Amar Patnaik

Parametric optimization of wire electrical discharge machining (WEDM) process using taguchi method

Wire electrical discharge machining (WEDM) is a specialized thermal machining process capable of accurately machining parts of hard materials with complex shapes. Parts having sharp edges that pose difficulties to be machined by the main stream machining processes can be easily machined by WEDM process. Technology of the WEDM process is based on the conventional EDM sparking phenomenon utilizing the widely accepted non-contact technique of material removal with a difference that spark is generated at wire and work piece gap. Since the introduction of the process, WEDM has evolved as a simple means of making tools and dies to the best alternative of producing micro-scale parts with the highest degree of dimensional accuracy and surface finish. This paper outlines the development of a model and its application to optimize WEDM machining parameters. Experiments are conducted to test the model and satisfactory results are obtained. The methodology described here is expected to be highly beneficial to manufacturing industries, and also other areas such as aerospace, automobile and tool making industries.

A Comparative Study on Different Ceramic Fillers Affecting Mechanical Properties of Glass—Polyester Composites

Filler plays a major role in determining the properties and behavior of particulate composites. In this study a series of glass fiber reinforced polyester composites are fabricated using flyash, aluminum oxide (Al 2O3) and silicon carbide (SiC) particles as filler materials. The effects of these three different ceramics on the mechanical properties of glass—polyester composites are investigated. Comparative analysis shows that with the incorporation of these fillers, the tensile strength of the composites decrease significantly. The flexural properties, interlaminar shear strength, density and hardness are also affected by the type and content of filler particles. It is found that the presence of SiC improves the hardness of the glass—polyester composites, whereas the other two fillers show marginal effect. The study reveals that the reduction in tensile strength is the minimum in case of flyash among all the fillers. Further, the composite with low flyash content (10 wt%) exhibits improved flexural strength. It is thus interesting to find that an industrial waste-like flyash shows better filler characteristics compared to those of alumina and SiC. Moreover, being cheap and easily available, it would hopefully provide a cost effective solution to composite manufacturers.

Processing and Characterization of Jute-Epoxy Composites Reinforced with SiC Derived from Rice Husk

This article depicts the processing and mechanical characterization of a new class of multi-phase composites consisting of epoxy resin reinforced with jute fiber and filled with silicon carbide (SiC) particulates. The SiC used as filler material in this work was prepared from rice husk through plasma-processing technique. The effect of filler in modifying the physical and mechanical properties of jute—epoxy composites has been studied. It is found that the incorporation of rice husk derived SiC modifies the tensile, flexural, and inter-laminar shear strengths of the jute—epoxy composites. The micro-hardness and density of the composites are also greatly influenced by the content of these fillers.

Implementation of Taguchi Design for Erosion of Fiber-Reinforced Polyester Composite Systems with SiC Filler

With the increased use of fiber/filler-reinforced polymer composites in erosive work environments, it has become extremely important to investigate their erosion characteristics intensively. This article describes the development of a multi-component composite system consisting of thermoplastic polyester resin reinforced with E-glass fiber and SiC particles, and studies its erosion behavior under different operating conditions. A room temperature erosion test facility and Taguchis orthogonal arrays are used for experimentation. It identifies significant control factors influencing the erosion wear and also outlines significant interaction effects. Finally, optimal factor settings for minimum wear rate have been determined using a genetic algorithm.

Parametric Optimization Erosion Wear of Polyester-GF-Alumina Hybrid Composites using the Taguchi Method

The improved performance of polymer-based hybrid composites in tribological applications has recently been a subject of considerable interest. A hybrid composite consists of the matrix reinforced with both fibers and particulate fillers. Alumina has the potential to be used as filler in such a multi-component system. This article investigates the effect of alumina filling on the erosion wear performance of glass fiber-reinforced polyester composites. For this purpose, an air jet type erosion test configuration and the design of experiment approach utilizing Taguchis orthogonal arrays are used. Taguchis design eliminates the need for repeated experiments; thus saving time, materials, and cost. The systematic experimentation leads to identifying significant factors and their interactions that predominantly influence the erosion wear. Pure glass-polyester composite without filler shows greater erosion rate whereas a significant improvement in the erosion resistance is observed with alumina fillers. This may be due to restriction of fiber-matrix debonding. The morphologies of the eroded surface are examined by a scanning electron microscope. Finally, optimal factor settings for minimum wear rate have been determined using genetic algorithm.

A Taguchi Approach for Investigation of Erosion of Glass Fiber - Polyester Composites

Polyester composites reinforced with three different weight fractions of woven E-glass fiber reinforcement are developed. To study the effect of various operational and material parameters on erosive wear behavior of these composites in an interacting environment, erosion test are carried out. For this purpose, an air jet type erosion test rig and the design of experiments approach utilizing Taguchis orthogonal arrays are used. The findings of the experiments indicate that erodent size, fiber loading, impingement angle and impact velocity are the significant factors in a declining sequence affecting the wear rate. Significance of erosion efficiency in identifying the wear mechanism is highlighted. It is confirmed that the glass-reinforced-polyester composites exhibit mostly semi-ductile erosion response. An optimal parameter combination is determined, which leads to minimization of erosion rate. Analysis of variance (ANOVA) is performed on the measured data and signal to noise (S/N) ratios. A correlation derived from the results of Taguchi experimental design is proposed as a predictive equation for estimation of erosion wear rate of these composites. It is demonstrated that the predicted results obtained using this equation are consistent with experimental observations. Finally, optimal factor settings for minimum wear rate are determined using genetic algorithm.

Modeling and Prediction of Erosion Response of Glass Reinforced Polyester-Flyash Composites

Solid particle erosion of polymer composites is a complex surface damage process, strongly affected by material properties and operational conditions. To avoid repeated experimentation, it is important to develop predictive equations to assess material loss due to erosion wear under any impact conditions. This paper presents the development of a mathematical model for estimating erosion damage caused by solid particle impact on flyash filled glass fiber reinforced polyester composites. The model is based upon conservation of particle kinetic energy and relates the erosion rate with composite properties and test conditions. Another correlation derived from the results of Taguchi experimental design is proposed as a predictive equation for erosion wear of these fiber reinforced composites. Further, considering the complexity and high degree of nonlinearity in the erosion process, an artificial neural networks (ANN) technique is implemented as an effective tool for prediction of wear response of these composites in a larger space. Finally, the results of a mathematical model and the ANN model are compared with those obtained from experimentation.

Effect of Different Parameters on Mechanical and Erosion Wear Behavior of Bamboo Fiber Reinforced Epoxy Composites

The application of natural fibers as reinforcement in polymer composites has been continuously growing during the last few decades. These composites find diverse applications in hostile environment where they are exposed to external attacks such as solid particle erosion. Also, in many respects, the mechanical properties of different polymer composites are their most important characteristics. Therefore, improvement of the erosion resistance and mechanical behavior of polymer composites are the prime requirements in their applications. Bamboo fiber which is rich in cellulose, relatively inexpensive, and abundantly available has the potential for reinforcement in polymers. To this end, an attempt has been made in this paper not only to study the utilization potential of bamboo fiber in polymer composites but also to study the effect of various parameters on mechanical and erosion wear performance of bamboo fiber reinforced epoxy composites.

Analysis of Dry Sliding Wear Behavior of Red Mud Filled Polyester Composites using the Taguchi Method

Red mud is an industrial waste generated during the production of alumina by Bayer’s process. Using this red mud as the filler, particulate reinforced polyester composites have been prepared and their dry sliding wear behavior has been studied experimentally. For this a standard pin-on-disc test set-up and Taguchi’s orthogonal arrays were used. Taguchi’s experimental design method eliminates the need for repeated experiments and thus saves time, materials, and cost. It identifies the significant control factors and their interactions predominantly influencing the wear rate. From the experimental findings, an optimal combination of control factors was obtained on the basis of which a predictive model was proposed. This model was validated by performing a confirmation experiment with an arbitrarily chosen set of factor combinations. Finally, the optimal factor settings for minimum wear rate under specified experimental conditions have been determined using a genetic algorithm.

An evolutionary approach to parameter optimisation of submerged arc welding in the hardfacing process

The Submerged Arc Welding (SAW) process finds wide industrial application due to its easy applicability, high current density and ability to deposit a large amount of weld metal using more than one wire at the same time. It is highly emphasised in manufacturing especially because of its ability to restore worn parts. SAW is characterised by a large number of process parameters influencing the performance outputs such as deposition rate, dilution and hardness, which subsequently affect weld quality. An exhaustive literature survey indicates that five control factors, viz., arc current, arc voltage, welding speed, electrode stick-out and preheat temperature, predominantly influence weld quality. In relation to this, an attempt has been made in this study to analyse the effect of process parameters on outputs of welding using the Taguchi method. The relationship between control factors and performance outputs is established by means of nonlinear regression analysis, resulting in a valid mathematical model. Finally, Genetic Algorithm (GA), a popular evolutionary approach, is employed to optimise the welding process with multiple objectives.