Search results for: Vasu Velagapudi

Authors: M. Sandeep Kumar, Vasu Velagapudi, A. Venugopal

Abstract:

When machining is carried out on a workpiece, residual stresses are induced in the workpiece due to nonuniform thermal and mechanical loads. These stresses play a vital role in the surface integrity of the final product or the output. Inconel 718 is commonly used in critical structural components of aircraft engines due to its properties at high temperatures. Therefore it is important to keep down the stresses induced due to machining. This can be achieved through proper lubricating conditions. In this work, experiments were carried out to check the influence of the developed nanofluid as cutting fluids on residual stresses developed during the course of machining. The results of MQL/Nanofluids were compared with MQL/Vegetable oil and dry machining lubricating condition. Results indicate the reduction in residual stress with the use of MQL/Nanofluid.

Keywords: nanofluids, MQL, residual stress, Inconel-718

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Authors: Vasu Velagapudi, G. Suresh

Abstract:

PTFE/HNTs nanocomposites are fabricated with 4%, 6%, and 8% by weight fraction, and the optimization study of wear parameters are performed using response surface methodology (RSM). The experiments are carried out on a pin on disc (POD) wear tester under different operating parameters planned according to Taguchi L27 orthogonal array. The input factors considered are wt% HNTs addition, sliding velocity, load, and distance with three levels for each factor. From ANOVA: The factors load, speed and distance and their interactions have a significant effect on COF. Also for SWR, composition factor and interaction of load and speed are observed to be significant ( < 0.05) Optimum input parameters corresponding to desirability 1 are found to be: COF (0.11) and SWR (17.5)×10⁻⁶ (mm3/N-m) at 6.34 wt% of composition, 5N of load, 2 km of distance and 1 m/sec of velocity.

Keywords: PTFE/HNT, nanocomposites, response surface methodology (RSM), specific wear rate

Procedia PDF Downloads 396

Authors: Azhar Alhasawi, Vasu D. Appanna

Abstract:

Chitin, the second most abundant bio-polymer in nature after cellulose, composed of β (1→4) linked N-acetylglucosamine (GlcNAc), is a major structural component in the cell walls of fungi and the shells of crustaceans. Chitin and its derivatives are gaining importance of economic value due to its biological activity and its industrial and biomedical applications. There are several methods to hydrolyze chitin to NAG, but they are typically expensive and environmentally unfriendly. Chitinase which catalyzes the breakdown of chitin to NAG has received much attention owing to its various applications in biotechnology. The presented research examines the ability of the versatile soil microbe, Pseudomonas fluorescens grown in chitin medium to produce chitinase and a variety of value-added products under abiotic stress. We have found that with high pH, Pseudomonas fluorescens enable to metabolize chitin more than with neutral pH and the overexpression of chitinase was also increased. P-dimethylaminobenzaldehyde (DMAB) assay for NAG production will be monitored and a combination of sodium dodecyl polyacrylamide gels will be used to monitor the proteomic and metabolomic changes as a result of the abiotic stress. The bioreactor of chitinase will also be utilized.

Keywords: Pseudomonas fluorescens, chitin, DMAB, chitinase

Procedia PDF Downloads 355

Authors: Ambuj Kumar Gautam, V. Vasu

Abstract:

This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

Procedia PDF Downloads 292

Authors: A. P. Puvanasvaran, Suresh A. L. Vasu, N. Norazlin

Abstract:

The Lean Environmental Management Integration System (LEMIS) framework development is integration between lean core element and ISO 14001. The curiosity on the relationship between continuous improvement and sustainability of lean implementation has influenced this study toward LEMIS. Characteristic of ISO 14001 standard clauses and core elements of lean principles are explored from past studies and literature reviews. Survey was carried out on ISO 14001 certified companies to examine continual improvement by implementing the ISO 14001 standard. The study found that there is a significant and positive relationship between Lean Principles: value, value stream, flow, pull and perfection with the ISO 14001 requirements. LEMIS is significant to support the continuous improvement and sustainability. The integration system can be implemented to any manufacturing company. It gives awareness on the importance on why organizations need to sustain its Environmental management system. At the meanwhile, the lean principle can be adapted in order to streamline daily activities of the company. Throughout the study, it had proven that there is no sacrifice or trade-off between lean principles with ISO 14001 requirements. The framework developed in the study can be further simplified in the future, especially the method of crossing each sub requirements of ISO 14001 standard with the core elements of Lean principles in this study.

Keywords: LEMIS, ISO 14001, integration, framework

Procedia PDF Downloads 406

Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

Abstract:

The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 165