Optimizing Feed Force in Turning Process Using Taguchi’s Parameter Design Approach

2014 ◽  
Vol 592-594 ◽  
pp. 668-672
Author(s):  
Praveen Kumar ◽  
Hari Singh

The objective of the paper is to obtain an optimal setting of turning process parameters (cutting speed, depth of cut and feed rate) resulting in an optimal value of the feed force when machining En19 steel with tungsten carbide cutting tool inserts. The effects of the selected turning process parameters on feed force and the subsequent optimal settings of the parameters have been accomplished using Taguchi’s parameter design approach. It was indicated by the results that the selected turning process parameters significantly affect the selected machining characteristic. The percent contributions of parameters as quantified in the S/N ANOVA envisage that the relative power of cutting speed (72.09 %) in controlling variation and mean feed force is significantly higher than that of the depth of cut (22.30 %) and feed rate (05.31 %). The predicted optimum feed force is 98.067 N. The results have been validated by the confirmation experiments.

2016 ◽  
Vol 852 ◽  
pp. 255-259 ◽  
Author(s):  
B. Singaravel ◽  
Chimmalagi Marulaswami ◽  
Thangiah Selvaraj

Turning is one of the fundamental machining operations and its process parameters leads to better machining performance. The economic benefit of turning operation is providing components with appropriate dimensional accuracy. In this work, the effects of process parameters on dimensional accuracy (circularity and cylindricity) parameters are analyzed in turning of EN25 steel. The process parameters considered are cutting speed, feed rate and depth of cut in order to minimize circularity and cylindricity. The result revealed that the minimum dimensional accuracy error values such as circularity and cylindricity are obtained in the combination of higher value of cutting speed and lower value of feed rate and depth of cut. This analysis is used to meet the machined work piece within the tolerance limit and improve the quality criteria.


2020 ◽  
Vol 19 (4) ◽  
pp. 547-558
Author(s):  
M. Ficko ◽  
D. Begic-Hajdarevic ◽  
V. Hadziabdic ◽  
S. Klancnik

The research deals with the optimisation of CNC turning process parameters to determine the optimal parametric combination that provides the minimal surface roughness (Ra) and maximal material removal rate. The experiment was conducted by the CNC turning process of S355J2 carbon steel. Data from the Taguchi design of experiments were the subject of analysis with Grey Relational Analysis (GRA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In the present study, three process parameters, such as cutting speed, feed rate and depth of cut, were chosen for the experimentation. It was found that 250 m/min cutting speed, 0.10 mm/rev feed rate and 1.8 mm depth of cut presented the optimal parametric combination by both used multi-objective optimisation methods. Analysis of variance (ANOVA) at a 95 % confidence level was used to determine the most significant parameters. Finally, the accuracy of GRA and TOPSIS results were validated by confirmation experiments.


Author(s):  
C. Divya ◽  
L. Suvarna Raju ◽  
B. Singaravel

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.


Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2998 ◽  
Author(s):  
Kubilay Aslantas ◽  
Mohd Danish ◽  
Ahmet Hasçelik ◽  
Mozammel Mia ◽  
Munish Gupta ◽  
...  

Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.


Author(s):  
Nilrudra Mandal ◽  
B Doloi ◽  
Biswanath Mondal ◽  
BK Singh

An attempt has been made to apply the Taguchi parameter design method and multi-response optimization using desirability analysis for optimizing the cutting conditions (cutting speed, feed rate and depth of cut) on machining forces while finish turning of AISI 4340 steel using developed yttria based zirconia toughened alumina inserts. These zirconia toughened alumina inserts were prepared through wet chemical co-precipitation route followed by powder metallurgy process. The L9 (4) orthogonal array of the Taguchi experiment is selected for three major parameters, and based on the mean response and signal-to-noise ratio of measured machining forces, the optimal cutting condition arrived for feed force is A1, B1 and C3 (cutting speed: 150 m/min, depth of cut: 0.5 mm and feed rate: 0.28 mm/rev) and for thrust and cutting forces is A3, B1 and C1 (cutting speed: 350 m/min, depth of cut: 0.5 mm and feed rate: 0.18 mm/rev) considering the smaller-the-better approach. Multi-response optimization using desirability function has been applied to minimize each response, that is, machining forces, simultaneously by setting a goal of highest cutting speed and feed rate criteria. From this study, it can be concluded that the optimum parameters can be set at cutting speed of 350 m/min, depth of cut of 0.5 mm and feed rate of 0.25 mm/rev for minimizing the forces with 78% desirability level.


2019 ◽  
Vol 26 (02) ◽  
pp. 1850139 ◽  
Author(s):  
A. PALANISAMY ◽  
T. SELVARAJ

In this work, an attempt has been made to optimize the process parameters on turning operation of INCOLOY 800H, with the aid of cryogenically treated (24[Formula: see text]h, 12[Formula: see text]h and untreated) multi-layer chemical vapor deposition (CVD) coated tools. The influencing factors like cutting speed, feed rate, depth of cut and cryogenic treatment were selected as input parameters. Surface roughness, microhardness and material removal rate (MRR) were considered as output responses. The experimentation was planned and conducted based on Taguchi L27 standard orthogonal array (OA) with three levels and four factors. Multi-criteria decision making (MCDM) methods like grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) have been used to optimize the turning parameters in this work. Similar results were obtained from these MCDM techniques. Analysis of variance (ANOVA) was employed to identify the significance of the process parameters on the responses. Experimental research proved that machining performance could be improved efficiently at cutting speed is 55[Formula: see text]m/min, feed rate is 0.06[Formula: see text]mm/rev, depth of cut is 1[Formula: see text]mm and 24[Formula: see text]h cryogenically treated tool. Tool wear was analyzed for the cutting tool machined at the optimum cutting condition with the help of scanning electron microscope (SEM) and energy dispersion spectroscopy (EDS). Dry sliding wear test was also conducted for the optimal condition. The percentage improvement in machining performances is 12.70%.


2021 ◽  
Vol 27 (4) ◽  
pp. 296-305
Author(s):  
Arpit Srivastava ◽  
Mukesh Kumar Verma ◽  
Ramendra Singh Niranjan ◽  
Abhishek Chandra ◽  
Praveen Bhai Patel

Abstract Aluminum alloy 7075-T651 is a widely used material in the aviation, marine, and automobile sectors. The wide application marks the importance of this material’s research in the manufacturing field. This research focuses on optimizing input process parameters of the turning process in the machining of Aluminum 7075-T651 with a tungsten carbide insert. The input machining parameters are cutting speed, feed, and depth of cut for the output response parameters cutting force, feed force, radial force, material removal, and surface roughness of the workpiece. For optimization of process parameters, the Taguchi method, with standard L9 orthogonal array, is used. ANOVA is applied to obtain signifi-cant factors and optimal combinations of process parameters.


2018 ◽  
Vol 14 (1) ◽  
pp. 67-76
Author(s):  
Mohanned Mohammed H. AL-Khafaji

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).


2012 ◽  
Vol 59 (2) ◽  
Author(s):  
Jaharah A. Ghani ◽  
Poh Siang Jye ◽  
Che Hassan Che Haron ◽  
Muhammad Rizal ◽  
Mohd Zaki Nuawi

Turning process is widely used in the production of components for automotive and aerospace applications. The machinability of a work material is commonly assessed in terms of cutting tool life, surface finish, and cutting force. These responses are dependent on machining parameters such as cutting speed, feed rate, and depth of cut. In this study, the relationships between cutting force, cutting speed, and sensor location in the turning process were investigated. Strain gauge was chosen as the sensor for the detection of cutting force signal during turning of hardened plain carbon steel JIS S45C. Two strain gauges were mounted on a tool holder at a defined location of I, II, or III at a distance of 37, 42, or 47 mm, respectively, from the cutting point. Only one set of machining experiments was conducted at spindle speed = 1000 rpm, feed = 0.25 mm/rev, and depth of cut = 0.80 mm. The turning process was stopped and the insert was discarded when average flank wear reached 0.30 mm. The main cutting force and the feed force for each cycle measured by the strain gauges at location I, II, and III were collected and analyzed. Results show that when cutting speed was increased, the main cutting force and the feed force were decreased accordingly. The change of was inversely proportional to the change of cutting speed, but the did not decrease continuously and behaved contrarily. A strain gauge placed at a distance of approximately 43 mm from the cutting point was found to be the best and most suitable for sensing accurate force signals.


2013 ◽  
Vol 415 ◽  
pp. 666-671
Author(s):  
Surasit Rawangwong ◽  
Jaknarin Chatthong ◽  
Worapong Boonchouytan

This research study aimed to investigate the effect of main factors on the surface roughness in oil palm wood turning process for manufacturing furniture parts using carbide tools. The main factors, namely, cutting speed, feed rate and depth of cut were investigated for the optimum surface roughness in furniture manufacturing process. The result of preliminary trial shown that the depth of cut had no effect on surface roughness. Moreover, the experiment was found that the factors affecting a surface roughness were cutting speed and feed rate, with having tendency for reduction of roughness value at lower feed rate and greater cutting speed, Therefore in the turning process of oil palm wood, it was possible to determine a cutting condition by means of the equation Ra = 19.8-0.00742 Cutting Speed+3.98 Feed rate, This equation can be best used with limitation of cutting speed at 122-450 m/min, feed rate at 0.1-0.5 mm/rev and depth of cut does not over 1 mm,. To confirm the experiment result, a comparison between the equation value and an actual value by estimating a prediction error value was calculate with the surface roughness and margin of error does not over 10%. The experimental result reveals the mean absolute percentage error (MAPE) of the equation of surface roughness is 3.24%, which is less than the predicted error value and it is acceptable.


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