecting the performance of turning operations. The developed model can be used in the metal machining industries in order to determine the optimum cutting parameters for minimum surface roughness.

Nowadays, aluminum and its alloys are used for different modern applications due to its improved mechanical properties like low density, good structural rigidity, etc. The purpose of this paper is to identify the optimal setting of machining parameters speed, feed rate and depth of cut on surface roughness (Ra), and material removal rate (MRR) in the face milling process. An L27 orthogonal array is used for face milling of Al 6061 T6 alloy. The surface roughness (Ra) and MRR are estimated and analyzed using the Taguchi design of experiment method for the identification of optimum controllable parameter combinations. ANOVA is utilized to explore the most significant parameter affecting the surface roughness and MRR. At long last, a multiresponse regression investigation is performed to study the consolidated impact of the two responses. Taguchi S/N ratio examination and ANOVA investigation conclude that feed rate is a significant parameter for surface finish followed by the speed and depth of cut, respectively. Again feed rate and depth of cut have an equivalent impact on the S/N ratios of material removal rate and speed does not affect the material removal rate. This research will add a new dimension to select the optimum values of parameters for surface finish and material removal rate which reduces the manufacturing time, manufacturing cost as well as increases the quality and productivity of the components.KeywordsAl6061MillingSurface roughnessMaterial removal rateTaguchiRegression analysis

Fused deposition modeling (FDM) is widely applied in various fields due to its affordability and ease of use. However, it faces challenges such as achieving high surface quality, precise dimensional tolerance, and overcoming anisotropic mechanical properties. This review analyzes and compares the machinability of 3D-printed PLA, PETG, and carbon-fiber-reinforced PETG, focusing on surface roughness and burr formation. A Design of Experiments (DoE) with a full-factorial design was used, considering three factors: rotation speed, feed rate, and depth of cut. Each factor had different levels: rotational speed at 3000, 5500, and 8000 rpm; feed rate at 400, 600, and 800 mm/min; and depth of cut at 0.2, 0.4, 0.6, and 0.8 mm. Machinability was evaluated by roughness and burr height using a profilometer for all the materials under the same milling conditions. To evaluate the statistical significance of the influence of various processing parameters on surface roughness and burr formation in 3D-printed components made of three different materials—PLA, PETG, and carbon-fiber-reinforced PETG—an analysis of variance (ANOVA) test was conducted. This analysis investigated whether variations in rotational speed, feed rate, and depth of cut resulted in measurable and significant differences in machinability results. Results showed that milling parameters significantly affect roughness and burr formation, with optimal conditions for minimizing any misalignment highlighting the trade-offs in parameter selection. These results provide insights into the post-processing of FDM-printed materials with milling, indicating the need for a balanced approach to parameter selection based on application-specific requirements.

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.

Quality of finished miniature products is characterized by surface roughness as well as burr formation after manufacturing processes.It gains more significance when it is gauged in terms of high precision and dimensional accuracy of final micro parts.The requirement of complex features in 3D micro parts also figures out its significance.Similarly, tool wear is an important indicator of production efficiency and quality related to finished parts.In the current research, the impact of key input parameters like depth of cut, feed rate, cutting speed and various tool coatings (TiAlN, TiSiN, nACo, including an uncoated tool) were statistically analyzed while carrying out micro-milling of Monel 400 super alloy.Surface roughness along with burr formation and tool wear were considered as response parameters due to their significant nature.Machining experiments were performed up to 80,000 rpm (high-speed range).Feed rate values were selected in comparison with cutting tool edge radius.The selected values of feed rate were taken into consideration at moderate and high-speed ranges while selecting the values equal to below and above the values of cutting-edge radius.Digital microscopy and scanning electron microscope (SEM) were utilized for analysis in addition to statistical techniques for response parameters.Methodology utilizes Taguchi's Experimental design.L16 orthogonal array was formulated to carry out micro milling experiments on Monel 400 specimen, having dimensions 203040 mm.Contribution ratio (CR) of individual input parameter was calculated through Analysis of Variance (ANOVA).The outcome of experimental work indicated that feed rate was the most significant factor for surface roughness with CR 27.86%.It also became most significant factor for top burr width in both categories (Up-milling & down-milling) with CR 56.56% and 56.60% respectively.Moreover, it was also most significant factor for top burr height in both categories (Up-milling and down-milling) with CR 23.84% and CR 28.47% respectively.Whereas in case of tool wear, the depth of cut and tool coatings were significant factors with CR 19.46% and 28.47% respectively.The findings in this work highlighted the importance of selection of suitable cutting conditions with appropriate tool coatings in micro-machining in enhancing productivity, quality and cost effect.In addition, the significance of burr height parameter, mainly unexplored till now, has also been underlined.

Optimization of flank wear using Zirconia Toughened Alumina (ZTA) cutting tool: Taguchi method and Regression analysis

Surface roughness has a significant role in the life cycle of mechanical components. Numerous secondary finishing operations are performed to achieve the desired roughness value. The aim of this study is to obtain better surface finish by optimizing the input parameters at primary stage of face milling operation. Effect of machining parameters (cutting velocity, feed rate, and depth of cut) and machining strategies (rolling direction, cutter offset, soaking time) are taken into consideration. Taguchi’s L27 orthogonal array is used for the design of experiments (DOE). Face milling of rolled steel (AISI 1040) is performed on vertical milling centre (HURCO-VM10) using titanium nitride (TiN)-coated carbide inserts. Surface roughness (SR) is evaluated in terms of signal-to-noise ratio (SNR). Analysis of means (ANOM) is applied on SNR to find the optimal levels of each input parameter. Moreover, significance level and percentage contribution of parameters is calculated using analysis of variance (ANOVA). Feed rate followed by cutting velocity is found the major contributors. Confirmation test is carried out to evaluate the amount of improvement and validation of predicted model. Improvement of 8.41 dB in SR is observed.

Optimization of Feed and Radial Force in Turning Process by using Taguchi Design Approach

In this study, the milling behavior of AISI D2 cold work tool steel was experimentally investigated on a CNC vertical machining center. The aim was to optimize surface roughness through the Taguchi L18 orthogonal array design, considering the effects of cooling method, spindle speed, feed rate, and depth of cut. A total of 18 experiments were conducted under both wet and dry machining conditions. The results revealed that the use of coolant generally led to higher roughness values compared to dry machining. Statistical analysis using signal-to-noise (S/N) ratios and analysis of variance (ANOVA) showed that coolant application had the highest impact on surface roughness with a contribution rate of 47.04%, followed by spindle speed (27.99%), feed rate (8.05%), and depth of cut (4.66%). Regression models were developed to predict surface roughness, achieving a high correlation with experimental values (R² = 0.90). Confirmation experiments verified the optimization, with the optimal parameter combination (dry machining, 4000 rpm, 750 mm/min feed rate, and 0.10 mm depth of cut) reducing the average surface roughness from 1.08 μm to 0.37 μm, corresponding to a 65.7% improvement. Additionally, quality loss analysis indicated that losses were minimized by nearly 88.3% under optimized conditions. The results indicate that surface roughness values obtained under dry machining conditions were lower than those achieved using coolant in the milling of AISI D2 tool steel.

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.

The aim of this research paper is to investigate the machinability of CSN 12050 carbon steel bars using carbide insert tool in order to utilize the optimum cutting parameters by employing Taguchi approach. Experiments have been performed under dry cutting condition using an optimization approach according to Taguchi’s L9(34) orthogonal arrays; signal-to-noise ratio tests are designed. Analysis of variance (ANOVA) was performed to determine the importance of machining parameters on the material removal rate (MRR). The results were analyzed using signal-to-noise ratios (S/N); 3D surface graphs, main effect graphs of mean, and predictive equations are employed to study the performance characteristics. The optimal parameters resulted as A3B2C3 (i.e., cutting speed 275 (m/min), depth of cut 0.35 (mm), and feed rate 0.25 (mm/rev), respectively). In the present study, there is an improvement of 5.22 dB at optimal cutting conditions for each significant MRR response parameters such as cutting speed, depth of cut, and feed rate. With these proposed optimal parameters, it is possible to optimize machinability for product sustainability.

This research is made to investigate the effectiveness of Minimum Quantity Lubrication (MQL) over flood-cooling lubrication in lathe turning operation on a 1-inch-thick mild steel rod. The cutting tool used for this operation was a tungsten carbide Chemical Vapor Deposition (CVD) coating. Two results needed to be determined; surface roughness value and chip formations. These were carried out using an orthogonal array (OA), and the analysis of variance (ANOVA). The experiment was carried out using cutting speeds of 460, 750 and 1250 rpm and feed rates of 0.2, 0.4 and 0.8 mm/rev. The depth of cut was maintained at 0.125 mm throughout the whole experiment. It was observed that cutting speed and feed rate have significant effect on surface roughness. In terms of chips produced from the turning operation, there were more discontinuous chips being obtained in flood-cooling conditions than in MQL conditions. In comparison, more segmented chips were produced in MQL conditions. The optimum process parameter setting of the experimental design was obtained, with high cutting speed and low feed rate in both MQL and flood-cooling lubrication.

In this study, surface roughness values, sound levels and instantaneous current values were measured with calibrated devices in accordance with the experimental parameters. In this study, turning tests were carried out on AISI S1 steel material workpieces at three different depth of cuts, three different feed rates and 3 different cutting speeds without coolant. A full factorial experimental design method was used. Three different cutting speeds (135, 155, 175 m/min), feed rates (0.045, 0.090, 0.135 mm/rev) and depth of cuts (0.04, 0.08, 0.12 mm) as control factors have been selected. The effect levels on the surface roughness of the control factors with analysis of variance (ANOVA) performed using the experimental results were determined. Finally, the confirmation tests were performed and showed that the analysis is successfully implemented. As a result of analysis, the most effective cutting parameter on all the output parameters was found to be the feed rate. Its influence on the sound level was found to be 60.26%. The feed rate was followed by the cutting speed (22.87%) and the depth of cut (6.58%), respectively. The motor current values were influenced by feed rate, cutting speed and depth of cut by 52.71%, 18.73% and 23.88%, respectively.

A research was conducted for the optimization of the turning process st 60 tool steel with multiple performance characteristics based on the orthogonal array with Taguchi-WPCA method. Minimum Quantity Cooling Lubrication (MQCL) metode was applied as a coolant. The experimental studies were conducted under varying the cutting speed, feeding, depth of cut and type of coolant. The optimized multiple performance characteristics were surface roughness, and material removal rate. An orthogonal array, signal-to-noise ratio, grey relational analysis, weighted pricipal component analysis and analysis of variance were employed to study the multiple performance characteristics. Experimental results show that cutting speed gives the highest contribution for minimize of surface roughness and maximize of material removal rate, followed by feeding speed, type of coolant and depth of cut. The minimum of surface roughness and maximize of material removal rat could be obtained by using the values of cutting speed, feeding speed, depth of cut and type of coolant of 172.95 m/minute, 0.053 mm/rev, 0.25 mm, and vegetable oil as a coolant respectively.