A tool for assessing reconfigurability of distributed manufacturing systems

In recent years, a large number of approaches to developing distributed manufacturing systems has been proposed. One of the principles reasons for these development has been to enhance the reconfigurability of a manufacturing operation; allowing it to readily adapt to changes over time. However, to date, there has only been a limited assessment of the resulting reconfigurability properties and hence it remains inconclusive as to whether a distributed manufacturing system design approach does in fact improve reconfigurability. This paper represents part of a study which investigates this issue. It proposes an assessment tool - the so called "Design Structure Matrix" as a means of assessing the modularity of elements in a manufacturing system. (Modularity has been shown to be a key characteristic of a reconfigurable manufacturing system.) The use of the Design Structure Matrix is illustrated in assessing a robot assembly cell designed on distributed manufacturing system principles. Copyright © 2006 IFAC.

Modular risk modeling and management of water infrastructure disaster incidents

Water supply and wastewater control are critical elements of society's infrastructure. The objective of this study will be to provide a generic risk assessment tool to provide municipalities and the nation as a whole with a quantifiable assessment of their vulnerability to water infrastructure threats. The approach will prioritize countermeasures and identify where research and development is required to further minimize risk. This paper outlines the current context, primary concerns and state-of-the art in critical infrastructure risk management for the water sector and proposes a novel approach to resolve existing questions in the field. The proposed approach is based on a modular framework that derives a quantitative risk index for varied domains of interest. The approach methodology is scaleable and based on formal definitions of event probability and severity. The framework is equally applicable to natural and human-induced hazard types and can be used for analysis of compound risk events.

Cortical thickness estimation of the proximal femur from multi-view Dual-Energy X-ray Absorptiometry (DXA)

Hip fracture is the leading cause of acute orthopaedic hospital admission amongst the elderly, with around a third of patients not surviving one year post-fracture. Although various preventative therapies are available, patient selection is difficult. The current state-of-the-art risk assessment tool (FRAX) ignores focal structural defects, such as cortical bone thinning, a critical component in characterizing hip fragility. Cortical thickness can be measured using CT, but this is expensive and involves a significant radiation dose. Instead, Dual-Energy X-ray Absorptiometry (DXA) is currently the preferred imaging modality for assessing hip fracture risk and is used routinely in clinical practice. Our ambition is to develop a tool to measure cortical thickness using multi-view DXA instead of CT. In this initial study, we work with digitally reconstructed radiographs (DRRs) derived from CT data as a surrogate for DXA scans: this enables us to compare directly the thickness estimates with the gold standard CT results. Our approach involves a model-based femoral shape reconstruction followed by a data-driven algorithm to extract numerous cortical thickness point estimates. In a series of experiments on the shaft and trochanteric regions of 48 proximal femurs, we validated our algorithm and established its performance limits using 20 views in the range 0°-171°: estimation errors were 0:19 ± 0:53mm (mean +/- one standard deviation). In a more clinically viable protocol using four views in the range 0°-51°, where no other bony structures obstruct the projection of the femur, measurement errors were -0:07 ± 0:79 mm. © 2013 SPIE.

Tailored sustainability assessment for urban masterplanning

Tailored sustainability assessment represents one approach to addressing sustainability issues on large-scale urban projects with varying geographical, social and political constraints and diverse incentives among stakeholders. This paper examines the value and limitations of this approach. Three case studies of tailored systems developed by the authors for three unique masterplanning projects are discussed in terms of: contextual sustainability drivers; nature and evolution of systems developed; outcomes of implementation; and overall value delivered. Analysis Leads to conclusions on the key features of effective tailored assessment, the value of tailored sustainability assessment from various perspectives (including client, designer, end-users and the environment), and the limitations of tailored assessment as a tool for comparative analysis between projects. Although systems considered here are specific to individual projects and developed commercially, the challenges and lessons learned are relevant to a range of sustainability assessment approaches developed under different conditions.

Development of a tool for rapidly assessing the implementation difficulty and emissions benefits of innovations

Consumer goods manufacturers aiming to reduce the environmental impact associated with their products commonly pursue incremental change strategies, but more radical approaches may be required if we are to address the challenges of sustainable consumption. One strategy to realize step change reductions is to prepare a portfolio of innovations providing different levels of impact reduction in exchange for different levels of organizational resource commitment. In this research a tool is developed to support this strategy, starting with the assumption that through brainstorming or other eco-innovation approaches, a long-list of candidate innovations has been created. The tool assesses the potential greenhouse gas benefit of an innovative option against the difficulty of its implementation. A simple greenhouse gas benefit assessment method based on streamlined LCA was used to analyze impact reduction potential, and a novel measure of implementation difficulty was developed. The predictions of implementation difficulty were compared against expert opinion, and showed similar results indicating the measure can be used sensibly to predict implementation difficulty. The assessment of the environmental gain versus implementation difficulty is visualized in a matrix, showing the trade-offs of several options. The tool is deliberately simple with scalar measures of CO 2 emissions benefits and implementation difficulty so tool users must remain aware of other potential environmental burdens besides greenhouse gases (e.g. water, waste). In addition, although relative life cycle emissions benefits of an option may be low, the absolute impact of an option can be high and there may be other co-benefits, which could justify higher levels of implementation difficulty. Different types of consumer products (e.g. household, personal care, foods) have been evaluated using the tool. Initial trials of the tool within Unilever demonstrate that the tool facilitates rapid evaluation of low-carbon innovations. © 2011 Elsevier Ltd. All rights reserved.

Selecting a multi-agent system development tool for industrial applications: A case study of self-serving aircraft assets

Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.

A whole-life value based assessment and optimisation model for high-performance glazed facades'

Façade design is a complex and multi-disciplinary process. One major barrier to devising optimal façade solutions is the lack of a systematic way of evaluating the true social, economic and environmental impacts of a design. Another barrier is the lack of automated design aids to assist decision-making. In this paper, we present our on-going study in developing a whole-life value based multi-objective optimisation model for high-performance façades. The principal outcome of this paper is a multi-objective optimisation model for early-stage façade design. The optimisation technique coupled with other 3rd party software and/or specially developed scripts provide façade designers with an integrated design tool of wide applicability.

An analysis of factors improving technology roadmap credibility: A communications theory assessment of roadmapping processes

In recent years, many industrial firms have been able to use roadmapping as an effective process methodology for projecting future technology and for coordinating technology planning and strategy. Firms potentially realize a number of benefits in deploying technology roadmapping (TRM) processes. Roadmaps provide information identifying which new technologies will meet firms' future product demands, allowing companies to leverage R&D investments through choosing appropriately out of a range of alternative technologies. Moreover, the roadmapping process serves an important communication tool helping to bring about consensus among roadmap developers, as well as between participants brought in during the development process, who may communicate their understanding of shared corporate goals through the roadmap. However, there are few conceptual accounts or case studies have made the argument that roadmapping processes may be used effectively as communication tools. This paper, therefore, seeks to elaborate a theoretical foundation for identifying the factors that must be considered in setting up a roadmap and for analyzing the effect of these factors on technology roadmap credibility as perceived by its users. Based on the survey results of 120 different R&D units, this empirical study found that firms need to explore further how they can enable frequent interactions between the TRM development team and TRM participants. A high level of interaction will improve the credibility of a TRM, with communication channels selected by the organization also positively affecting TRM credibility. © 2011 Elsevier Inc.

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.

A classification of data quality assessment methods

Data quality (DQ) assessment can be significantly enhanced with the use of the right DQ assessment methods, which provide automated solutions to assess DQ. The range of DQ assessment methods is very broad: from data profiling and semantic profiling to data matching and data validation. This paper gives an overview of current methods for DQ assessment and classifies the DQ assessment methods into an existing taxonomy of DQ problems. Specific examples of the placement of each DQ method in the taxonomy are provided and illustrate why the method is relevant to the particular taxonomy position. The gaps in the taxonomy, where no current DQ methods exist, show where new methods are required and can guide future research and DQ tool development.