Abstract
In this paper, the influence of machining parameters, Cutting Speed, Feed Rate, and Depth of cut, on surface finish during dry orthogonal turning of Al 6061 – T6 alloy, is studied using the response surface methodology (RSM). This paper proposes a unique way to predict the surface finish in turning, using the effective plastic strain (PEEQ) values obtained from the simulations. A comprehensive finite element model was proposed to predict the surface finish accurately, by correlating the variance of the PEEQ. The Johnson-Cook damage model is used to define the damage criteria and Johnson-Cook material model is used to explain the material constitutive behavior. A dynamic, explicit method is used along with the Adaptive Lagrangian-Eulerian (ALE) method to predict material flow accurately. The influence of machining parameters was studied by assuming Central Composite Design (CCD). The output response, PEEQ, was fitted into analytical quadratic polynomial models using regression analysis, which shows that feed rate was the most dominant factor for PEEQ than the other parameters considered in this study. Using the individual desirability function method, the objective, optimal setting of the machining parameters was obtained for better surface finish.
Highlights
Aluminum compounds are among the most critical metals in industries
The most commonly used response surface designed experiment, Central Composite Design (CCD) method was used in this study
The quadratic model derived for PEEQ from response surface methodology (RSM), is shown in Eq (3)
Summary
Aluminum compounds are among the most critical metals in industries. The Al 6061-T6 aluminum composite is an exceptionally significant alloy because of its prevailing mechanical properties, for example, weldability, hardness, and manageability at high temperatures. Al 6061 alloy is generally utilized for commercial applications in the aviation, car parts development, and designing industries. Hasçalık and Çaydaş [3] studied effect and optimization of machining parameters on surface roughness and tool life in a turning operation was investigated by using the Taguchi method. Lodhi and Shukla [4] optimized the surface roughness and MRR during machining of AISI 1018 alloy with Titanium coated Carbide inserts using Taguchi method. Suresh et al [6] developed a model to predict the surface roughness using RSM while machining mild steel by TiC-coated tungsten carbide (CNMG) cutting tools. Nalbant et al [7] applied Taguchi method for optimizing the machining parameters for surface roughness while turning. The surface finish of the machined surfaces was taken using the handy surf - surface roughness tester
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