Research and development of a reconfigurable robotic end-effector for machining and part handling.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF

NASA/USRA University Advanced Design Program Fourth Annual Summer Conference

The study topics cover a broad range of potential space and aeronautics projects which could be undertaken during a 20-30 year period beginning with the Space Station Initial Operating Configuration scheduled for the mid 1990's. Both manned and unmanned endeavors are embraced, and the systems approach to the design problem is emphasized. The student teams pursue the chosen problem during their senior year in a one or two semester capstone design course and submit a comprehensive written report at the conclusion of the project. Finally, student representatives from each of the universities summarize their work in oral presentations at the annual Summer Conference, held at one of the NASA centers and attended by the university faculty, NASA and USRA personnel, and aerospace industry representatives

Friction Force Microscopy of Deep Drawing Made Surfaces

Aim of this paper is to contribute to micro-tribology understanding and friction in micro-scale interpretation in case of metal beverage production, particularly the deep drawing process of cans. In order to bridging the gap between engineering and trial-and-error principles, an experimental AFM-based micro-tribological approach is adopted. For that purpose, the can’s surfaces are imaged with atomic force microscopy (AFM) and the frictional force signal is measured with frictional force microscopy (FFM). In both techniques, the sample surface is scanned with a stylus attached to a cantilever. Vertical motion of the cantilever is recorded in AFM and horizontal motion is recorded in FFM. The presented work evaluates friction over a micro-scale on various samples gathered from cylindrical, bottom and round parts of cans, made of same the material but with different deep drawing process parameters. The main idea is to link the experimental observation with the manufacturing process. Results presented here can advance the knowledge in order to comprehend the tribological phenomena at the contact scales, too small for conventional tribology

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

Research and Technology 2004

This report selectively summarizes NASA Glenn Research Center's research and technology accomplishments for fiscal year 2004. It comprises 133 short articles submitted by the staff scientists and engineers. The report is organized into three major sections: Programs and Projects, Research and Technology, and Engineering and Technical Services. A table of contents and an author index have been developed to assist readers in finding articles of special interest. This report is not intended to be a comprehensive summary of all the research and technology work done over the past fiscal year. Most of the work is reported in Glenn-published technical reports, journal articles, and presentations prepared by Glenn staff and contractors. In addition, university grants have enabled faculty members and graduate students to engage in sponsored research that is reported at technical meetings or in journal articles. For each article in this report, a Glenn contact person has been identified, and where possible, a reference document is listed so that additional information can be easily obtained. The diversity of topics attests to the breadth of research and technology being pursued and to the skill mix of the staff that makes it possible. For more information, visit Glenn's Web site at http://www.nasa.gov/glenn/. This document is available online (http://www.grc.nasa.gov/WWW/RT/). For publicly available reports, visit the Glenn Technical Report Server (http://gltrs.grc.nasa.gov)

Of yeast and men : insights into evolution and human health from 1 billion years of divergence

Life on the planet is incredibly diverse and it is often easy to compare and contrast the many features that distinguish any two pairs of species from each other. Despite this diversity, all organisms on Earth share a common origin. This shared ancestry establishes conservation at the core of biology. The concept of conservation (or what’s equivalent) across species organizes biology and stems from the natural selection of favorable traits in organisms. Evolutionary conservation extends even to the genetic and molecular level with genes, proteins, and the networks they constitute also sharing common ancestry. This property enables biologists to study conserved genes (orthologs) in simpler model organisms and relate them to their corresponding human equivalents. Despite this, it is largely unclear the extents to which orthologs between species are functionally compatible. The dissertation aims to directly address this question via cross-species gene swaps. By systematically humanizing yeast genes, this dissertation provides insights into how orthologous genes between species functionally diverge and evolve over vast timescales. In chapter one, I present conservation as a powerful organizing principle in biology and the roles orthologous biological systems play in connecting genotype and phenotype. In chapters two and three, I describe efforts to apply humanized yeast as a platform to study functional divergence in orthologs constituting expanded gene families and examine the trends that underlie them. In chapter four, I describe the synthesis of observations from multiple research threads including humanized yeast, model organisms, evolutionary conservation of biological systems, and global signatures of pesticide resistance to uncover a novel class of antifungals all capable of functioning as vascular disrupting agents. Finally, in chapter five, I discuss the future of cross-species gene swaps, humanized yeast, and their utility to human health and diseaseBiochemistr

Microfluidics for Biosensing

There are 12 papers published with 8 research articles, 3 review articles and 1 perspective. The topics cover: Biomedical microfluidics Lab-on-a-chip Miniaturized systems for chemistry and life science (MicroTAS) Biosensor development and characteristics Imaging and other detection technologies Imaging and signal processing Point-of-care testing microdevices Food and water quality testing and control We hope this collection could promote the development of microfluidics and point-of-care testing (POCT) devices for biosensing