A method for evaluating lean assembly process at design stage

Lean product design has the potential to reduce the overall product development time and cost and can improve the quality of a product. However, it has been found that no or little work has been carried out to provide an integrated framework of "lean design" and to quantitatively evaluate the effectiveness of lean practices/principles in product development process. This research proposed an integrated framework for lean design process and developed a dynamic decision making tool based on Methods Time Measurement (MTM) approach for assessing the impact of lean design on the assembly process. The proposed integrated lean framework demonstrates the lean processes to be followed in the product design and assembly process in order to achieve overall leanness. The decision tool consists of a central database, the lean design guidelines, and MTM analysis. Microsoft Access and C# are utilized to develop the user interface to use the MTM analysis as decision making tool. MTM based dynamic tool is capable of estimating the assembly time, costs of parts and labour of various alternatives of a design and hence is able to achieve optimum design. A case study is conducted to test and validate the functionality of the MTM Analysis as well as to verify the lean guidelines proposed for product development.

Multi-objective optimisation of bijective s-boxes

In this paper we investigate the heuristic construction of bijective s-boxes that satisfy a wide range of cryptographic criteria including algebraic complexity, high nonlinearity, low autocorrelation and have none of the known weaknesses including linear structures, fixed points or linear redundancy. We demonstrate that the power mappings can be evolved (by iterated mutation operators alone) to generate bijective s-boxes with the best known tradeoffs among the considered criteria. The s-boxes found are suitable for use directly in modern encryption algorithms.

Aircraft emission reduction through multi-disciplinary flight path optimisation

There is worldwide interest in reducing aircraft emissions. The difficulty of reducing emissions including water vapour, carbon dioxide (CO2) and oxides of nitrogen (NOx) is mainly due from the fact that a commercial aircraft is usually designed for a particular optimal cruise altitude but may be requested or required to operate and deviate at different altitude and speeds to archive a desired or commanded flight plan, resulting in increased emissions. This is a multi- disciplinary problem with multiple trade-offs such as optimising engine efficiency, minimising fuel burnt, minimise emissions while maintaining aircraft separation and air safety. This project presents the coupling of an advanced optimisation technique with mathematical models and algorithms for aircraft emission reduction through flight optimisation. Numerical results show that the method is able to capture a set of useful trade-offs between aircraft range and NOx, and mission fuel consumption and NOx. In addition, alternative cruise operating conditions including Mach and altitude that produce minimum NOx and CO2 (minimum mission fuel weight) are suggested.

An FPGA-based approach to multi-objective evolutionary algorithm for multi-disciplinary design optimisation

This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.

Coupling hybrid-game strategies with particle swarm optimisation for multi-objective high lift systems design optimisation

This paper investigates the High Lift System (HLS) application of complex aerodynamic design problem using Particle Swarm Optimisation (PSO) coupled to Game strategies. Two types of optimization methods are used; the first method is a standard PSO based on Pareto dominance and the second method hybridises PSO with a well-known Nash Game strategies named Hybrid-PSO. These optimization techniques are coupled to a pre/post processor GiD providing unstructured meshes during the optimisation procedure and a transonic analysis software PUMI. The computational efficiency and quality design obtained by PSO and Hybrid-PSO are compared. The numerical results for the multi-objective HLS design optimisation clearly shows the benefits of hybridising a PSO with the Nash game and makes promising the above methodology for solving other more complex multi-physics optimisation problems in Aeronautics.

Obligatory dangerousness criteria in the involuntary commitment and treatment provisions of Australian mental health legislation

Abstract Objective Involuntary commitment and treatment (IC&T) of people affected by mental illness may have reference to considerations of dangerousness and/or need for care. While attempts have been made to classify mental health legislation according to whether IC&T has obligatory dangerousness criteria, there is no standardised procedure for making classification decisions. The aim of this study was to develop and trial a classification procedure and apply it to Australia's mental health legislation. Method We developed benchmarks for ‘need for care’ and ‘dangerousness’ and applied these benchmarks to classify the mental health legislation of Australia's 8 states and territories. Our focus was on civil commitment legislation rather than criminal commitment legislation. Results One state changed its legislation during the course of the study resulting in two classificatory exercises. In our initial classification, we were able to classify IC&T provisions in legislation from 6 of the 8 jurisdictions as being based on either ‘need for care’ or ‘dangerousness’. Two jurisdictions used a terminology that was outside the established benchmarks. In our second classification, we were also able to successfully classify IC&T provisions in 6 of the 8 jurisdictions. Of the 6 Acts that could be classified, all based IC&T on ‘need for care’ and none contained mandatory ‘dangerousness’ criteria. Conclusions The classification system developed for this study provided a transparent and probably reliable means of classifying 75% of Australia's mental health legislation. The inherent ambiguity of the terminology used in two jurisdictions means that further development of classification may not be possible until the meaning of the terms used has been addressed in case law. With respect to the 6 jurisdictions for which classification was possible, the findings suggest that Australia's mental health legislation relies on ‘need for care’ and not on ‘dangerousness’ as the guiding principle for IC&T. Keywords: Involuntary commitment; Mental health legislation; Dangerousness; Australia

Practical improvements to simultaneous computation of multi-view geometry and radial lens distortion

This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

Career decision making among gifted students : the mediation of teachers

There is international concern about falling enrollments in higher education, particularly the sciences, by gifted students. In this mixed method study, the top performing 200 students (approximately 1%) within a particular education jurisdiction at the beginning of their first year at university were surveyed and 20 interviewed about their school experiences using a biographical interpretive design. This study focussed on identifying those characteristics of teachers which supported students’ interests. Participants identified seven characteristics of teachers that students identified as supportive of their potential career pathways. These included connecting pedagogical practices with student interests, being passionate about their subject matter, having good content knowledge, making learning experiences relevant, setting high expectations of students, being a good explainer of complex ideas, and being a good classroom manager. This study extends our knowledge of how teachers influence gifted students and has implications for both pre-service and in-service teacher education and career counselling.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Strategic project evaluation for open pit mining ventures using real options and allied econometric techniques

Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

A Delphi study on the critical sustainability criteria and indicators for Australian road infrastructure projects

With increasing media exposure and evidence of environmental impacts, it is increasingly recognized that incorporating sustainability principles in construction works is both crucial and beneficial. However a recent survey reveals that among stakeholders of infrastructure projects such as roads, there is no common understanding on what constitutes sustainability in real-life projects. Sustainability has been interpreted widely and differently and as a result, sustainability outcomes are not tangible at the project level or often neglected. Under such conditions, policies and strategies on sustainability remain largely ideological and cannot be sufficiently reflected in the actual project delivery. The major difficulty of this sustainability pursuit lies in the lack of consensus among the experts on sustainability criteria and indicators. To move ahead, these criteria and indicators are to be agreed upon. This paper reviews the sustainable infrastructure development, its criteria and indicators, focusing on road infrastructure context. It goes on to introduce a Delphi study, an integral part of a QUT research, aimed at identifying critical sustainability criteria and indicators for Australian road infrastructure projects. It paves the way for further identification of solutions for each critical indicator at a subsequent stage. The criteria, indicators and solutions will be encapsulated into a decision making framework for the enhancement of sustainability deliverables. By doing so, the research will promote more integrated thinking of and consistent approaches to the sustainability agenda in road and highway infrastructure projects in Australia.

A semi-local method for iterative depth-map refinement

We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.

Project management governance : a situational approach

The purpose of this paper is to show how project management governance is addressed through the use of a specific meta-method. Governance is defined here on two criteria: accountability and performance. Accountability is promoted through transparency and performance is promoted by responsive and responsible decision-making. According to a systemic perspective, transparency and decision-making involve having information, tacit or explicit knowledge, as well as understanding of the context, the different parameters and variables, their interaction and conditions of change. Although this method of methods was built according a heuristic process involving 25 years of various researches and consulting activities, it seems appropriate to draw its foundations. I clarify first my epistemological position and the notion of project and project management, as Art and Science. This lead me to define a "Be" / "Have" posture to this regards. Then, the main theoretical roots of MAP Method are exposed: Boisot' s Social Learning Cycle, Praxeology and Theory of Convention. Then we introduced the main characteristics of the method and the 17 methods and tools constituting MAP "tool box", thus with regard to the project management governance perspective. Finally, I discuss the integration of two managerial modes (operational and project modes) and the consequence in term of governance in a specific socio-techno-economic project/context ecosystem.

Updating and verification for multi-scale finite element model of structure behavior

The method on concurrent multi-scale model of structural behavior (CMSM-of-SB) for the purpose of structural health monitoring including model updating and validating has been studied. The detailed process of model updating and validating is discussed in terms of reduced scale specimen of the steel box girder in longitudinal stiffening truss of a long span bridge. Firstly, some influence factors affecting the accuracy of the CMSM-of-SB including the boundary restraint regidity, the geometry and material parameters on the toe of the weld and its neighbor are analyzed using sensitivity method. Then, sensitivity-based model updating technology is adopted to update the developed CMSM-of-SB and model verification is carried out through calculating and comparing stresses on different locations under various loading from dynamic characteristic and static response. It can be concluded that the CMSM-of-SB based on the substructure method is valid.