scholarly journals Machining force comparison for surface defect hard turning and conventional hard turning of AISI 52100 steel

2021 ◽  
Vol 13 (3) ◽  
pp. 205-214
Author(s):  
P. U MAMAHESWARRAO ◽  
D. RANGARAJU ◽  
K. N. S. SUMAN ◽  
B. RAVISANKAR

In this article, a recently developed method called surface defect machining (SDM) for hard turning has been adopted and termed surface defect hard turning (SDHT). The main purpose of the present study was to explore the impact of cutting parameters like cutting speed, feed, depth of cut, and tool geometry parameters such as nose radius and negative rake angle of the machining force during surface defect hard turning (SDHT) of AISI 52100 steel in dry condition with Polycrystalline cubic boron nitride (PCBN) tool; and results were compared with conventional hard turning (CHT). Experimentation is devised and executed as per Central Composite Design (CCD) of Response Surface Methodology (RSM). Results reported that an average machining force was decreased by 22% for surface defect hard turning (SDHT) compared to conventional hard turning (CHT).

2021 ◽  
Vol 13 (1) ◽  
pp. 211-224
Author(s):  
P. UMAMAHESWARRAO ◽  
D. RANGARAJU ◽  
K. N. S. SUMAN ◽  
B. RAVISANKAR

In the present work by employing the Technique for order of preference by similarity to ideal solution (TOPSIS) machining parameters optimization is performed with polycrystalline cubic boron nitride (PCBN) tools while AISI 52100 steel hard turning (HT). Based on the CCD of RSM, 32 experimental runs were performed by varying cutting speed, feed, depth of cut, nose radius, and negative rake angle to identify the optimal level of the process parameters. In this study, the multiple performance characteristics measured are machining force, surface roughness, and workpiece surface temperature. To ascertain the impact of cutting parameters on responses, Analysis of Variance (ANOVA) was deployed. An optimum combination of input process parameters for the multiple performance characteristics should be as follows: speed 200 rpm, feed 0.1 mm/rev, depth of cut 0.8 mm, nose radius 1.2 mm, and negative rake angle 45º leading to the value of optimum response variables machining force 561.163 N, Surface roughness 0.507μm and workpiece surface temperature 84.38°C.


2019 ◽  
Vol 818 ◽  
pp. 87-91 ◽  
Author(s):  
P. Umamaheswarrao ◽  
D. Ranga Raju ◽  
K.N.S. Suman ◽  
B. Ravi Sankar

In the present work hard turning of AISI 52100 steel has been performed using Polycrystalline cubic boron nitride (PCBN) tools. The input parameters considered are cutting speed, feed, depth of cut, nose radius and negative rake angle and the measured responses are machining force and workpiece surface temperature. Experiments are planned as per Central Composite Design (CCD) of Response Surface Methodology (RSM). The effect of input parameters and their interactions are discussed with main effects plot. Further, the multi-objective optimization scheme is proposed by adopting Grey Relational Analysis (GRA) coupled with Principle Component Analysis (PCA). Results demonstrated that speed is the most significant factor affecting the responses followed by negative rake angle, feed, depth of cut, and nose radius. The optimum cutting parameters obtained are cutting speed 1000 rpm, feed 0.02 mm/rev, depth of cut 0.5 mm, Nose radius 1 mm and Negative rake angle 5o.


2015 ◽  
Vol 15 (3) ◽  
pp. 309-318 ◽  
Author(s):  
Suha K. Shihab ◽  
Zahid A. Khan ◽  
Arshad Noor Siddiquee

AbstractEffect of cryogenic hard turning parameters (cutting speed, feed rate, and depth of cut) on surface roughness (Ra) and micro-hardness (µH) that constitute surface integrity (SI) of the machined surface of alloy steel AISI 52100 is investigated. Multilayer hard surface coated (TiN/TiCN/Al2O3/TiN) insert on CNC lathe is used for turning under different cutting parameters settings. RSM based Central composite design (CCD) of experiment is used to collect data for Ra and µH. Validity of assumptions related to the collected data is checked through several diagnostic tests. The analysis of variance (ANOVA) is used to determine main and interaction effects. Relationship between the variables is established using quadratic regression model. Both Ra and µH are influenced principally by the cutting speed and the feed rate. Model equations are found to predict accurate values of Ra and µH. Finally, desirability function approach for multiple response optimization is used to produce optimum SI.


Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1726
Author(s):  
S. Parasuraman ◽  
I. Elamvazuthi ◽  
G. Kanagaraj ◽  
Elango Natarajan ◽  
A. Pugazhenthi

Reinforced aluminum composites are the basic class of materials for aviation and transport industries. The machinability of these composites is still an issue due to the presence of hard fillers. The current research is aimed to investigate the drilling topographies of AA7075/TiB2 composites. The samples were prepared with 0, 3, 6, 9 and 12 wt.% of fillers and experiments were conducted by varying the cutting speed, feed, depth of cut and tool nose radius. The machining forces and surface topographies, the structure of the cutting tool and chip patterns were examined. The maximum cutting force was recorded upon increase in cutting speed because of thermal softening, loss of strength discontinuity and reduction of the built-up-edge. The increased plastic deformation with higher cutting speed resulted in the excess metal chip. In addition, the increase in cutting speed improved the surface roughness due to decrease in material movement. The cutting force was decreased upon high loading of TiB2 due to the deterioration of chips caused by fillers. Further introduction of TiB2 particles above 12 wt.% weakened the composite; however, due to the impact of the microcutting action of the fillers, the surface roughness was improved.


Author(s):  
Michaela Samardžiová ◽  
Miroslav Neslušan

Abstract Hard turning has been applied in machining since the early 1980s. There is an effort to substitute finish grinding by hard machining, because of machining by cutting tool with defined geometry. For machining of hardened steels (up to 45 HRC) are used two different cutting materials. PCBN are used the most for discontinuous machining of hardened steel (up to 63 HRC) and mixed ceramic tools, which are used in the experiment. This paper reports a development of surface roughness parameters when using wiper tool geometry of mixed ceramic tool and conventional geometry of mixed ceramic tool in hard turning. Roughness parameters (Ra, Rz, Rsk, Rku, RSm, Rdq) are measured when changing the feed, depth of cut and cutting speed are constant.


2020 ◽  
Vol 66 (7-8) ◽  
pp. 467-478 ◽  
Author(s):  
Anastasios Tzotzis ◽  
César García-Hernández ◽  
José-Luis Huertas-Talón ◽  
Panagiotis Kyratsis

Hard turning is one of the most used machining processes in industrial applications. This paper researches critical aspects that influence the machining process of AISI-4140 to develop a prediction model for the resultant machining force-induced during AISI-4140 hard turning, based on finite element (FE) modelling. A total of 27 turning simulation runs were carried out in order to investigate the relationship between three key parameters (cutting speed, feed rate, and depth of cut) and their effect on machining force components. The acquired numerical results were compared to experimental ones for verification purposes. Additionally, a mathematical model was established according to statistical methodologies such as the response surface methodology (RSM) and the analysis of variance (ANOVA). The plurality of the simulations yielded results in high conformity with the experimental values of the main machining force and its components. Specifically, the resultant cutting force agreement exceeded 90 % in many tests. Moreover, the verification of the adequacy of the statistical model led to an accuracy of 8.8 %.


Author(s):  
Durai Kumaran ◽  
S.P. Sundar Singh Sivam ◽  
Harshavardhana Natarajan ◽  
G. Balakumaran ◽  
R. Naveen

Amid the delivering of an item, any material or abundance vitality created moreover to a definitive item will be named as waste. The waste produced in light of machining could be a noteworthy ecological worry for creators. The shape and condition of waste streams created and their transportation components contrast with the strategy utilized and also shift among the technique. The effect in view of each waste stream differs as well. This examination reports a machining strategy includes the procedure of material to give a completed or a semicompleted item. This is frequently done to abuse tools, frills, machines and distinctive data sources that are appropriate to the strategy. The procedures for this work include machining of material abuse devices to give parts and items. The yield of the technique incorporates the item and thusly the waste streams. The waste streams convey with the material inside the kind of chips, energy usage, worn cutting tools and operating time. Grey relational analysis and ANOVA was acclimated with the chief essential cutting speed, feed rate, depth of cut and tool nose radius conditions that influence the minimum response. The cooperative effects of the informational factors on the normal reactions are researched. The normal and estimated esteems are genuinely close. The given model may be acclimated to pick the measure of machining process parameters.


2017 ◽  
Vol 867 ◽  
pp. 171-176 ◽  
Author(s):  
B. Ravi Sankar ◽  
P. Umamaheswarrao ◽  
Shaik Nawaz Sharief ◽  
T. Suresh ◽  
Rayudu Raju

The present work is aimed to investigate the effect of the turning parameters on the surface roughness produced during hard turning of AISI 52100 bearing steel with PCBN cutting tools. The experiments are devised using Taguchi L27 orthogonal array and analysis is carried out using MINITAB 14 software. The influence of individual parameters is discussed with main effects plot and the combined parametric effect is presented with interaction effects plot. From the results it is observed that speed and nose radius has a great influence on surface roughness. The interaction effect is significant for speed and feed combination.


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