Manufacturing Technology Today

Manufacturing Technology Today, Manufacturing Technology Abstracts, Vol. 14, No. 4, September 2015, Bangalore, India

Pattern Recognition

A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Advanced Automation for Space Missions

The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Development of virtual cities models during emergencies

L'abstract è presente nell'allegato / the abstract is in the attachmen

1996 Laboratory directed research and development annual report

This report summarizes progress from the Laboratory Directed Research and Development (LDRD) program during fiscal year 1996. In addition to a programmatic and financial overview, the report includes progress reports from 259 individual R&D projects in seventeen categories. The general areas of research include: engineered processes and materials; computational and information sciences; microelectronics and photonics; engineering sciences; pulsed power; advanced manufacturing technologies; biomedical engineering; energy and environmental science and technology; advanced information technologies; counterproliferation; advanced transportation; national security technology; electronics technologies; idea exploration and exploitation; production; and science at the interfaces - engineering with atoms

Combining evolutionary algorithms and agent-based simulation for the development of urbanisation policies

Urban-planning authorities continually face the problem of optimising the allocation of green space over time in developing urban environments. To help in these decision-making processes, this thesis provides an empirical study of using evolutionary approaches to solve sequential decision making problems under uncertainty in stochastic environments. To achieve this goal, this work is underpinned by developing a theoretical framework based on the economic model of Alonso and the associated methodology for modelling spatial and temporal urban growth, in order to better understand the complexity inherent in this kind of system and to generate and improve relevant knowledge for the urban planning community. The model was hybridised with cellular automata and agent-based model and extended to encompass green space planning based on urban cost and satisfaction. Monte Carlo sampling techniques and the use of the urban model as a surrogate tool were the two main elements investigated and applied to overcome the noise and uncertainty derived from dealing with future trends and expectations. Once the evolutionary algorithms were equipped with these mechanisms, the problem under consideration was defined and characterised as a type of adaptive submodular. Afterwards, the performance of a non-adaptive evolutionary approach with a random search and a very smart greedy algorithm was compared and in which way the complexity that is linked with the configuration of the problem modifies the performance of both algorithms was analysed. Later on, the application of very distinct frameworks incorporating evolutionary algorithm approaches for this problem was explored: (i) an ‘offline’ approach, in which a candidate solution encodes a complete set of decisions, which is then evaluated by full simulation, and (ii) an ‘online’ approach which involves a sequential series of optimizations, each making only a single decision, and starting its simulations from the endpoint of the previous run

Design and testing of a position adaptation system for KUKA robots using photoelectric sensors

This thesis presents the development and analysis of a position monitoring and adaptation system to be used in conjunction with a KUKA KR16-2 articulated robot using components readily available in most manufacturing settings. This system could be beneficial in the manufacturing sector in areas such as polymer welding and spray painting. In the former it could be used to maintain an effective distance between a welding end effector laying molten plastic and the surface area of the parts being welded, or in the case of the latter the system would be useful in painting objects of unknown shape or objects with unknown variations in the surface level. In the case of spray painting if you spray to close to an object you will get an inconsistent amount of paint applied to an area. This system would maintain the programmed distance between the robot system and target object. Typically, systems that achieve this level of control rely on expensive sensors such as force torque sensors. This research proposes to take the first step in trying to address the technical problems by introducing a novel way of adapting to a target surface deformation using comparably low cost photoelectric diffuse sensors. The key outcomes of this thesis can be found in the form of a software package to interface the photo-electric sensors to the KUKA robot system. This system is operated by a custom-built algorithm which is capable of dynamically calculating robot movements based off the sensor input. Additionally, an optimum system setup is developed with different configurations of sensor mounting and speeds of robot operation discussed and tested. The viability of the photo-electric diffuses sensors used in this application is also considered with further works suggested. Finally, a secondary application is developed for recording and analysing KUKA robot movements for use in other research activities