Experimentation and Prediction of Temperature Rise in Turning Process using Response Surface Methodology

Reducing the temperature rise during turning operation improves the quality of the product and reduces tool wear. Experiments are conducted as per the Design of Experiments (DoE) of Response Surface Methodology (RSM) to predict the temperature rise by varying the cutting parameters such as cutting speed, feed rate and depth of cut. In the present study, the experiment was conducted on Aluminium Al 6061 by coated carbide tool. A second order mathematical model in terms of machining parameters was developed for temperature rise prediction using RSM. This model gives the factor effects of the individual process parameters. Values of Prob> F less than 0.05 indicate model terms are significant. The cutting speed is the most important parameter that cause the temperature of the turning process compared to the other factors such as feed rate and depth of cut. Validation results show good agreement between the actual process output and the predicted temperature rise

Multi-objective optimization of machining factors on surface roughness, material removal rate and cutting force on end-milling using MWCNTs nano-lubricant

The art of nano-additive manufacturing in developing advanced mechanical components via machining cannot be over-emphasized when developing mechanical parts for aerospace, automobile, and structural application through the end-milling of aluminum alloys. However, the end-milling process generates heat and friction due to the machining parameter that initiated the contact between the cutting tool and the workpiece. This excess heat leads to high surface roughness (SR), low material removal rate (MRR), and high cutting force (CF). This study aimed to resolve the machining parameters and the material adhesion by carrying out an experimental evaluation with multiobjective optimization of the machining factors on end-milling of AL8112 alloy using copra oil-based multi-walled carbon nanotube (MWCNTs) nanolubricant. The nano-lubricant preparation was done using the two-step method, and nano-lubricants were implemented via the minimum quantity lubrication (MQL) method with the five machining factors. Additionally, the multi-objective optimization and prediction study was achieved using the ramp and desirability bar plot for the three responses, i.e., SR, MRR, and CF under the quadratic rotatable central composite design (QRCCD). The multiobjective optimization result shows that the minimum SR of 1.16 μm, maximum MRR of 52.1 mm3/min, and minimum CF of 33.75 N was obtained at the optimized machining factors. Furthermore, the models predicted the experimental results accurately. In conclusion, the multi-objective optimization with copra oil-based MWCNT’s-nano-lubricant enhanced machine parts’ production for sustainable additive manufacturing

Recent advancements in nano-lubrication strategies for machining processes considering their health and environmental impacts

Industries have been seeking an efficient lubrication system that meets the requirement of sustainability without compromising manufacturing efficiency or final part quality. Conventional cutting fluids have been recognized as hazardous to the environment, health and economy of industries. The nano lubrication strategy has emerged as a sustainable and power-efficient lubrication system with encouraging performance in machining processes. This paper encapsulates an overview of the impact regarding usage of nanofluid as a cutting fluid in different machining processes. The recent innovations in the past decade, altered nano lubrication systems have been briefly summarized. A state of art review commences with a short synopsis of the historic perspective followed by a summary of the impact of nanofluid on different machining processes. The discussion section has been bifurcated according to the characterization of machining performance metrics. The environmental and health issues that emerged with the use of nanofluid are then discoursed thoroughly. Finally, the major findings are summarized and the future scope of research is identified. It can be quantified that the implementation of a nano lubrication system can significantly improve the heat transfer characteristic of base fluid which ultimately leads to the functionally tremendous product. However, there are major unknowns related to the health and environmental impact of nanoparticles

Prediction Of The Coefficient Of Friction In The Single Point Incremental Forming Of Truncated Cones From A Grade 2 Titanium Sheet

The aim of this paper is to analyze the effect of the process parameters on the coefficient of friction (COF) in the single-point incremental forming process. This investigation may be useful for further FEM analyses where the tool-workpiece contact must be set appropriately to obtain adequate results. The friction was analyzed between a solid tungsten carbide ⌀8 hemispherical ended tool with a radius of 4 mm and a grade 2 pure titanium sheet. As a lubricant, 10W40 engine oil was used. The experiment was of a central composite design and 20 runs in random order were carried out. The influence of input factors, namely spindle speed, tool feed and incremental step depth, was analyzed for the COF response. Two type of equations founded in the literature have been acquired to calculate COF values. An investigation of COF analysis was done for initial tool contact, the first tool full depth contact and stabilized forming region. Additionally, single components of the horizontal force (X-axis and Y-axis) were taken into account. Analysis of variance shows that there is no correlation between the input factors and the COF responses. However, the mean model fitted to the results obtained allows for the prediction of the COF by using the vertical force component and only one horizontal force component. The resulting mean value of the COF between the tool and the workpiece equals 0.4 for Eq. (1) initial contact, stabilized forming: Eq. (1) 0.656 and Eq. (2) 0.469

Impact of Palm Oil based Minimum Quantity of Lubrication on Machinability of Ti and its Alloy (Ti-6AI-4V)

This project investigates the usage of palm oil as a metal cutting fluid in minimum quantity lubrication assisted turning operations and its effect on surface roughness, tool wear and cutting temperature for Titanium alloy Ti-6Al-4V. Artificial Neural Network models were developed to determine the optimum cutting parameters considering the sustainability of palm oil in titanium alloy machining to improve future manufacturing costs and qualities

Proceedings of the 4th International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME2018)

The Mechatronics Department (Accredited by National Board of Accreditation, New Delhi, India) of the G H Patel College of Engineering and Technology, Gujarat, India arranged the 4th International Conference on Innovations in Automation and Mechatronics Engineering 2018, (ICIAME 2018) on 2-3 February 2018. The papers presented during the conference were based on Automation, Optimization, Computer Aided Design and Manufacturing, Nanotechnology, Solar Energy etc and are featured in this book

A review on conventional and nonconventional machining of SiC particle-reinforced aluminium matrix composites

AbstractAmong the various types of metal matrix composites, SiC particle-reinforced aluminum matrix composites (SiCp/Al) are finding increasing applications in many industrial fields such as aerospace, automotive, and electronics. However, SiCp/Al composites are considered as difficult-to-cut materials due to the hard ceramic reinforcement, which causes severe machinability degradation by increasing cutting tool wear, cutting force, etc. To improve the machinability of SiCp/Al composites, many techniques including conventional and nonconventional machining processes have been employed. The purpose of this study is to evaluate the machining performance of SiCp/Al composites using conventional machining, i.e., turning, milling, drilling, and grinding, and using nonconventional machining, namely electrical discharge machining (EDM), powder mixed EDM, wire EDM, electrochemical machining, and newly developed high-efficiency machining technologies, e.g., blasting erosion arc machining. This research not only presents an overview of the machining aspects of SiCp/Al composites using various processing technologies but also establishes optimization parameters as reference of industry applications

Wear rate reduction mechanism of minimum quantity lubrication to enhance machinability using hybrid nano-coolant (TiO2- Al2O3)

In the advanced manufacturing world, the applications of aluminium alloys are dramatically increasing in various engineering fields due to their exciting mechanical properties. The machining of aluminium alloy has the challenges of occurrences of tool wear, surface degradation forming built-up edge, adhesion due to high heat and friction at the contact zone. Hence, proper cooling and lubrication technique can improve machining efficiency by minimizing tool wear, friction, surface roughness. Recently, researchers have been giving priorities to the Minimum Quantity Lubrication (MQL) technique using minimum fluid compared to conventional coolant technique. Hence, the objective of this study to investigate machining performance in terms of the tool wear mechanism, including surface roughness, material removal rate and to develop multi-objective optimization of end milling of aluminium alloy with conventional flooded and hybrid nanofluid (HNF) MQL conditions. The TiO2-Al2O3 hybrid nanofluid is synthesized for volume concentration from 0.02 to 0.1% using the two-step synthesis method. The stability of hybrid nanofluids is assessed using zeta potential test, UV- Vis spectral analysis, sedimentation photograph and the thermophysical properties are measured for the temperature range of 30 to 80 oC. For machining central composite design of response surface methodology is followed. The study considers the flow rate of commercial mineral oil (added 5 % with water) as 30 L/min for the flooded condition and the flow rate of HNF as 0.3 to 1.2 ml/min for the HNF-MQL condition. The mechanism of tool wear is presented using SEM micrographs with EDX analysis as well as the interaction of tool wear with surface roughness and material removal rate is also analysed. The study reveals that the TiO2-Al2O3 hybrid nanofluid has a stability period of more than one month, showing standard zeta potential value (more than 30 mV), absorbance ratio (more than 80 %) with no apparent sedimentation. Besides, the new HNF also shows significant improvement of thermophysical properties in terms of thermal conductivity (37.44%) and viscosity (101.22 %). In the case of machining, second-order mathematical models of tool wear, including the surface roughness and material removal rate, are developed for both cooling conditions with excellent accuracy. Adhesion, abrasion marks, built-up edge, edge breakage or chipping are the significant wear of the study for both conditions. The performance of HNF-MQL machining in terms of considered response factors shows significant improvement compared to flood machining. Among all the response factors, tool wear (29 %) and surface roughness (30.13 %) noticeably improved for the application of HNF-MQL, followed by material removal rate (12.16 %). The material removal rate also shows consistency for the HNF-MQL condition. Besides, the tool wear mechanism shows a significant relationship with the efficiency of machining, revealing a significant interaction with surface roughness and material removal rate. Finally, from optimization results, tool wear is improved by 21.36 %, while the surface roughness is improved by 80.90%. Hence, experimental results revealed the prospective utilization of hybrid nanofluids in machining as coolant. Beneficial results of the study in HNF characterization terms and machining performance measures compared to flood machining suggest that researcher and engineers study and apply various types of HNF-based MQL technique in advanced manufacturing industries