| Mr. UMA SHANKAR THUMMALAPALLI Plot No.106, Hastinapuri Colony Sainikpuri P.O, Secunderabad-500094 email id: shankar349@yahoo.com Andhra Pradesh, INDIA. Phone number: +91 (0)9985657991 Career Objective: To pursue a challenging career in an organization wherein my belief in the importance of intelligence and creativity, skill and initiative will be put to the best use. Qualification: Bachelor of Technology in Mechanical Engineering Project: TITLE: ¡§The Manufacturing of Feed Ratchet on CNC Lathe¡¨. PROJECT DESCRIPTION: In the present manufacturing scenario, the facilities should be able to handle small batch production and also ensure high productivity with good quality and reliability. The technology of CAD, CAM has evolved as the key elements right from the product concept to analysis, design, detailing, processing, manufacturing and inspection of components. It is necessary to reduce the lead-time. The new methodologies and standards are emerging in reducing the lead-times in the fabrication of a new product. The project deals with the Computer Aided Manufacturing of Feed Ratchet using Computer Numerical Control. The component, which is being manufactured using CNC Lathe, is used for the automatic feed (cross feed) in surface grinding machine. In CNC, complete machining of precision work piece is done by the capability of CNC Lathe. In this project, the configuration and modes of operations of Computer Numerical Control Systems have been studied. Thus, in order to meet the increasing demand to manufacture the complicated components of high accuracy in large quantities and to reduce production costs by reducing the production time, CNC and CIM play a prominent role. Presentations: I have actively participated in the paper presentations held every week in the college, but the topic that have earned me a certificate in the ENVISAGE 2006 held at Osmania University is ¡§Machine Vision¡¨. Brief Description: Machine Vision is the application of computer vision to manufacturing and industry. Machine Vision requires digital input/output devices and computer networks to control other manufacturing equipment such as robotic arms. Machine Vision is a subfield of engineering that encompasses computer science, optics, mechanical engineering, and industrial engineering. A typical machine vision system consist of one or more digital and analog cameras, a frame grabber, a processor, input/output hardware, lenses to focus, LED illuminators or halogen lamps, a program to process images, a synchronizing sensor for part detection and some form of actuators to sort or reject defective parts. Firstly, sync sensor determines when a part is in position to be inspected. The sensor triggers the camera to take a picture of the part and the frame grabber captures that image and it places the image in the computer memory so that it may be processed by the machine vision software. Later, following the initial simplification, the software will count, measure or identify objects, dimensions, defects and other features in the image. As a final step, the software passes or fails the part according to the programmed criteria. Machine Vision systems are programmed to perform narrowly defined tasks such as counting objects on a conveyor, reading serial numbers and searching for surface defects. This system is favorable for visual inspections that require high speed, high magnification, 24 hour operation and repeatability of measurements. The applications of Machine Vision are diverse; this system can be used in Biometrics, Large Scale Industrial Manufacturing, and Safety Systems in Industrial Environments, Control of Automated Guided Vehicles, Quality Control, Consumer Equipment Control, Visual Stock Control and Management Systems, Automated Monitoring of Sites for Safety and Security. Machine Vision systems are widely used in semiconductor fabrication since they inspect silicon wafers, processor chips, and sub components such as resistors and capacitors and hence increasing the yield of computer chips. In the automotive industry, machine vision systems are used to guide industrial robots, gauge the fit of stamped metal components and inspect the surface of the painted vehicle, weld seams, engine blocks and many other components for defects. Operating Systems: „« Windows 2000/XP/Vista, Linux/Unix. „« Ms- Office Strengths: „« Good faculties of reasoning and analyzing „« Excellent Communication & Interpersonal skills „« Good independent/team worker „« Hard working Educational Qualifications: „« Graduation: Completed Bachelor of Technology in Mechanical Engineering from CMR College of Engineering and Technology, Hyderabad, affiliated to JNTU, Hyderabad Percentage of Marks: 56.08 Year of Completion: 2007 „« Intermediate: Ratna Junior College, Hyderabad Percentage of Marks: 65.40 Year of Completion: 2003 „« School: Atomic Energy Central School, Hyderabad, affiliated to the Central Board of Secondary Education Percentage of Marks: 53.2 Year of Completion: 2000 | 
