Performance of End Milling Process on Advanced Ceramics

Experimental study has been carried out to investigate the performance of conventional CNC end milling machining technology with particular reference to Machinable Glass Ceramic and Aluminum Nitride Ceramic using three different cutting tools. The surface finish, tool life and cutting force have been chosen as measurements for machinability. Predictive mathematical models are developed and finally optimal machining parameters are determined in order to achieve good surface finish, high material removal rate and low cutting forces

Finite element analysis and modeling of temperature distribution in turning of titanium alloys

The titanium alloys (Ti-6Al-4V) have been widely used in aerospace, and medical applications and the demand is ever-growing due to its outstanding properties. In this paper, the finite element modeling on machinability of Ti-6Al-4V using cubic boron nitride and polycrystalline diamond tool in dry turning environment was investigated. This research was carried out to generate mathematical models at 95% confidence level for cutting force and temperature distribution regarding cutting speed, feed rate and depth of cut. The Box-Behnken design of experiment was used as Response Surface Model to generate combinations of cutting variables for modeling. Then, finite element simulation was performed using AdvantEdge®. The influence of each cutting parameters on the cutting responses was investigated using Analysis of Variance. The analysis shows that depth of cut is the most influential parameter on resultant cutting force whereas feed rate is the most influential parameter on cutting temperature. Also, the effect of the cutting-edge radius was investigated for both tools. This research would help to maximize the tool life and to improve surface finish

Investigating the Correlation between Electrolyte Concentration and Electrochemical Properties of Ionogels

Ionogels are hybrid materials comprising an ionic liquid confined within a polymer matrix. They have garnered significant interest due to their unique properties, such as high ionic conductivity, mechanical stability, and wide electrochemical stability. These properties make ionogels suitable for various applications, including energy storage devices, sensors, and solar cells. However, optimizing the electrochemical performance of ionogels remains a challenge, as the relationship between specific capacitance, ionic conductivity, and electrolyte solution concentration is yet to be fully understood. In this study, we investigate the impact of electrolyte solution concentration on the electrochemical properties of ionogels to identify the correlation for enhanced performance. Our findings demonstrate a clear relationship between the specific capacitance and ionic conductivity of ionogels, which depends on the availability of mobile ions. The reduced number of ions at low electrolyte solution concentrations leads to decreased ionic conductivity and specific capacitance due to the scarcity of a double layer, constraining charge storage capacity. However, at a 31 vol% electrolyte solution concentration, an ample quantity of ions becomes accessible, resulting in increased ionic conductivity and specific capacitance, reaching maximum values of 58 ± 1.48 μS/cm and 45.74 F/g, respectively. Furthermore, the synthesized ionogel demonstrates a wide electrochemical stability of 3.5 V, enabling diverse practical applications. This study provides valuable insights into determining the optimal electrolyte solution concentration for enhancing ionogel electrochemical performance for energy applications. It highlights the impact of ion pairs and aggregates on ion mobility within ionogels, subsequently affecting their resultant electrochemical properties

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization By Response Surface Methodology

This paper presents the prediction of a statistically analyzed model for the surfaceroughness of end-milled Machinable glass ceramic (MGC). Response Surface Methodology(RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is foundthat cutting speed is the most significant factor contributing to the surface roughness value followedby the depth of cut and feed rate. The surface roughness value decreases for higher cutting speedalong with lower feed and depth of cut. Additionally, the process optimization has also been donein terms of material removal rate (MRR) to the model’s response. Ideal combinations of machiningparameters are then suggested for common goal to achieve lower surface roughness value andhigher MRR

Performance study of solder bond on thermal mismatch stresses in electronic packaging assembly

Thermo-mechanical stresses have been considered as one of the major concern in electronic Packaging assembly structural failure. The interfacial stresses are often caused by the thermal mismatch stresses induced by the coefficient of thermal expansion (CTE) difference between materials, typically during the high temperature change in the bonding process. This research work examined the effect of bond layer on thermal mismatch inter-facial stresses in a bi-layered assembly. The paper verified the existing thermal mismatch solder bonded bi-layered analytical model using finite element method (FEM) simulation. The parametric studies on the effect of change of the bond layer properties were carried out in order to provide useful reference for interfacial stress evaluation and the electronic packaging assembly design. These parameters included CTE, temperature, thickness, and stiffness (compliant and stiff bond) of the bond layer. The recent development on the lead free bonding material was being reviewed and found to have enormous potential and key role to address the future electronic packaging assembly reliability

Development of Cutting Force Model of Aluminum Nitride ceramic processed by Micro End Milling

Advanced ceramics are difficult to do machining due to brittle nature. High cuttingforces will generate in the machining, which will affect the surface integrity of final product.Selection of proper machining parameters is important to obtain less cutting force. The presentwork deals with the study and development of a cutting force prediction model in end millingoperation of Aluminum Nitride ceramic. The cutting force equation developed using ResponseSurface Methodology (RSM) to analyze the effect of Spindle speed, feed rate and axial depth of cut.The cutting tests were carried under dry condition using two flute square end micro grain carbideend mills

Surface Roughness Model when Machining Aluminum Nitride Ceramicwith Two Flute Square end Micro Grain Solid Carbide end Mill

This research presents the performance of Aluminum Nitride ceramic in end milling using two flute square end micro grain solid carbide end mill under dry cutting. Surface finish is one of the important requirements in the machining process. This paper describes mathematically the effect of cutting parameters on surface roughness in end milling process. The quadratic model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using the response surface methodology (RSM). Design of experiments approach was employed in developing the surface roughness model in relation to cutting parameters. The predicted results are in good agreement with the experimental results within the specified range of cutting conditions. Experimental results showed surface roughness increases with increase in the cutting speed, feed rate, and the axial depth of cut

Machinability of aluminum nitride ceramic using TiAlN and TiN coated carbide tool insert

This research presents the performance of Aluminum nitride ceramic in end milling using titanium coated carbide insert under dry machining. The surface roughness of the work piece and tool wear was analyzed in this. The design of experiments (DOE) approach using Response surface methodology was implemented to optimize the cutting parameters of a computer numerical control (CNC) end milling machine. The analysis of variance (ANOVA) was adapted to identify the most influential factors on the CNC end milling process. The mathematical predictive model developed for surface roughness and tool wear in terms of cutting speed, feed rate, and depth of cut. The cutting speed is found to be the most significant factor affecting the surface roughness of work piece and tool wear in end milling process

Aluminum-silicon carbide composites for enhanced physio- mechanical properties

Stir casting method is used in the production of SiC reinforced-aluminium metal matrix composite (AMMC) to enhance the properties of base metal. Different weight fraction of Silicon carbide, SiC (5 wt%, 10 wt% and 15 wt %) particulate-reinforced AMMCs are fabricated and characterizations of physical and mechanical properties of the materials are performed based on the experimental. The microstructure of the fabricated composite material are studied and analyzed. The results indicate that the mechanical properties of the composite, including yield strength, tensile strength and hardness are enhanced by the increment of the weight fraction of reinforcing phase. Nevertheless, the elongation and fracture toughness of the composite decreased as the reinforcing phase increased. This is mainly due to the brittleness of the SiC particles which act as micro void initiator