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Today's metal matrix composites are widely used due to their excellent properties, which are useful for high-performance applications in the automotive and aerospace industries. Furthermore, improving the machinability of these composites is vital for improving product quality in the manufacturing process. In this research, various adaptive network-based fuzzy inference systems (ANFISs) were introduced to evaluate the effect of the feed rate, the cutting speed and the particle size on the machinability of Al–20 Mg2Si metal matrix composite. Two ANFIS models were selected as the most precise models for predicting surface roughness and cutting force. Results show that the proposed ANFIS models have an adequate accuracy in predicting the machinability of metal matrix composites. [ABSTRACT FROM AUTHOR]

Aluminum alloys are widely used in several applications. Cast alloys are usually considered to be brittle materials leading to short chip formation during machining. Although they can be produced near net shapes, products made of these alloys very often require some machining. The purpose of this study is to evaluate the machinability ofA319andA356underT0andT6conditions. The machinability was assessed during the dry drilling machining process, with the machinability indexes including the chip form, chip breakability, and the cutting forces. It was found thatA319andA356exhibit different machinability behaviors, especially under the T6-condition in terms of force requirements, chip breakability, and chip segmentation. The chip grain size obtained by X-ray diffraction techniques was also studied and correlated to the machining conditions. It was also found that both the microstructure of the workpiece materials and the machining conditions significantly affect the chip formation mechanism, and so the machining parameters could therefore be selected to promote a chip form that is easily manageable in production. [ABSTRACT FROM PUBLISHER]

This article presents the influence of machining conditions on typical process performance indicators, namely cutting force, specific cutting energy, cutting temperature, tool wear, and fine dust emission during dry milling of CFRPs. The main goal is to determine the machining process window for obtaining quality parts with acceptable tool performance and limited dust emission. For achieving this, the cutting temperature was examined using analytical and empirical models, and systematic cutting experiments were conducted to assess the reliability of the theoretical predictions. A full factorial design was used for the experimental design. The experiments were conducted on a CNC milling machine with cutting speeds of 10,000, 15,000, and 20,000 rpm and feed rates of 2, 4, and 6 µm/tooth. Based on the results, it was ascertained that spindle speed significantly affects the cutting temperature and fine particle emission while cutting force, specific cutting energy, and tool wear are influenced by the feed rate. The optimal conditions for cutting force and tool wear were observed at a cutting speed of 10,000 rpm. The cutting temperature did not exceed the glass transition temperature for the cutting speeds tested and feed rates used. The fine particles emitted ranged from 0.5 to 10 µm aerodynamic diameters with a maximum concentration of 2776.6 particles for those of 0.5 µm diameters. Finally, results of the experimental optimization are presented, and the model is validated. The results obtained may be used to better understand specific phenomena associated with the milling of CFRPs and provide the means to select effective milling parameters to improve the technology and economics of the process. [ABSTRACT FROM AUTHOR]

The machinability of composite materials depends on reinforcements, matrix properties, cutting parameters, and on the cutting tool used (material, coating, and geometry). For new composites, experimental studies must be performed in order to understand their machinability, and thereby help manufacturers establishing appropriate cutting data. In this study, investigations are conducted to analyze the effects of cutting parameters and drill bit diameter on the thrust force, surface roughness, specific cutting energy, and dust emission during dry drilling of a new hybrid biocomposite consisting of polypropylene reinforced with miscanthus fibers and biochar. A full factorial design was used for the experimental design. It was found that the feed rate, the spindle speed, and the drill bit diameter have significant effects on the thrust force, the surface roughness, and the specific cutting energy. The effects of the machining parameters and the drill bit diameter on ultrafine particles emitted were not statistically significant, while the feed rate and drill bit diameter had significant effects on fine particle emission. [ABSTRACT FROM AUTHOR]