Electric routing and concurrent flow cutting

We investigate an oblivious routing scheme, amenable to distributed computation and resilient to graph changes, based on electrical flow. Our main technical contribution is a new rounding method which we use to obtain a bound on the L1->L1 operator norm of the inverse graph Laplacian. We show how this norm reflects both latency and congestion of electric routing.Comment: 21 pages, 0 figures. To be published in Springer LNCS Book No. 5878, Proceedings of The 20th International Symposium on Algorithms and Computation (ISAAC'09

Manufacturing Mechatronics Using Thermal Spray Shape Deposition

A new technology for manufacturing mechatronics is described. The technique is based on recursive masking and deposition of thermally sprayed materials. Using these methods, mechanical structures can be created that embed and interconnect electronic components. This results in highly integrated mechatronic devices. A simple, electromechanical artifact was designed and produced to assess the feasibility of these techniques. The details and limitations of this project will be discussed. Areas of future research are identified which are aimed at realizing the full potential of this emerging manufacturing process.Mechanical Engineerin

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution

Electric power is the main energy source for a modern society. Good management of electric power cycle is essential for a sustainable society. The electric power cycle is composed of Generation, Transmission, Distribution, and Consumption. Smart Grid (SG) is a system that integrated traditional grids with Information and Communication Technology (ICT). In addition, SG has the ability to integrate electrical power supply from both to main power substation and Distributed Generation (DG), which compensates for the power demand during peak times. However, SG still has a similar problem to the original grid in terms of active power loss, from electric current injecting through the transmission line. This paper solves the active power loss problem by feeder routing using the Adjusting Dijkstra's Cost Method, follow by deciding the allocation position and sizing of DG by the use of Evolutionary Computing, namely Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO). The experiments evaluate the performance of the algorithm using power flow analysis, Backward / Forward Sweep Method, on the IEEE 33 bus system. From the experimental results, PSO provides the best performance. The overall active power loss in the cases of 3 DGs was reduced from 202.67 to 52.29 kW, representing a reduction of 74.20%

Resource selection and route generation in discrete manufacturing environment

When put to various sources, the question of which sequence of operations and machines is best for producing a particular component will often receive a wide range of answers. When the factors of optimum cutting conditions, minimum time, minimum cost, and uniform equipment utilisation are added to the equation, the range of answers becomes even more extensive. Many of these answers will be 'correct', however only one can be the best or optimum solution. When a process planner chooses a route and the accompanying machining conditions for a job, he will often rely on his experience to make the choice. Clearly, a manual generation of routes does not take all the important considerations into account. The planner may not be aware of all the factors and routes available to him. A large workshop might have hundreds of possible routes, even if he did know it all', he will never be able to go through all the routes and calculate accurately which is the most suitable for each process - to do this, something faster is required. This thesis describes the design and implementation of an Intelligent Route Generator. The aim is to provide the planner with accurate calculations of all possible production routes m a factory. This will lead up to the selection of an optimum solution according to minimum cost and time. The ultimate goal will be the generation of fast decisions based on expert information. Background knowledge of machining processes and machine tools was initially required, followed by an identification of the role of the knowledge base and the database within the system. An expert system builder. Crystal, and a database software package, DBase III Plus, were chosen for the project. Recommendations for possible expansion of and improvements to the expert system have been suggested for future development

Aggregate process planning and manufacturing assessment for concurrent engineering

The introduction of concurrent engineering has led to a need to perform product development tasks with reduced information detail. Decisions taken during the early design stages will have the greatest influence on the cost of manufacture. The manufacturing requirements for alternative design options should therefore be considered at this time. Existing tools for product manufacture assessment are either too detailed, requiring the results of detailed design information, or too abstract, unable to consider small changes in design configuration. There is a need for an intermediate level of assessment which will make use of additional design detail where available, whilst allowing assessment of early designs. This thesis develops the concept of aggregate process planning as a methodology for supporting concurrent engineering. A methodology for performing aggregate process planning of early product designs is presented. Process and resources alternatives are identified for each feature of the component and production plans are generated from these options. Alternative production plans are assessed in terms of cost, quality and production time. A computer based system (CESS, Concurrent Engineering Support System) has been developed to implement the proposed methodology. The system employs object oriented modelling techniques to represent designs, manufacturing resources and process planning knowledge. A product model suitable for the representation of component designs at varying levels of detail is presented. An aggregate process planning functionality has been developed to allow the generation of sets of alternative plans for a component in a given factory. Manufacturing cost is calculated from the cost of processing, set-ups, transport, material and quality. Processing times are calculated using process specific methods which are based on standard cutting data. Process quality cost is estimated from a statistical analysis of historical SPC data stored for similar operations performed in the factory, where available. The aggregate process planning functionality has been tested with example component designs drawn from industry