This paper provides a comprehensive review of literature, mostly of the last 10–15 years, on modeling of machining of composite materials with a focus on the process of turning. The paper discusses modeling of both fiber reinforced and particle reinforced composites. Modeling studies include molecular dynamic simulations, 2-D and 3-D finite element models and the emerging field of multi-scale models. In fiber reinforced composites the focus is on glass and carbon fiber reinforced polymeric composites as well as long fiber reinforced metal matrix composites. On the other hand modeling of particulate composites is restricted to that of metal matrix composites (MMC). The paper includes recent modeling work to predict cutting forces, tool–particle interaction, cutting temperatures and machined sub-surface damage. A case study on the machining of the MMC A359 aluminum matrix composite reinforced with 20% by volume fraction silicon carbide particles is included to showcase the hierarchical multi-scale machining model.

Modeling of machining of composite materials: A review

Monitoring and processing signal applied in machining processes – A review

In the present study, an attempt has been made to investigate the influence of cutting speed, depth of cut, and feed rate on surface roughness during machining of 7075 Al alloy and 10 wt.% SiC particulate metal-matrix composites. The experiments were conducted on a CNC Turning Machine using tungsten carbide and polycrystalline diamond (PCD) inserts. Surface roughness of 7075Al alloy with 10 wt.% SiC composite during machining by tungsten carbide tool was found to be lower in the feed range of 0.1 to 0.3 mm/rev and depth of cut (DOC) range of 0.5 to 1.5 mm as compared to surface roughness at other process parameters considered. Above cutting speed of 220 m/min surface roughness of SiC composite during machining by PCD tool was less as compared to surface roughness at other values of cutting speed considered. Wear of tungsten carbide and PCD inserts was analyzed using a metallurgical microscope and scanning electron microscope. Flanks wear of carbide tool increased by a factor of 2.4 with the increase of cutting speed from 180 to 240 m/min at a feed of 0.1 mm/rev and a DOC of 0.5 mm. On the other hand, flanks wear of PCD insert increased by only a factor of 1.3 with the increase of cutting speed from 180 to 240 m/min at feed of 0.1 mm/rev and DOC 0.5 mm.

Effect of machining parameters on surface roughness and tool wear for 7075 Al alloy SiC composite

Study on surface roughness measurement for turning of Al 7075/10/SiCp and Al 7075 hybrid composites by using response surface methodology (RSM) and artificial neural networking (ANN)

Aluminum metal matrix composites (AMMCs) used in different industries from automotive to aerospace for specific purposes. Many problems hinder the full-scale industrialization of AMMCs but the main problems include wettability, particle distribution, porosity, and chemical reaction. These problems have explicit effects on mechanical, wear, and corrosion resistance properties of the composite materials. Therefore, it is essential to cope up with these problems for better quality of AMMCs. This paper focuses on issues related to AMMCs fabrication, corrosion resistance, wear resistance, machining parameter optimization, and chip analysis of AMMCs. Literature provides a guideline to researchers about present scenario of AMMC fabrication using stir casting process. Moreover, paper presents properties and applications of AMMCs.

Processing issues, machining, and applications of aluminum metal matrix composites

Surface roughness classification using image processing

The paper attempts to study the machinability issues of aluminium-silicon carbide (Al-SiC) metal matrix composites (MMC) in turning using different grades of poly crystalline diamond (PCD) inserts. Al-SiC composite containing 15%wt of SiC was used as work material for turning and PCD inserts of three different grades were used as cutting tools. Experiments were conducted at various cutting speeds, feeds and depth of cuts and parameters, such as surface roughness, specific power consumed, and material removal rate were measured. The worn surface of the insert was examined by scanning electron microscope (SEM). The surface finish observed was found to be much lower than the theoretical surface roughness. The influence of cut was examined for the different grades of PCD inserts. It was observed that the 1600 grade PCD inserts performed well from the surface finish and specific power consumption points of view closely followed by the 1500 grade.

An investigation on the machinability of Al-SiC metal matrix composites using pcd inserts

Monitoring of tool wear during hard turning is essential. Many investigators have analyzed the acoustic emission (AE) signals generated during machining to understand the metal cutting process and for monitoring tool wear and failure. In the current study on hard turning, the skew and kurtosis parameters of the root mean square values of AE signal (AERMS) are used to monitor tool wear. The rubbing between the tool and the workpiece increases as the tool wear crosses a threshold, thereby shifting the mass of AERMS distribution to right, leading to a negative skew. The increased rubbing also led to a high kurtosis value in the AERMS distribution curve.

/pdf/monitoring-of-hard-turning-using-acoustic-emission-signal-2l0t1xwgzw.pdf

Monitoring of hard turning using acoustic emission signal

An experimental approach for surface roughness measurement based on the speckle images caused by a laser beam on the milled surfaces and the white-light images of the same surfaces is presented. Since the surface slope at every point of the surface influences the speckle pattern, the surface roughness parameters Rda and Rdq were used for comparison. A CMOS camera, LASER and LED light sources were used for capturing speckle and white-light images of the milled surfaces. From the image pixel intensity matrix, a signal vector was generated and was used for the image metric. It is found that standard deviation and mean of the image signal vector correlate well with Ra, Rda and Rdq values measured by a standard Taylor Hobson surface roughness tester. The correlation was found to be better for speckle images than the white-light images.

Surface Roughness Evaluation of Milled Surfaces by Image Processing of Speckle and White-Light Images

This paper deals with the important issues of chip breaking. During metal cutting, the excess material is removed in the form of chips. These chips are obtained in various shapes and sizes, and are influenced by cutting conditions, work material, tool material, tool geometry and chip breaker geometry. This experimental work deals with the influence of two design parameters, width of chip breaker and angle of chip breaker of a clamped on chip breaker on effective chip breaking. All turning experiments were carried out on low carbon steel work material at a constant cutting speed of 100 m/min. Length of cut chip (LC) is used as a parameter to assess the effectiveness of chip breaking. The optimal distance of the chip breaker from the cutting edge and the chip breaker angle producing acceptable chip forms for finish, medium and rough turning conditions were identified.

Influence of chip breaker location and angle on chip form in turning low carbon steel

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