Tribological properties of mems materials measured on a small-scale device

Micro-electro-mechanical systems, MEMS, is a rapidly growing interdisciplinary technology within the general field of Micro-Systems Technology which deals with the design and manufacture of miniaturised machines with major dimensions at the scale of tens, to perhaps hundreds, of microns. Because they depend on the cube of a representative dimension, component masses and inertias rapidly become small as size decreases whereas surface and tribological effects, which often depend on area, become increasingly important. Although MEMS components and their areas of contact are small, tribological conditions, measured by contact pressures or acceptable wear rates, are demanding and technical and commercial success will require careful measurement and precise control of surface topography and properties. Fabrication of small numbers of MEMS devices designed to test potential material combinations can be prohibitively expensive and thus there is a need for small scale test facilities which mimic the contact conditions within a micro-machine without themselves requiring processing within a full semiconductor foundry. The talk will illustrate some initial experimental results from a small-scale experimental device which meets these requirements, examining in particular the performance of Diamond-Like-Carbon coatings on a silicon substrate. Copyright © 2005 by ASME.

Minimize frequency fluctuations of isolated power system with wind farm by using superconducting magnetic energy storage

Wind power generation as one of the most popular renewable energy applications is absorbing more and more attention all over the world. However, output power fluctuations of wind farm due to random variations of wind speed can cause network frequency and voltage flicker in power systems. The power quality consequently declines, particularly in an isolated power system such as the power system in a remote community or a small island. This paper proposes an application of superconducting magnetic energy storage (SMES) to minimize output fluctuations of an isolated power system with wind farm. The isolated power system is fed by a diesel generator and a wind generator consisting of a wind turbine and squirrel cage induction machine. The control strategy is detailed and the proposed system is evaluated by simulation in Matlab/Simulink.

Simulating intertwined design processes that have similar structures: A case study of a small company that creates made-to-order fashion products

The authors use simulation to analyse the resource-driven dependencies between concurrent processes used to create customised products in a company. Such processes are uncertain and unique according to the design changes required. However, they have similar structures. For simulation, a level of abstraction is chosen such that all possible processes are represented by the same activity network. Differences between processes are determined by the customisations that they implement. The approach is illustrated through application to a small business that creates customised fashion products. We suggest that similar techniques could be applied to study intertwined design processes in more complex domains. Copyright © 2011 Inderscience Enterprises Ltd.

Evaluating the impacts of iteration on PD processes by transforming task network models into System Dynamics models

Iteration is unavoidable in the design process and should be incorporated when planning and managing projects in order to minimize surprises and reduce schedule distortions. However, planning and managing iteration is challenging because the relationships between its causes and effects are complex. Most approaches which use mathematical models to analyze the impact of iteration on the design process focus on a relatively small number of its causes and effects. Therefore, insights derived from these analytical models may not be robust under a broader consideration of potential influencing factors. In this article, we synthesize an explanatory framework which describes the network of causes and effects of iteration identified from the literature, and introduce an analytic approach which combines a task network modeling approach with System Dynamics simulation. Our approach models the network of causes and effects of iteration alongside the process architecture which is required to analyze the impact of iteration on design process performance. We show how this allows managers to assess the impact of changes to process architecture and to management levers which influence iterative behavior, accounting for the fact that these changes can occur simultaneously and can accumulate in non-linear ways. We also discuss how the insights resulting from this analysis can be visualized for easier consumption by project participants not familiar with simulation methods. Copyright © 2010 by ASME.

Making a shallow network deep: Conversion of a boosting classifier into a decision tree by boolean optimisation

This paper presents a novel way to speed up the evaluation time of a boosting classifier. We make a shallow (flat) network deep (hierarchical) by growing a tree from decision regions of a given boosting classifier. The tree provides many short paths for speeding up while preserving the reasonably smooth decision regions of the boosting classifier for good generalisation. For converting a boosting classifier into a decision tree, we formulate a Boolean optimization problem, which has been previously studied for circuit design but limited to a small number of binary variables. In this work, a novel optimisation method is proposed for, firstly, several tens of variables i.e. weak-learners of a boosting classifier, and then any larger number of weak-learners by using a two-stage cascade. Experiments on the synthetic and face image data sets show that the obtained tree achieves a significant speed up both over a standard boosting classifier and the Fast-exit-a previously described method for speeding-up boosting classification, at the same accuracy. The proposed method as a general meta-algorithm is also useful for a boosting cascade, where it speeds up individual stage classifiers by different gains. The proposed method is further demonstrated for fast-moving object tracking and segmentation problems. © 2011 Springer Science+Business Media, LLC.