A. Gopala Krishna

Simultaneous optimization of multiple performance characteristics in WEDM for machining ZC63/SiCp MMC

The compliance of an integrated approach, principal component analysis (PCA), coupled with Taguchi’s robust theory for simultaneous optimization of correlated multiple responses of wire electrical discharge machining (WEDM) process for machining SiCP reinforced ZC63 metal matrix composites (MMCs) is investigated in this work. The WEDM is proven better for its efficiency to machine MMCs among others, while the particulate size and volume percentage of SiCp with the composite are the utmost important factors. These improve the mechanical properties enormously, however reduce the machining performance. Hence the WEDM experiments are conducted by varying the particulate size, volume fraction, pulse-on time, pulse-off time and wire tension. In the view of quality cut, the most important performance indicators of WEDM as surface roughness (Ra), metal removal rate (MRR), wire wear ratio (WWR), kerf (Kw) and white layer thickness (WLT) are measured as responses. PCA is used as multi-response optimization technique to derive the composite principal component (CPC) which acts as the overall quality index in the process. Consequently, Taguchi’s S/N ratio analysis is applied to optimize the CPC. The derived optimal process responses are confirmed by the experimental validation tests results. The analysis of variance is conducted to find the effects of choosing process variables on the overall quality of the machined component. The practical possibility of the derived optimal process conditions is also presented using SEM.

Selection of optimal conditions in the surface grinding process using a differential evolution approach

Abstract The selection of machining parameters in any machining process significantly affects the production rate, quality, and cost of a component. The present work involves the application of a recently developed global optimization technique called differential evolution to optimize the machining parameters of a surface grinding process. The wheel speed, workpiece speed, depth of dressing, lead of dressing, cross-feed rate, wheel diameter, wheel width, grinding ratio, wheel bond percentage, and grain size are considered as the process variables. The production cost, production rate, and surface finish are evaluated for the optimal grinding conditions, subject to the constraints of thermal damage, wheel wear parameter, and machine tool stiffness. An example is taken from the literature to compare the results obtained by the proposed approach with other approaches.

An integrated evolutionary approach for modelling and optimisation of CNC end milling process

In this research, a novel integrated evolutionary based approach is presented for the modelling and multi-objective optimisation of a machining process. Computer numerical control end milling process has been considered in the present work as it finds significant applications in diversified engineering industries. Firstly, genetic programming (GP) has been proposed for explicit formulation of non-linear relations between the machining parameters (spindle speed, feed and depth of cut) and the performance measures of interest (material removal rate and tool wear) using experimental data. Genetic programming approach optimises the complexity and size of the model during the evolutionary process itself and hence this technique has the potential to identify the true models avoiding the problems of conventional methods. Central composite second-order rotatable design had been utilised to plan the experiments and the effect of machining parameters on the performance measures is also reported. In the second part, as the chosen responses are conflicting in nature, a multi-objective optimisation problem has been formulated. A non-dominated sorting genetic algorithm-II (NSGA-II) has been used to simultaneously optimise the objective functions. The Pareto-optimal set generated is useful for process planning which is a critical link in computer-integrated manufacturing (CIM).

Multi-Objective Optimization of EDM Process Parameters using Taguchi Method, Principal Component Analysis and Grey Relational Analysis

This paper investigates multi-objective optimization of electrical discharge machining process parameters using a new combination of Taguchi method and principal component analysis based grey relational analysis. In this study, three conflicting performance characteristics related to surface integrity such as surface roughness, white layer thickness and surface crack density are considered in electrical discharge machining of RENE80 nickel super alloy. The process parameters considered are peak current, pulse on time and pulse off time. The experiments are conducted based on Taguchi method and these experimental results are used in grey relational analysis and weights of the corresponding performance characteristics are determined by principal component analysis. The weighted grey relational grade is used as a performance index to determine optimum process parameters and results of the confirmation experiments indicate that the combined approach is effective in determining optimum process parameters.

Mechanical properties improvement of weldments using vibratory welding system

From the last few decades, vibratory welding techniques have been used for improving the mechanical properties of weldments. Previous results showed that welded test specimens under vibratory conditions exhibited improvements in mechanical properties than the conventional arc welding. In this present work, vibratory set-up has been developed for inducing mechanical vibrations during welding operation. The designed vibratory set-up produces the required frequency with amplitude and acceleration in terms of voltages. In the current investigation, weld specimens were prepared while varying the two input parameters: voltage and time of vibration. And the remaining process parameters such as travel speed, current, and other electrode parameters were kept constant. Metallurgical properties showed that refined microstructure has been achieved for the vibratory welded specimens. The refined grain structure is responsible for the improvement in flexural strength, ultimate tensile strength, impact strength, and hardness of the vibratory weld pieces.

Flexural Strength Improvement of Welded Joints Prepared by Vibratory Welding Process

Vibration techniques have been used in welding for improving the mechanical properties of metals in the last few decades. In the present work, vibratory setup has been used for inducing mechanical vibrations into the weld pool during welding. The designed vibratory setup produces the required frequency with the amplitude and acceleration in terms of voltages. An increase in the flexural strength of the weld pieces in to the heat affected zone (HAZ) has been observed. The increase in mechanical properties is attributed to, as the weld pool solidifies, grains are not only limited in size but also dendrites are broken before they grow large in size. Refined microstructure has been observed. The above mechanism is responsible for the improvement in flexural strength of weld pieces welded with vibratory setup compared to without vibration during welding.

Principal Component Analysis of Correlated WEDM Performance Characteristics during Machining ZC63/SiCP MMCs

Abstract The present investigation proposes the optimization of the wire electrical discharge machining process for machining ZC63/SiCP metal matrix composite. SiC particulate size and its percentage with the matrix are considered as the process variables along with the most significant WEDM variables such as pulse-on time, pulse-off time and wire tension. In view of quality cut, surface roughness, metal removal rate and kerf are considered as the process responses. Since, these responses are correlated with each other and they need to be optimized simultaneously. Therefore, the problem is treated as multi-response optimization problem. Principal component analysis (PCA) has been implemented to convert the multi-objective optimization problem in to single objective optimization problem by converting the multiple correlated responses in to the total quality index. Taguchis robust optimization technique has been adopted to derive the set optimal process parameters which maximize the total quality index. The derived optimal process responses are confirmed with the experimental validation tests. ANOVA is conducted find the importance of the chosen process variables on the overall quality of the machined component. The practical possibility of the obtained optimal process performance is observed using SEM studies.

A smart prediction tool for estimating the impact strength of welded joints prepared by vibratory welding process

Previous researches have been devoted to development of vibratory setup for inducing mechanical vibrations into the weld pool during welding process. The designed vibratory setup produces the required frequency with suitable amplitude and acceleration in terms of voltages. This helps in producing uniform and fine grain structure in the welded joints which results in an improvement in the mechanical properties of the weld pieces at heat affected zone. This paper presents the development of a smart prediction tool by implementing generalized regression neural network to establish a relation between vibration parameters such as input voltage to the vibromotor, time of vibration and impact strength of vibratory weld joints. In order to validate the feasibility of the developed prediction tool, a comparison is made with the experimental results.

Mechanical Milling Influence on Lattice Vibrational Behaviour of MoO3-V2O5 Composite Nanopowders

The present work aimed to synthesis an ultrafine thermally excelled MoO3-V2O5 nanocomposite powders using mechanical milling synthesis technique at different time intervals. Spectroscopic characterizations like Powder X-ray diffraction (PXRD), Scanning Electron Microscope, Electron Dispersive X-ray Spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy, Raman, optical absorption and Thermogravimetric and Differential Thermal Analysis were used to characterize the synthesised composite powders. The orthorhombic phases of MoO3 and V2O5 are revealed by the X-Ray peak profile demonstrates. The average crystalline sizes and lattice strain evaluated from XRD data and W-H plot calculations were found to be nearly equal. The qualitative information of the prepared nanocompositie is revealed from Raman analysis. The vibrational modes of Raman spectra also reveal the orthorhombic phases of the prepared Nanocomposite. The depositions of vanadium powders on molybdenum are revealed by SEM images. The fundamental modes of Mo=O and V=O and other functional groups were analysed by FT-IR. Thermogravimetry analysis and Differential Thermal Analysis (DTA) of MoO3-V2O5 revealed that, the composite is stable up to 670 °C with a insignificant weight loss. Hence the synthesised mixed lubricous oxide nanocomposite may be used as a solid lubricant at elevated temperatures.

An integrated evolutionary approach for simultaneous optimization of laser weld bead characteristics

The selection of optimal welding parameters in any welding process significantly improves the quality, production rate, and cost of a component. The weld bead characteristics such as bead width, depth of penetration, and heat-affected zone are the prominent factors for evaluating the performance of a welded joint. The work presents a novel evolutionary multi-objective optimization approach to derive the optimal laser welding conditions for the weld bead geometrical parameters. The welding experiments were conducted with the consideration of pulse frequency, pulse width, welding speed, and pulse energy as the process-control variables to evaluate the weld bead characteristics. Empirical models for the bead characteristics were developed in terms of the input variables using response surface methodology. The individual and interactive effects of the variables on the responses were also analyzed. As the influence of control variables on the bead characteristics is conflicting in nature, the problem is formulated as a multi-objective optimization problem to simultaneously optimize the output parameters. The aim is to simultaneously minimize the bead width, maximize the depth of penetration, and minimize the heat-affected zone. An efficient evolutionary algorithm called non-dominated sorting genetic algorithm-II was applied to derive the set of Pareto-optimal solutions. The derived optimal process responses were confirmed with the experimental values. The proposed integrated methodology can be applied to any welding process to automate the process conditions in computer-integrated manufacturing environment.