Multi-objective optimization of process parameter in Activated Tungsten Inert Gas (A-TIG) Welding

Tungsten Inert Gas (TIG) welding is a process which is used in those applications requiring a high degree of quality and accuracy. However, this welding process has disadvantage of less productivity. To overcome this disadvantage, Activated Tungsten Inert Gas (A-TIG) welding was developed. In the present work, experiments were performed on 6 mm thick 304L stainless steel plates using A-TIG welding process. TIG welding fixture was designed and developed for getting fixed arc length and different welding speeds. Three different combination of fluxes like TiO2+ MnO2, SiO2+ TiO2 and Al2O3+ CaO were used to investigate its effect on geometric shape and distortion of weldments.  A-TIG welding process parameters optimization was performed by multi-objective optimization technique named as Gray Principal Component Analysis (G-PCA). The optimum process parameters were found to be 140 A current, 100 mm/min speed and mixture of SiO2 and TiO2 flux

Optimization of Surface Roughness Using RSM Techniques in Dry Turning of Hardened Steel

Machining of hardened steel using multilayer coated carbide tools provides lot of opportunities in saving machining time as compared to traditional grinding processes.   In this paper, optimization of cutting parameters in hard turning of AISI D3 steel using multilayer coated carbide inserts under dry turning operations were done.  Several experiments were conducted using Response Surface Methodology with face centered design.  Analysis of Variance (ANOVA) was performed to find out the effect of machining parameters on surface roughness in hard turning.  Cutting speed, feed and depth of cut were selected as parameters to optimize surface roughness.  Effect of individual independent variables and their interaction plots were drawn to study the effect of input parameters on output parameter.  It was found that feed rate was most significant factor influencing the surface roughness in hard turning.  Quadratic model was proposed to predict surface roughness value

Effect of Cutting Parameters on Power Consumption and Tool Wear during Turning of EN31 Steel under Minimum Quantity Solid Lubrication

This paper reports the comparative investigation of effect of cutting parameters i.e. cutting speed, feed and depth of cut on power consumption and too wear during turning operation of EN31. Three cooling techniques were employed during the turning operations of which one is Minimum Quantity Solid Lubrication (MQSL). Calcium Fluoride powder used as solid lubricant and mixed with SAE 40 oil, which was used as MQSL cooling technique. The experimental results highlight the power consumption was less during MQSL cooling technique. Further, the tool wear was also less in MQSL cooling compare to other cooling technique

Determination of Natural Frequency for CFRP Composite Satellite Antenna Reflector using Vibration Analysis

The reflector is required for high gain space antenna systems for telecommunication payloads. The carbon fibre reinforced polymer (CFRP) is extensively used in space and aero-space application due to their good specific properties over conventional metals and alloys. The frequency for a typical satellite antenna reflector is important parameter for different types of payloads.   In this paper, CFRP reflectors have been manufactured using autoclave curing process to achieve high dimensional accuracy. Four layers of CFRP prepreg have been laid at various orientation on stainless steel AISI 430 paraboloid mould. The assembly of mould and prepreg along with consolidation material has been vacuumed and cured in autoclave machine. The high volume fraction can be achieved using autoclave process in composite manufacturing. The natural frequency has been determined for reflector using FFT analyser in vibration measurement test setup. The volume fraction has been determined using scanning electron microscopic (SEM) technique. The effect of layup orientation and fiber volume fraction on natural frequency has been studied. As volume fraction increases, the natural frequency for reflector decreases gradually

Design of Linearity Improved Low Noise Amplifier using Derivative Superposition

This paper proposes different implementation of derivative superposition technique to improve the linearity of “Low Noise Amplifier” used in the receiver part of communication system. Derivative superposition is proved to be the promising technique for the improvement of linearity of LNA. This paper introduces the DS techniques in different forms by varying W, L or VGS to achieve higher IIP3. Also the results in the implementations are compared to other existing methods. The proposed scheme just not only provides high IIP3 values but it remains stable for a large variations in VGS, which is not the case with other existing techniques

Features fusion based approach for handwritten Gujarati character recognition

Handwritten character recognition is a challenging area of research. Lots of research activities in the area of character recognition are already done for Indian languages such as Hindi, Bangla, Kannada, Tamil and Telugu. Literature review on handwritten character recognition indicates that in comparison with other Indian scripts research activities on Gujarati handwritten character recognition are very less.  This paper aims to bring Gujarati character recognition in attention. Recognition of isolated Gujarati handwritten characters is proposed using three different kinds of features and their fusion. Chain code based, zone based and projection profiles based features are utilized as individual features. One of the significant contribution of proposed work is towards the generation of large and representative dataset of 88,000 handwritten Gujarati characters. Experiments are carried out on this developed dataset. Artificial Neural Network (ANN), Support Vector Machine (SVM) and Naive Bayes (NB) classifier based methods are implemented for handwritten Gujarati character recognition. Experimental results show substantial enhancement over state-of-the-art and authenticate our proposals

Productivity Improvement of Rubber Roller Mixing Process using Cause and Effect Analysis: A case study

Productivity plays an important role in any industry which enables a firm to compete in a competitive global world. Productivity provides an idea about how efficiently resources in a company are utilized. These paper addresses the application of cause and effect diagram for a mixing process of rubber compound. Rubber roll is an essential component which is used in a textile, plastic industry, rayon, paper mill and printing industry. For a product to have a good quality, the product should be made with standardize process and with consistent quality. Rubber roll and other rubber products are made by mixing process of various ingredients within specific temperature limits. The purpose of this project is to examine the rubber roll manufacturing process. The concept of work study to observe in detail is used to improve the productivity. The mixing process is taken into consideration, by taking number of trials, problem related with the mixing process are identified. Corrective action are taken to improve the effectiveness of equipment used for mixing process. Based on the observations a detailed cause and effect diagram is constructed. With the help of this study and after the necessary modifications, the goal is achieved by a proposed standardized mixing process, which in turn leads to the productivity improvement

Implementation of Low Power Rail-To-Rail Dynamic Latch Comparator With Modified Adaptive Power Control Technique

this paper presents a modified technique of power reduction for the preamplifier based dynamic latch comparator. The comparator presented in this paper is having a preamplifier, which is followed by a dynamic latch topology. The comparator is having cross coupled latch to achieve high speed and at a same time kickback effect is also reduced. A modified power control technique is presented to minimize the power consumption, having good reduction in the power compared to other technique presented in the literature. The rail to rail input range and low power comparator which can be suitably used in low-to-medium speed Analog to Digital Converters is implemented in 90nm technology using HSPICE. The simulation results have shown that the power consumption of comparator is 916.9μw at the clock frequency of 200MHz and 1V supply voltage with a delay of 80.3p

Personalized Resource Recommendations using Learning from Positive and Unlabeled Examples

This paper proposes a novel approach for recommending social resources using learning from positive and unlabeled examples. Bookmarks submitted on social bookmarking system delicious1 and artists on online music system last.fm2 are considered as social resources. The foremost feature of this problem is that there are no labeled negative resources/examples available for learning a recommender/classifier. The memory based collaborative filtering has served as the most widely used algorithm for social resource recommendation. However, its predictions are based on some ad hoc heuristic rules and its success depends on the availability of a critical mass of users. This paper proposes model based two-step techniques to learn a classifier using positive and unlabeled examples to address personalized resource recommendations. In the first step of these techniques, naïve Bayes classifier is employed to identify reliable negative resources. In the second step, to generate effective resource recommender, classification and regression tree and least square support vector machine (LS-SVM) are exercised. A direct method based on LS-SVM is also put forward to realize the recommendation task. LS-SVM is customized for learning from positive and unlabeled data. Furthermore, the impact of feature selection on our proposed techniques is also studied. Memory based collaborative filtering as well as our proposed techniques exploit usage data to generate personalized recommendations. Experimental results show that the proposed techniques outperform existing method appreciably

An Application of Taguchi Parameter Design in Predicting and Optimizing the Machining Parameters for Face Milling Operation

The quality of surface finish is always an application based and higher the surface finish higher is the manufacturing cost. This paper exhibits an application of the Taguchi parameter design approach in selecting the major influencing factors on the study of face milling operation of an automobile chassis component and optimization of the same parameters for achieving required surface finish and cycle time in a CNC face milling operation. The Taguchi’s parameter design approach is an efficient trial strategy by which different parameters that are effecting the process were analyzed. An orthogonal L9 array was utilized and experiments were carried out to optimize machining parameters based on the signal to noise ratio. At last, validation tests was also conducted to verify process capability