Development of Al-SiC composite material from rice husk and its parametric assessment

In this research work, the development of Al-SiC composite material from rice husk and its parametric assessment is done using a CNC milling machine. They are further surface characterized, and mechanical properties such as BET surface area, SEM-EDX, and XRD, fracture toughness, tensile, and bending strength are studied. The machinability of the components is investigated for selected values of input-output parameters. Three castings, each with different particulate reinforcement combinations, are made with aluminum alloy (6061) using the stir casting method. BET surface area of extracted silica and Al-SiC composite material was found 374 m2/g and 150 m2/g, respectively. From results of BET surface area revealed that silica obtained from rice husk is more heterogeneous with a large surface area. A heterogeneous surface with larger pores was found through SEM images. XRD diffraction peaks show changes of amorphous silica into crystallinity in the composite material. The results also indicate that fracture toughness is very good at low temperatures and good machinability on CNC milling machines makes it suitable for aerospace applications.

CNC Milling of Medical-Grade PMMA

This study evaluates CNC milling parameters (spindle speed, depth of cut, and feed rate) on medical-grade PMMA. A single objective analysis conducted showed that the optimal material removal rate (MRR) occurs at a spindle speed of 1250 rpm, a depth of cut of 1.2 mm, and a feed rate of 350 mm/min. The ANOVA showed that feed rate is the most significant factor towards the MRR, and spindle speed (11.83%) is the least contributing. The optimal surface roughness (Ra) occurred at spindle speed of 500 rpm, depth of cut of 1.2 mm, and feed rate of 200 mm/min. The milling factors were insignificant. A regression analysis for prediction was also conducted. Further, a multi-objective optimization was conducted using the Grey Relational Analysis. It showed that the best trade-off between the MRR and the Ra could be obtained from a combination of 1250 rpm (spindle speed), 1.2 mm (depth of cut), and 350 mm/min (feed rate). The depth of cut was the largest contributor towards the grey relational grade (54.48%), followed by the feed rate (10.36%), and finally, the spindle speed (4.28%).

THERMAL SIMULATION OF CNC MILLING MACHINE DRIVES

The publication deals with the design of thermal simulation of CNC milling machine drives. The first part of the publication defines the individual parts of the thermal model concept and their mutual influence. Subsequently, simulations of drives were created. The first thermal model is defined for a stepper motor which is a drive for the linear axes of a CNC milling machine. Subsequently, the design of the thermal drive of the spindle is analysed, which uses a DC motor with permanent magnets. Using previous models of the drive, a model of the entire CNC milling machine was designed. In the last part, the model was compared with real measurements, which evaluated the tolerances of the system.

A Novel CNC Milling Energy Consumption Prediction Method Based on Program Parsing and Parallel Neural Network

Accurate and rapid prediction of the energy consumption of CNC machining is an effective means to realize the lean management of CNC machine tools energy consumption as well as to achieve the sustainable development of the manufacturing industry. Aiming at the drawbacks of existing CNC milling energy consumption prediction methods in terms of efficiency and precision, a novel milling energy consumption prediction method based on program parsing and parallel neural network is proposed. Firstly, the relationship between CNC program and energy consumption of CNC machine tool is analyzed. Based on the structural characteristics of the CNC program, an automatic parsing algorithm for the CNC program is proposed. Moreover, based on the improved parallel neural network, the mapping relationship between the energy consumption parameters of each CNC instruction and the milling energy consumption is constructed. Finally, the proposed method is compared with the literature to verify the superiority of the proposed method in terms of prediction efficiency and accuracy, and the practicability of the method is verified through the case study. The proposed method lays the foundation for efficient and low-consumption process planning and energy efficiency improvement of machine tools and is conducive to the sustainable development of the environment.

EXPERIMENTAL RESEARCH OF PARTIAL REGULAR MICRORELIEFS FORMED ON ROTARY BODY FACE SURFACES

The basic regularities in the influence of processing parameters on the geometrical characteristics of the partially regular microreliefs, formed on the rotary body face surface, are established. Combinations of partially regular microreliefs are formed by using a contemporary CNC milling machine, and an advanced programing method, based on previously developed mathematical models. Full factorial experimental design is carried out, which consist of three factors, varied on three levels. Regression stochastic models in coded and natural form, which give the relations between the width of the grooves and the deforming force, feed rate and the pitch of the axial grooves, are derived as a result. Response surfaces and contour plots are built in order to facilitate the results analysis. Based on the dependencies of the derived regression stochastic models, it is found that the greatest impact on the width of the grooves has the magnitude of the deforming force,followed by the feed rate. Also, it is found that the axial pitch between adjacent toolpaths has the least impact on the width of the grooves. As a result of the full-factorial experiment, the average geometric parameters of the microrelief grooves were obtained on their basis. When used, these values will provide for the required value of the relative burnishing area of the surface with regular microreliefs, and, accordingly, the specified operational properties.

Optimization of an autonomous robotic drilling system for the machining of aluminum aerospace alloys

This paper aims to identify the capability of a highly flexible industrial robot modified with a high-speed machine spindle for drilling of aluminum 6061-T6. With a focus on drilling feed rate, spindle speed, and pecking cycle, the hole surface roughness and exit burr heights were investigated using the Taguchi design methodology. A state of the art condition monitoring system was used to identify the vibrations experienced during drilling operation and to establish which robot pose had increased stiffness, and thus the optimum workspace for drilling. When benchmarked against a CNC machine the results show that the CNC was capable of producing the best surface finish and the lowest burr heights. However, the robot system matched and outperformed the CNC in several experiments and there is much scope for further optimization of the process. By identifying the optimum pose for drilling together with the idealized settings, the proposed drilling system is shown to be far more flexible than a CNC milling machine and when considering the optimized drilling of aerospace aluminum this robotic solution has the potential to drastically improve productivity.

Effect of feed rate and depth of cut on face milling process on surface roughness of Al-Mg alloy using CNC milling machine 3 axis

The purpose of this study was to determine the effect of feed rate and depth of cut on the surface roughness of Al-Mg aluminum using a DIY CNC Milling Machine and Krisbow Universal Milling Machine as a comparison. The open-loop control system is a control system used in the design of DIY CNC Milling machines. A PC with Mach3 software is used as a PC Based Direct Digital Controller to control the system. In this study, the feed rate variation 24 mm/minute and 42 mm/minute and depth of cut 0.25 mm, 0.5 mm, and 0.75 mm were used. After the face milling process, the surface roughness test was carried out using the Mitoyo Surface Roughness Tester to determine the level of surface roughness of the machining results the DIY Milling Machine and Krisbow Universal Milling Machine as a comparison. The results showed that as the feed rate and depth of cut increased, the surface roughness values of both tools increased.