Elsevier

Measurement

Volume 76, December 2015, Pages 170-182
Measurement

Evaluation of cutting force and surface roughness in the dry turning of Al–Mg2Si in-situ metal matrix composite inoculated with bismuth using DOE approach

https://doi.org/10.1016/j.measurement.2015.08.032Get rights and content

Highlights

  • Machinability of Al–Mg2Si composite was investigated systematically.

  • Analysis of variance is employed to determine the significance of cutting parameter.

  • Bi is a promising element to improve the machinability of Al–Mg2Si composite.

  • High cutting speed and low feed rate are advised to obtain appreciable Ra.

  • Mathematical models derived to predict Fc and Ra at a reliability of 95.

Abstract

Al–Mg2Si particulate metal matrix composites (PMMC) has recently received wider attention because of its improved properties, however there is a lack of knowledge about machinability characteristics of these composites especially with bismuth addition. The purpose of this study is to evaluate the machining parameters and modifier element effects on cutting force (Fc) and surface roughness (Ra) when dry turning Al–Mg2Si with a coated carbide tool (K10U). The experimental trials are designed using the multi-level factorial design (DOE) and their results are analyzed using Analysis of Variance (ANOVA). Statistical models are developed to represent the relationship among machining parameters as independent variables, surface roughness and cutting force as response variables. For each experiment, a new cutting insert is used to encourage accurate reporting of the cutting force and surface roughness. The statistical observation revealed that the main effect of cutting speed, feed rate and modifier element influenced the cutting force and surface roughness. Moreover, there are no interaction effects of variables. Built-up-edge (BUE) formation was observed at every combinations of cutting speed and feed rate which affected the surface quality negatively. The proximity of predicted results and experimental results provide evidence that the DOE method has successfully derived the predictive models. The addition of Bi as modifier reagent results in lower cutting force and better surface roughness due to the formation of Bi compound and modifies the morphology of Mg2Si reinforcement particle. Our findings showed that the Bi is a promising element to improve the machinability of Al–Mg2Si composite.

Introduction

Metal-matrix composites (MMCs) are developed to satisfy the demand for materials with high strength and toughness and capable to be used effectively in adverse conditions. MMCs have attracted the attention of automotive and aerospace industries which are looking for materials with low density and, appropriate mechanical properties such as high strength and stiffness in order to reduce weight and fuel consumption [1]. Particulate metal-matrix composites (PMMC) offer some advantages, such as better manufacturability, when compared to fiber metal-matrix composites. Even though components made from PMMCs are produced to near net shape, some secondary operations are needed to achieve the required dimensions and surface finish [2]. The main problem associated with the machining of MMCs is the high rate of tool wear because of the ceramic reinforcing particles which act as an abrasive and result in tool wear and short tool life thereby increasing the overall cost of production. The alteration of tool geometry caused some defect on the machined surface and these defects and their distribution play an important role in determining some mechanical properties such as creep and fatigue that consequently affect the performance of the machined components during service [3], [4].

Although it has been reported that cutting speed and volume fraction of reinforcing particles affect the surface quality, feed rate is the most influential factor [5]. The previous investigations based on Taguchi method explore that tool geometry (flank wear) and cutting force are affected by the cutting speed and most significant factor which influence the surface roughness is feed rate [6], [7], [8]. The findings supported that Taguchi method and Analysis of Variance (ANOVA) are powerful techniques to develop predictive models [9]. Most of the ex-situ/in-situ MMCs such as Al–SiC suffer from thermodynamic instability of interfaces among the ceramic reinforcement/matrix and poor wettability of the reinforcement [10]. Therefore, in recent years, in-situ composite such as Al–Mg2Si in which reinforcements are synthesized internally in the matrix during the composite solidification has attracted many researchers. Moreover, in situ fabrication provides more homogeneous distribution of the dispersed phase particles. Mg2Si compounds are prone to the formation of undesirable coarse Chinese script and brittle dendritic morphologies, which would deteriorate the mechanical properties of the materials. Thus, several researches have been done to modify the deleterious morphology of Mg2Si particles with addition of strontium (Sr) [11], [12], [13], phosphorous (P) [14], yttrium (Y) [15], antimony (Sb) [13], [16], manganese (Mn) [17], lithium (Li) [18], mischmetal [19], and cerium (Ce) [20]. Moreover, bismuth (Bi) is used as an alloying element in wrought aluminium alloys to promote chip breaking and helping tool lubrication [21]. Bi is also added to Al–Mg alloys to prevent embrittlement by sodium [22], and to disrupt the formation of oxide defects in Al alloys [23]. It has also been shown that the presence of Bi has a refinement effect on the morphology of eutectic silicon and Mg2Si reinforcement particles [24], [25], [26], [27], [28]. Additionally, Bi-containing work-piece showed the lowest cutting force and better surface roughness in Al–11Si–2Cu cast alloy in comparison to Sb and Sr containing work-pieces [29]. Moreover, it has been found that cutting force decreased and chip fragility increased by adding Bi to the 220 Al–2%Cu–1.3%Si–0.4%Mg alloy [30]. In terms of Al–Mg2Si in-situ composite, most previous studies focused on its microstructure and mechanical properties. There is a lack of knowledge about machinability characteristics of Al–Mg2Si composite especially with addition of Bi. Furthermore, the design of experiment (DOE) methodology was used to achieve this objective. The analysis of the effects of each variable and their reciprocal interaction on the machinability characteristic provided the necessary information needed for the machining of Al–Mg2Si composite casting.

Section snippets

Work-piece fabrication

A commercially available Al–11Si–2Cu alloy, pure aluminium and pure magnesium were used as starting materials for adjusting the chemical composition. The materials were melted in an induction furnace to fabricate the composite ingot with chemical composition given in Table 1. A 1 kg ingot was then re-melted with a melt temperature of 750 ± 5 °C. The molten metal was degassed using hexachloroethance tablets. After degassing, the desired amount of pure bismuth (99.99 wt.%) in the form of metallic

Microstructure analysis

Fig. 1 shows the elemental mapping of fabricated composite without Bi addition indicating that the particles are composed of Mg and Si elements, which are distributed in aluminium matrix. Moreover, based on the EDS profile shown in Fig. 1 the atomic ratio of Mg is almost twice that of the Si element in order to form the molecular structure of Mg2Si particle. Optical and SEM micrographs of Al–20Mg2Si work-piece is shown in Fig. 2(a) and (b) and the coarse polyhedral Mg2Si particles in the

Conclusion

The multilevel factorial design was used to examine the effect of cutting speed (70–210 m/min), feed rate (0.1–0.2 mm/rev) and Bi addition on cutting force and surface roughness of Al–20%Mg2Si in-situ composite. The obtained results were analyzed using Analysis of Variance. The following conclusion can be drawn:

  • 1.

    The recommended optimum cutting conditions in machining of Al–20%Mg2Si composite is found to be: cutting speed at 210 m/min and feed rate at 0.1 mm/rev in the presence of Bi.

  • 2.

    According to the

Acknowledgments

Financial support from the Ministry of Higher Education Malaysia (MOHE) and Universiti Teknologi Malaysia (UTM) through the Fundamental Research Grant Scheme and Research University Grant Scheme are gratefully acknowledged.

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