Abstract: The reduction and distillationcontainer in titanium-sponge-production is of great concern. In order to get access to a highly efficient vessel which can produce sponge titanium of high quality, a new structureof new material was brought forward in this paper. This new structure, with doublelayers, inner layer of carbon steel and outer layer of stainless steel, was a substitute for traditional single-layer stainless steel container. This new optimization method of 12t container brought in the paper can reduce the impurities in the sponge titanium lump andincrease the times of the container to use.Of cause, it has a great improvement in yield per unit time. For the purpose of improving the reliability of this new optimization structure, temperature and stress field was established and simulated by an integrated FEM/FEM system based on ANSYS. This theory, therefore, can be one of the solutions to the development of titanium-sponge-production equipments by means of the thermal stress field analysis.
Abstract: This paper proposes a hybrid model combining artificial neural networks (ANN) and simple average exponential smoothing (SES) forecasting models, termed as the ANNSES model. The proposed model attempts to incorporate the linear characteristics of SES and nonlinear patterns of ANN for predicting the score of suppliers in an e-procurement system of an automobile industry. The MAPE and RMSE errors obtained indicate that predictions upto a month ahead was accurate using the hybrid model compared to those obtained using ANN and SES forecasting models individually.
Abstract: The present paper reports the optimization of process parameters in hybrid machining process (Electro-Discharge Diamond Surface Grinding) of Ti-6Al-4V with multiple performance characteristics using the combination of Grey Relational Analysis (GRA) and Taguchi approach. The various input process parameters in this work are wheel speed (RPM), duty factor, current (ampere) and pulse on-time (µs). In this research work nine experiments have been conducted according to the Taguchi’s L9 orthogonal array on in-house-designed & fabricated EDDSG set-up. The machining parameters wheel speed (S), duty factor (DF), current (I) and pulse on-time (Ton) are optimized with consideration of multiple performance characteristics such as material removal rate (MRR) and average surface roughness (Ra). The confirmation experimental results show that combined Grey-Taguchi approach enhances the machining performance in EDDSG of Ti-6Al-4V.
Abstract: In this study, input parameters of Electrical Discharge machining (EDM) process have been optimised for two different materials EN-8 and Die steel-D3 were machined by using sintered copper electrode. Analysis of variance (ANOVA) was applied to study the influences of process parameters viz: - peak current, pulse on time, di-electric pressure and diameter of electrode on material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) for both materials. Response surface methodology (RSM) has been applied to optimise the multi responses in order to get maximum MRR, minimum TWR and minimum SR. Furthermore, mathematical model has been formulated to estimate the corresponding output responses for both work pieces. It has been observed that compared to EN 8 material, the MRR value is low and TWR is high for D3 material. However the SR value is marginally lower than obtained in EN8.R2 value is above 0.90 for both work pieces.
Abstract: The numerical control (NC) heat bending of thin-walled Ti-alloy tube with large diameter and small bending radius with Ф50×1×R75mm (diameter OD bending radius CLR) is explored by 3D-FE thermal-mechanical coupling simulation of heat conducting and NC bending. The results show that: (1) The heating of both pressure die and mandrel is proved to be appropriate to obtain the required temperature field. (2) In terms of wall thickness variation, wrinkling and cross-section deformation, the optimum span of the key parameters are obtained: the bending velocity of 0.4rad/s, the matched pressure die speed of 80%-110%, and temperature of 600-800°C.
Abstract: This paper applies Taguchi methodology to optimize the machining parameters in micro EDM-drilling of copper using a tungsten carbide tool electrode. The experimental design has been applied to find out the optimal combination of process parameters corresponding to maximum material removal rate, minimum over-cut, minimum tool wear ratio and minimum error-in-depth of drilled hole. Orthogonal array and signal-to-noise ratio is employed to optimize the process parameter. Analysis of variance (ANOVA) is performed to determine the influence of parameters such as, gap voltage, capacitance, feed rate and spindle rotationof micro EDM-drilling process on the performance measures. From the analysis, it is concluded that gap-voltage and capacitance arethe most significant parameters whereas spindle speed is the least among all.
Abstract: Most of real-life engineering problems are objectives optimization problems. In many cases objectives under consideration conflict with each other and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other.FMS Scheduling problem is considered as one of the most difficult NP-hard combinatorial optimization problems. Therefore, determining an optimal schedule and controlling an FMS is considered a difficult task. It is difficult for traditional optimization techniques to provide the best solution. In this paper, we propose a multi-objective genetic algorithm for effectively solving job processing FMS Scheduling problem. An attempt has been made to generate a schedule using Genetic Algorithm with Roulette Wheel Base Selection Process to minimize Total Make Span Time and to maximize machine utilization time.
Abstract: With the exponential development of mobile communications and the miniaturization of radio frequency transceivers, the need for small and low profile antennas at mobile frequencies is constantly growing. Therefore, new antennas should be developed to provide both larger bandwidth and small dimensions. The aim of this project is to design and optimize the bandwidth of a Planar Inverted-F Antenna (PIFA) in order to achieve a larger bandwidth in the 2 GHz band. This paper presents an intelligent optimization technique using a hybridized Genetic Algorithms (GA) coupled with the intelligence of the Binary String Fitness Characterization (BSFC) technique. The optimization technique used is based on the Binary Coded GA (BCGA) and Real-Coded GA (RCGA). The process has been further enhanced by using a Clustering Algorithm to minimize the computational cost. Using the Hybridized GA with BSFC and Clustering, the bandwidth evaluation process has been observed to be more efficient combining both high performance and minimal computational cost. During the optimization process, the different PIFA models are evaluated using the finite-difference time domain (FDTD) method.
Abstract: In submerged arc welding (SAW), weld quality is greatly affected by the weld parameters such as welding current, traverse speed, arc voltage and stickout since they are closely related to weld joint. The joint quality can be defined in terms of properties such as weld bead geometry and mechanical properties. There are several control parameters which directly or indirectly affect the response parameters. In the present study, an attempt has been made to search an optimal parametric combination, capable of producing desired high quality joint in submerged arc weldment by Taguchi method coupled with weighted principal component analysis. In the present investigation three process variables viz. Wire feed rate (Wf), stick out (So) and traverse speed (Tr) have been considered and the response parameters are hardness, tensile strength (Ts), toughness (IS).