Effect of Carburizing Flame and Oxidizing Flame on ... - CyberLeninka

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ScienceDirect Procedia Materials Science 6 (2014) 840 – 850

3rd International Conference on Materials Processing and Characterisation (ICMPC 2014)

Effect of Carburizing Flame and Oxidizing Flame on Surface Roughness in Turning of Aluminium Metal Matrix Composite and Differential Evolution Optimization of Process Parameters N.V.V.S.Sudheera, K.Kateeka Pavanb a,b

R.V.R&J.C.College of Engineering, Guntur-522 019, India

Abstract This paper presents an experimental probe into the effects of carburizing and oxidizing flame ofn the surface finish in turning of Aluminium metal matrix composite. The experimental design is performed by using 3 3 full factorial design. From the measured values the mathematical models are developed. These models are subjected to Differential Evolution (DE) optimization technique for finding global values of speed, feed, and depth of cut for minimizing surface roughness and maximizing material removal rate. Observation of results proved that carburizing flame cutting operation yields better surface finish compared to dry and oxidizing flame cutting. © Ltd. This is an openbyaccess article under the CC BY-NC-ND license © 2014 2014Elsevier The Authors. Published Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the Gokaraju Rangaraju Institute of Engineering and Technology (GRIET). Selection and peer review under responsibility of the Gokaraju Rangaraju Institute of Engineering and Technology (GRIET) Keywords: Carburizing flame; Oxidizing flame; Al-MMC; BUE, Differential Evolution (DE).

1. Introduction In the recent past Aluminium Metal Matrix Composites (Al-MMC) became the most preferred elements by the manufacturers because of their improved mechanical strength, thermal properties and lower specific weight. Taya, and Arsenault (1989) observed that Al – MMC pose many problems to the industry in machining since the particles present in MMC are harder than the HSS tools and carbide tools. Manna and Battacharya (2001) observed that the hard silicon particles, which intermittently come into contact with the cutting tool edge, which in due course becomes worn out by abrasion, resulting in the formation of very poor surface finish. Manna and Battacharya (2002) stated that when soft Al- MMC job slides over a hard cutting tool edge during turning, because of high temperature, friction and pressure the built-up edge (BUE) is formed which produces a very poor surface finish. * Corresponding author. Tel.: +91-9493239828; E-mail address:[email protected]

2211-8128 © 2014 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer review under responsibility of the Gokaraju Rangaraju Institute of Engineering and Technology (GRIET) doi:10.1016/j.mspro.2014.07.101

N.V.V.S. Sudheer and K. Kateeka Pavan / Procedia Materials Science 6 (2014) 840 – 850

Hence generation of good surface finishes for Al-MMC jobs during turning is a challenge to manufacturing Industry. Diniz and Micaroni (2002) observed that the cutting fluids perform as coolant and lubricant, the coolant effect reduces temperature in cutting zone and lubricant action decreases cutting forces. Thus friction coefficient between tool and chip becomes lower in comparison to dry machining. Unfortunately, conventional cutting fluids cause environmental and health problems. The current attention to the environmental regulations has been forcing manufacturers to reduce or eliminate the amount of pollutants. Therefore in theory, it seems to be better options to eliminate cutting fluid usage. The machinability of Al-MMC can be improved by different treatments. Tash et al. (2006) observed that the heat treatments, which increase hardness, will reduce the built-up edge (BUE) tendency during machining. Roy et al.. (2009) stated that, in the case of dry machining, the major problems encountered are the BUE at low cutting speeds and sticking at high cutting speeds, hence the need for special methods. Thermally enhanced machining uses external heat sources to heat the workpiece, change microstructure or remove the workpiece locally in front of the cutting tool to facilitate the machining process due to softening, change in deformation behavior and thinning of the workpiece. Sun et al. (2010) observed that he heat energy reduces the yield strength and hardness and makes brittle material have ductile materials. Attia et al. (2010) compared Laser assisted machining with conventional machining, he observed that surface finish of Laser assisted turning is improved by more than 25% and the material removal rate is increase by approximately 800%. Riaz Muhammad et al. (2012) used a new hybrid machining technique–hot ultrasonically assisted turning was used for the machining of β – Ti alloy to investigate the benefits of the machining process. This technique offers better results in terms of cutting forces and surface roughness when compared to conventional turning. Yongho Jeon et al. (2013)] stated that the external energy assistance enables the machining of hard to cut materials and improve the quality of machining. However, they are still at the beginning stage of research and require the extensive studies for the basic understandings in the mechanisms and optimal processes and the systems In this study, the effect of Carburising Flame (combined progressive spin-hardening) and Oxidizing Flame on surface roughness in turning of Al-MMC has been investigated and the results were compared with dry machining. The experiments were conducted by varying cutting speed, feed and depth of cut in three levels each and test results were analyzed. In three conditions the mathematical models (power type) were developed by using multiple regression. These mathematical models are subjected to Differential Evolution (DE) technique for finding the optimal values of speed, feed and depth of cut for minimizing surface roughness and maximizing material removal rate (MRR). Storn and Price. (1995) introduced the Differential Evolution (DE), which is one of the most powerful stochastic real-parameter optimization algorithms in current use. Storn and Price (1997) reported that the DE follows similar computational steps as in a standard evolutionary algorithm. DE uses a weighted difference of the solution vectors to explore the objective function in population. Swagatam Das et al. (2009) stated that the DE is very simple to code compared to other Evolutionary Algorithms. The recent studies done by Swagatam Das and Nagaratnam Suganthan (2011) on DE and they have shown that DE provides a better performance in terms of accuracy, robustness and convergence speed with its simplicity. Swagatam Das and Ajith Abraham (2008), Swagatam Das and Amith Konar (2009) stated that the number of control parameters in DE is very few compared to other algorithms hence DE is became a successful technique for many applications. Gong and Cai (2009), Qu and Suganthan (2010) stated that the DE algorithm is also used as a competitive solution for various multi objective problems. 2. Work Piece Material The Al- MMC of 75mm diameter is used for experimentation. The chemical composition of the material is shown in the Table 1. Table 2 shows the mechanical properties of the work material. Table 3 shows the details of cutting tool and tooling system used for experimentation.

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842

N.V.V.S. Sudheer and K. Kateeka Pavan / Procedia Materials Science 6 (2014) 840 – 850 Table 1: Chemical composition of the material Type of MMC

Size of reinforced Particles

%Si

%Mg

%Cu

%Fe

%Ti

Discontinuous MMC

25μm

0.40.8

0.8-1.2

0.150.4

0.7

0.15

%Cr .040.35

%Zn

%Mn

%SiC

%Al

0.25

0.15

15

remaining

Table 2: Physical and Mechanical properties of Al –MMC Material

Hardness, BHN

Density gm/cm3

Al6061/SiC

95

2.7

Table 3: Details of cutting tool and tooling system used for experimentation Tool holder ISO code

PSDNN 2525 M12

Tool geometry specification

Back rake angle -6°, Side rake angle -6°, Relief angle -6°

Tool insert ISO code

SNMG120408-TN2000

3. Experimentation Al/SiC-MMC of 75mm diameter is used for experimentation. The cutting experiments have been carried out on TMX-2030 engine lathe which has a maximum spindle speed of 1200 rpm and considering cutting speed (v), feed (f) and depth of cut (d) as parameters. These parameters are changed in three levels each as shown in Table 4 and twenty seven experiments were conducted separately in the dry condition , the Carburizing flame heating and oxidizing flame heating in two replicates and a total of 162 (3x3x3x2x3) experiments were conducted. Machining at each experimental condition has been carried out for a cutting length of 10-15mm. The Al-MMC bar stocks of 300mm length and 75mm diameter have been used, and on each bar stock 10 to 12 tests have been performed. The machined surface was measured by using surftest - 211 (Mitutuyo make) at three different positions on circumference at an angle of 1200 and average value was taken for analysis shown in Fig.1. Table 4: Levels for process parameters Levels

v(m/min)

f(mm/rev)

d(mm)

-1

34

0.113

0.25

0

64

0.178

0.5

+1

94

0.249

0.75

Fig. 1. Work piece and Surf test – 211

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3.1. Accomplishment of Carburizing Flame Heating and Oxidizing Flame Heating While turning process is going on, the Carburizing flame(acetylene rich flame) is supplied to the work-piece by maintaining a gap of 4cm between work-piece and torch tip and a gap of 5cm arc length between flame and workpiece interface. After the flame heating the work-piece is drenched by cooling water before it is cut. This arrangement was shown in Fig.2.The same procedure is adopted for oxidizing flame (oxygen rich flame) heating process.

Fig. 2. Flame Heating

4. Mathematical Model for Surface Roughness and DE Procedure The power model used to find the effect of process parameters on surface roughness. The general form of power model for three parameters was used in this experimentation is

Surface Roughness

k.v a f b d c

(1)

Where v = velocity in m/minute f = feed mm/rev. d= depth of cut in mm In this work power model was developed for dry condition, the Carburizing flame heating and oxidizing flame heating individually. 4.1. DE Procedure [Swagatam Das, P and Nagaratnam Suganthan, 2011] Initialization - Creation of a population of individuals. The i th individual vector (chromosome) of the population at current generation t with d dimensions is as follows,

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[

]

Zi (t ) = Zi,1 (t ), Zi, 2 (t ), ..., Zi,d (t )

(2)

Mutation - A random change of the vector components. It can be a single-point mutation, inversion, translocation, deletion, etc. For each individual vector Zk(t) that belongs to the current population, a new individual, called the mutant individual is derived through the combination of randomly selected and pre-specified individuals.

U k ,n t Z m,n t F Z i,n t Z j ,n t

(3)

the indices m, n, i, j are uniformly random integers mutually different and distinct from the current index k, and F > 0 is a real positive parameter, called mutation or scaling factor (usually€[0, 1]). Recombination (Crossover) - merging the genetic information of two or more parent individuals for producing one or more descendants. DE has two crossover schemes: the exponential and the binomial or uniform crossover. We have used the binomial crossover in this paper. The binomial or uniform crossover is performed on each component n (n= 1, 2, . . . , d) of the mutant individual Uk,n(t). For each component a random number r in the interval [0, 1] is drawn and compared with the crossover rate or recombination factor (another DE control parameter), CR € [0, 1]. If r