Manufacturing Technology Today

S. Balasivanandha Prabu ¹, L. Karunamoorthy ¹

Affiliations
1 Dept. of Mechanical Engineering, CEG Campus, Anna University, Chennai-600025, IN

Abstract

This paper reports the influence of particle size and heat treatment (T6) on some mechanical properties of Al-Si alloy based SiC particulate composites. The T6 heat treatment was carried out to improve' the mechanical properties. The heat treatment consists of solution treatment and quenching followed by artificial ageing. After solution treatment and quenching, copper and magnesium rich compounds dissolve in aluminium matrix. The composites produced by stir casting technique were solution treated isothermally at 538°C for 8 hrs to dissolve the precipitates. An electric furnace with a temperature control of ±3°C was used for solution treatment. Ageing was carried out at 155°C for 5 hrs. The mechanical properties such as hardness, tensile strength, failure strain and compressive behaviour have been studied for 9,11,15,40 and 60-micron size particulate added Al-Si (A384) alloy. The fracture behaviour and microstructural aspects were studied from microstructure and SEM photograph.

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S. Ramesh ¹, M. Pradeep Kumar ², L. Karunamoorthy ², K. S. Vijay Sekar ²

Affiliations
1 Dept. of Mechanical & Prod. Engg., Sathyabama University, Chennai, IN
2 Dept. of Mechanical Engg., Anna University, Chennai, IN

Abstract

Titanium and its alloys are attractive materials due to their unique high strength to weight ratio and their exceptional corrosion resistance. This paper combines the predictive machining approach with neural network modeling of cutting parameters. Experimental work has been performed in orthogonal cutting of Ti-6Al-4V using Plain Carbide tool. At the selected cutting conditions the forces have been measured. The experimental data were utilized to train the developed simulation environment based on back propagation neural network modeling. The cutting speed, feed, depth of cut have been considered as the input parameters and cutting force, feed force as output parameters to develop the model. The trained neural network was used in predicting the cutting parameters. Predictive ANN models were found to be capable of better predictions of forces about 93 to 97% accuracy within the range that they had been trained.

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R. Ramakrishnan ¹, L. Karunamoorthy ²

Affiliations
1 Dept. of Mechanical Engineering, Panimalar Engineering College, Chennai, IN
2 Dept. of Mechanical Engineering, Anna University, Chennai, IN

Abstract

This paper describes the development of a mathematical model and multi response optimization for predict and select the best cutting parameters of wire electro discharge machining (WEDM) process. To predict the performance characteristics namely material removal rate and surface roughness mathematical model using non-linear regression models were applied. AISI 02 Tool steel was selected as work material to conduct experiments. Experiments were planned as per Taguchi'sL16 orthogonal array. Each experiment has been performed using different cutting conditions of pulse on time, wire tension, delay time, wire feed speed, and ignition current. The responses were optimized concurrently using multi response signal to noise (MRSN) ratio in addition to Taguchi's traditional parametric design approach. Analysis of variance (ANOVA) was employed to identify the level of importance of the machining parameters on the multiple performance characteristics. Finally experimental confirmations were carried out to identify the effectiveness of this proposed method. A good improvement was obtained.

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D. Sathianarayanan ¹, L. Karunamoorthy ², G. S. Kandasami ³, B. Mohan ¹

Affiliations
1 Department of Production Technology, M.l.T. Campus, Anna University, Chennai, 600 044, IN
2 Department of Mechanical Engineering, CEG Campus, Anna University, Chennai, 600 025, IN
3 Jaya Engineering College, Tiruninravur, Chennai, IN

Abstract

Chatter develops easily during boring operation on a lathe because of low stiffness and damping of the system. The most important parameter is damping associated with the cutting process, which is related to cutting conditions. In this paper a method of utilizing the magnetorheological fluid’s non-linear vibration characteristics for increasing the cutting stability is proposed. The designed damper is a semi-actively controllable fluid damper, which improves cutting stability and suppresses the chatter vibrations. The damper employs a magnetorheological fluid that changes its rheological properties in the presence of a magnetic field. Varying the current flow through the magnetic coil can vary the damping force developed by the magnetorheological fluid damper. The results show that for a particular cutting condition a particular value of magnetic coil current is more effective in chatter suppression.

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S. Ragunathan ¹, L. Karunamoorthy ²

Affiliations
1 Department of Mechanical Engineering, Govt. College of Engineering, Salem-11, IN
2 Department of Mechanical Engineering, Anna University, Chennai-25, IN

Abstract

The deformation behaviours of flexibie materials for various handling conditions are analyzed using ANSYS software and their results are presented. This will help in the necessary robotic handling automation and proper handling of limp materials in the automotive and textile industries. A two step method of using dynamic and static analysis with a nine node flexible shell element produces flexible material simulations very close to actual deformation. The equilibrium equations are solved using the finite element method. The simulation must be sufficiently realistic to the robotic gripper designers' needs and be carried out quickly enough for the designer to optimize the grasping locations for handling flexible materials. Computational simulation with this model can assist the engineer in specifying design variables as gripping conditions, grasping locations and loads applied to supporting structure.

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S. Ragunathan ¹, L. Karunamoorthy ², S. Malligarjunan ¹

Affiliations
1 Department of Mechanical Engineering, Govt. College of Engineering, Salem-11, IN
2 Department of Mechanical Engineering, Anna University, Chennai-25, IN

Abstract

In this paper, a reconfigurable robotic gripper for grasping of limp materials has been developed and presented, based on pneumatic technology. To grasp flexible and fabric materials, it is necessary to have several pickup points, whose location is selected on the basis of the shape of the part to be grasped and it is also necessary to have low overall flow drop in the pneumatic circuits. This paper also presents the results of dynamic simulation and analysis of the reconfigurable gripper system in the dynamic simulation package ADAMS. The architecture of the gripper is simple and the choice of pneumatic actuators improves the reliability of the system.

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R. Ramakrishnan ¹, L. Karunamoorthy ²

Affiliations
1 Dept. of Mechanical Engineering, EVP Engineering College, Chennai-602103, IN
2 Dept. of Mechanical Engineering, Anna University, Chennai-600025, IN

Abstract

In Wire electrical discharge machining (WEDM) process the removal of metal takes place due to successive sparks generated between the wire electrode and the gap of the work-piece. WEDM machines are widely applied to produce complex and intricate shapes of components in hard and conductive materials. In order to predict the performance of the WEDM process many researchers have attempted using various experimental parameters such as applied voltage, pulse on time, delay time, ignition current, dielectric pressure, wire tension, servo reference mean voltage, wire feed speed. However the results of these studies are limited to certain process parameters and materials. In WEDM process there is no direct contact between the toot electrode and work-piece. Therefore there is no shear stress exerted during machining. In this present work, the study and development of a surface roughness prediction model for machining of Oil Hardened Non Shrinkage (OHNS) steel, using response surface methodology (RSM) was developed. A five axis Robofil 290 CNC WEDM manufactured by Charmilles Technologies is applied to carry out experiments. Experiments have been planned according to Taguchi's L16 fractional factorial orthogonal array. A 0.25 mm diameter zinc coated brass wire was selected as toot electrode. A first order mathematical model for surface roughness has been developed, in terms of pulse on time, wire tension, delay time and ignition current intensity. The effect of these cutting parameters on the surface roughness has been carried out using design of experiments and RSM. In addition, the analysis of variance (ANOVA) is applied to identify the significance of the developed model. The test results confirm the validity and adequacy of the developed RSM model.

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K. Palanikumar ¹, L. Karunamoorthy ²

Affiliations
1 Sathyabama Institute of Science & Technology, Deemed University, Chennai-119, IN
2 Department of Mechanical Engineering, College of Engineering, Anna University, Chennai-25, IN

Abstract

In recent years, the utilization of GFRP composite materials in many different engineering fields has undergone a tremendous increase. Accordingly, the need for accurate machining of composites has increased enormously. However, the knowledge acquired in machining of ductile metals is not suitable for composites. To make an effective use of composites, it is essential that a high degree of confidence be achieved in predicting the process state variables. This work has been taken up with a view to bring out the benefits in developing a model for surface roughness and tool wear prediction in terms of speed, feed, depth of cut and work piece (fiber orientation angle) in composite material. Fiber orientation angle is the variable, which is specially applied to the fiber reinforced composite material. Experiments were conducted as per full factorial experimental design. Regression analysis is used to develop the model. Sum of squares are calculated using Yates method. Analysis of variance is used to study the effect of process parameters on machining process. The developed models can be used to predict the surface roughness and tool wear for turning of GFRP composites within the ranges of variable studied. This procedure eliminates the need for repeated experiments, time and material consumption by the use of conventional procedure.

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