Design of a model-generated repository as a service for USDL

SAP and its research partners have been developing a lan- guage for describing details of Services from various view- points called the Unified Service Description Language (USDL). At the time of writing, version 3.0 describes technical implementation aspects of services, as well as stakeholders, pricing, lifecycle, and availability. Work is also underway to address other business and legal aspects of services. This language is designed to be used in service portfolio management, with a repository of service descriptions being available to various stakeholders in an organisation to allow for service prioritisation, development, deployment and lifecycle management. The structure of the USDL metadata is specified using an object-oriented metamodel that conforms to UML, MOF and EMF Ecore. As such it is amenable to code gener-ation for implementations of repositories that store service description instances. Although Web services toolkits can be used to make these programming language objects available as a set of Web services, the practicalities of writing dis- tributed clients against over one hundred class definitions, containing several hundred attributes, will make for very large WSDL interfaces and highly inefficient “chatty” implementations. This paper gives the high-level design for a completely model-generated repository for any version of USDL (or any other data-only metamodel), which uses the Eclipse Modelling Framework’s Java code generation, along with several open source plugins to create a robust, transactional repository running in a Java application with a relational datastore. However, the repository exposes a generated WSDL interface at a coarse granularity, suitable for distributed client code and user-interface creation. It uses heuristics to drive code generation to bridge between the Web service and EMF granularities.

On location : the imagined private interior in public life

This paper reveals the interior landscapes of selected contemporary Australian films, such as The Caterpillar Wish and Bad Boy Bubby, to develop a number of thematic influences on the manner in which domestic and private lives are constructed through filmic imagination. The research uncovers the conditions that contribute to particular scenographic representations of the humble interiors that act as both backdrop and performer to subtle and often troubled narratives. Such readings are informed by the theoretical works of writer Gertrude Stein, among others, who explore the relationships between the scenographic third dimension and the fourth dimensional performance in the representation of narrative space. A further theoretical thread lies in Giuliana Bruno’s work on the tension between private and public filmic space, which is explored through the public outing of intensely private spaces generated through narratives framed by the specificities of found interiors. Beyond the interrogation of qualities of imagined filmic space is the condition whereby locations, once transformed by the event of movie making are consequently forever revised. These altered conditions subsequently reinvest the lives of those who return to the location with layered narratives of occupation. Situationally, the now reconverted interior performs as contributor to subsequent private inhabitation, even if only as imagined space. The possibility here is that the qualities of the original may be superimposed and recontextualised to invest post-produced interiors with the qualities of the other space as imagined. This reading of film space explores new theoretical design scenarios for imagined and everyday interior landscapes.

Bushfire sustainability : Strategies for reconciling bushfire and biodiversity with daily life

This exhibition and catalogue provides a visual record of student work exhibited at the Australian Institute of Architects offices in Brisbane from November 15 to 29, 2010. The exhibition features the final design outcomes of the inaugural Bushfire Sustainability unit conducted at QUT in semester two, 2010. The core objective of this unit was to develop our students’ skills in collaborative practice in design, research and presentation. The theme of ‘bushfire sustainability’ was chosen because living sustainably in bushfire prone landscapes presents a number of problems, the nature of which might only be resolved via multidisciplinary collaboration among the design disciplines. The students involved represent the disciplines of Interior Design, Landscape Architecture, Industrial Design, Architecture and Sustainability – all from within the School of Design at QUT. 55 students, mostly in their third year of study, worked in teams of five (one from each discipline) to design one of a number of homes in highly bushfire prone sites in either Western Australia or SE Queensland. This year level and the interdisciplinary mix are perhaps the best placed to resolve these problems: being unrestrained from the burdens of professional practice and technical overload they retain the potential for innovative, lateral thinking across the range of spatial scales and philosophical perspectives associated with inhabitation of bushfire prone landscapes. It is envisaged that, through the ‘vehicle’ of this design research, that the students’ work will contribute to understandings of how creative design disciplines might respond to this significant national problem, which hitherto has been attended to primarily by engineering and the sciences.

Asset renewal decision modelling with application to the water utility industry

Reliable infrastructure assets impact significantly on quality of life and provide a stable foundation for economic growth and competitiveness. Decisions about the way assets are managed are of utmost importance in achieving this. Timely renewal of infrastructure assets supports reliability and maximum utilisation of infrastructure and enables business and community to grow and prosper. This research initially examined a framework for asset management decisions and then focused on asset renewal optimisation and renewal engineering optimisation in depth. This study had four primary objectives. The first was to develop a new Asset Management Decision Framework (AMDF) for identifying and classifying asset management decisions. The AMDF was developed by applying multi-criteria decision theory, classical management theory and life cycle management. The AMDF is an original and innovative contribution to asset management in that: · it is the first framework to provide guidance for developing asset management decision criteria based on fundamental business objectives; · it is the first framework to provide a decision context identification and analysis process for asset management decisions; and · it is the only comprehensive listing of asset management decision types developed from first principles. The second objective of this research was to develop a novel multi-attribute Asset Renewal Decision Model (ARDM) that takes account of financial, customer service, health and safety, environmental and socio-economic objectives. The unique feature of this ARDM is that it is the only model to optimise timing of asset renewal with respect to fundamental business objectives. The third objective of this research was to develop a novel Renewal Engineering Decision Model (REDM) that uses multiple criteria to determine the optimal timing for renewal engineering. The unique features of this model are that: · it is a novel extension to existing real options valuation models in that it uses overall utility rather than present value of cash flows to model engineering value; and · it is the only REDM that optimises timing of renewal engineering with respect to fundamental business objectives; The final objective was to develop and validate an Asset Renewal Engineering Philosophy (AREP) consisting of three principles of asset renewal engineering. The principles were validated using a novel application of real options theory. The AREP is the only renewal engineering philosophy in existence. The original contributions of this research are expected to enrich the body of knowledge in asset management through effectively addressing the need for an asset management decision framework, asset renewal and renewal engineering optimisation based on fundamental business objectives and a novel renewal engineering philosophy.

Technology, design and process innovation in the built environment

Buildings and infrastructure represent principal assets of any national economy as well as prime sources of environmental degradation. Making them more sustainable represents a key challenge for the construction, planning and design industries and governments at all levels; and the rapid urbanisation of the 21st century has turned this into a global challenge. This book embodies the results of a major research programme by members of the Australia Co-operative Research Centre for Construction Innovation and its global partners, presented for an international audience of construction researchers, senior professionals and advanced students. It covers four themes, applied to regeneration as well as to new build, and within the overall theme of Innovation: Sustainable Materials and Manufactures, focusing on building material products, their manufacture and assembly – and the reduction of their ecological ‘fingerprints’, the extension of their service lives, and their re-use and recyclability. It also explores the prospects for applying the principles of the assembly line. Virtual Design, Construction and Management, viewed as increasing sustainable development through automation, enhanced collaboration (such as virtual design teams), real time BL performance assessment during design, simulation of the construction process, life-cycle management of project information (zero information loss) risk minimisation, and increased potential for innovation and value adding. Integrating Design, Construction and Facility Management over the Project Life Cycle, by converging ICT, design science engineering and sustainability science. Integration across spatial scales, enabling building–infrastructure synergies (such as water and energy efficiency). Convergences between IT and design and operational processes are also viewed as a key platform increased sustainability.

Queer cops in Queensland : exploring LGBT narrative histories in the Queensland Police Service

This chapter reports on a narrative project recording the experiences of LGBT former and current police officers in the Queensland Police Service (QPS), Australia. It begins by examining the historical and research contexts of LGBT police officers, followed by a discussion of the methodology employed for the project. The chapter then examines and analyzes key themes emerging from the data about coming out, macho police culture, and the double life syndrome often experienced by LGBT police officers. Finally, it suggests that further research might uncover a more widespread application of these findings.

Service enhanced manufacturing in the building and construction product system

This report examines the involvement of manufacturers in value-adding through service-enhancement of product offerings. This focus has been prompted by:  emphasis in the knowledge-economy literature on the increasing role played by services in economic growth; and  recent analysis which suggests that the most dynamic sector of many economies is an integrated manufacturing-services sector (see Part One of this report). The report initially describes the emergence of an integrated manufacturing-services sector in the context of increasingly knowledge-based economic systems. Part Two reports on the results of a survey of manufacturers in the building and construction product system, investigating their involvement in service provision. Parts Three and Four present two case studies of exemplary manufacturers involved in adding value to their manufacturing operations through services offered on building and construction projects. The report examines manufacturers of materials, products, equipment and machinery used on building and construction projects. The two case study sections of the report, in part, focus on a major project undertaken by each of the manufacturers. This project element of activity is focussed on (as opposed to wholesale or retail supply), because this area of activity involves a broader array of service-enhancement mechanisms and more complex bundling of products and services.

Business service management : understanding business models

One of the prominent topics in Business Service Management is business models for (new) services. Business models are useful for service management and engineering as they provide a broader and more holistic perspective on services. Business models are particularly relevant for service innovation as this requires paying attention to the business models that make new services viable and business model innovation can drive the innovation of new and established services. Before we can have a look at business models for services, we first need to understand what business models are. This is not straight-forward as business models are still not well comprehended and the knowledge about business models is fragmented over different disciplines, such as information systems, strategy, innovation, and entrepreneurship. This whitepaper, ‘Understanding business models,’ introduces readers to business models. This whitepaper contributes to enhancing the understanding of business models, in particular the conceptualisation of business models by discussing and integrating business model definitions, frameworks and archetypes from different disciplines. After reading this whitepaper, the reader will have a well-developed understanding about what business models are and how the concept is sometimes interpreted and used in different ways. It will help the reader in assessing their own understanding of business models and that and of others. This will contribute to a better and more beneficial use of business models, an increase in shared understanding, and making it easier to work with business model techniques and tools.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Integrated Acquisition Engineering Model for acquiring heavy engineering assets

In asset intensive industries such as mining, oil & gas, utilities etc. most of the capital expenditure happens on acquiring engineering assets. Process of acquiring assets is called as “Procurement” or “Acquisition”. An asset procurement decision should be taken in consideration with the installation, commissioning, operational, maintenance and disposal needs of an asset or spare. However, such cross-functional collaboration and communication does not appear to happen between engineering, maintenance, warehousing and procurement functions in many asset intensive industries. Acquisition planning and execution are two distinct parts of asset acquisition process. Acquisition planning or procurement planning is responsible for determining exactly what is required to be purchased. It is important that an asset acquisition decision is the result of cross-functional decision making process. An acquisition decision leads to a formal purchase order. Most costly asset decisions occur even before they are acquired. Therefore, acquisition decision should be an outcome of an integrated planning & decision making process. Asset intensive organizations both, Government and non Government in Australia spent AUD 102.5 Billion on asset acquisition in year 2008-09. There is widespread evidence of many assets and spare not being used or utilized and in the end are written off. This clearly shows that many organizations end up buying assets or spares which were not required or non-conforming to the needs of user functions. It is due the fact that strategic and software driven procurement process do not consider all the requirements from various functions within the organization which contribute to the operation and maintenance of the asset over its life cycle. There is a lot of research done on how to implement an effective procurement process. There are numerous software solutions available for executing a procurement process. However, not much research is done on how to arrive at a cross functional procurement planning process. It is also important to link procurement planning process to procurement execution process. This research will discuss ““Acquisition Engineering Model” (AEM) framework, which aims at assisting acquisition decision making based on various criteria to satisfy cross-functional organizational requirements. Acquisition Engineering Model (AEM) will consider inputs from corporate asset management strategy, production management, maintenance management, warehousing, finance and HSE. Therefore, it is essential that the multi-criteria driven acquisition planning process is carried out and its output is fed to the asset acquisition (procurement execution) process. An effective procurement decision making framework to perform acquisition planning which considers various functional criteria will be discussed in this paper.

Prognostic modelling options for remaining useful life estimation by industry

Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

Maximum recovery after knee replacement - the MARKER study rationale and protocol

Background There is little scientific evidence to support the usual practice of providing outpatient rehabilitation to patients undergoing total knee replacement surgery (TKR) immediately after discharge from the orthopaedic ward. It is hypothesised that the lack of clinical benefit is due to the low exercise intensity tolerated at this time, with patients still recovering from the effects of major orthopaedic surgery. The aim of the proposed clinical trial is to investigate the clinical and cost effectiveness of a novel rehabilitation strategy, consisting of an initial home exercise programme followed, approximately six weeks later, by higher intensity outpatient exercise classes. Methods/Design In this multicentre randomised controlled trial, 600 patients undergoing primary TKR will be recruited at the orthopaedic pre-admission clinic of 10 large public and private hospitals in Australia. There will be no change to the medical or rehabilitative care usually provided while the participant is admitted to the orthopaedic ward. After TKR, but prior to discharge from the orthopaedic ward, participants will be randomised to either the novel rehabilitation strategy or usual rehabilitative care as provided by the hospital or recommended by the orthopaedic surgeon. Outcomes assessments will be conducted at baseline (pre-admission clinic) and at 6 weeks, 6 months and 12 months following randomisation. The primary outcomes will be self-reported knee pain and physical function. Secondary outcomes include quality of life and objective measures of physical performance. Health economic data (health sector and community service utilisation, loss of productivity) will be recorded prospectively by participants in a patient diary. This patient cohort will also be followed-up annually for five years for knee pain, physical function and the need or actual incidence of further joint replacement surgery. Discussion The results of this pragmatic clinical trial can be directly implemented into clinical practice. If beneficial, the novel rehabilitation strategy of utilising outpatient exercise classes during a later rehabilitation phase would provide a feasible and potentially cost-effective intervention to optimise the physical well-being of the large number of people undergoing TKR.

Measuring transit service reliability using data from web-based transit user survey : a case study at Brisbane, Australia

This paper reports an empirical study on measuring transit service reliability using the data from a Web-based passenger survey on a major transit corridor in Brisbane, Australia. After an introduction of transit service reliability measures, the paper presents the results from the case study including study area, data collection, and reliability measures obtained. This includes data exploration of boarding/arrival lateness, in-vehicle time variation, waiting time variation, and headway adherence. Impacts of peak-period effects and separate operation on service reliability are examined. Relationships between transit service characteristics and passenger waiting time are also discussed. A summary of key findings and an agenda of future research are offered in conclusions.

Hybrid-Game Strategies for multi-objective design optimization in engineering

A number of Game Strategies (GS) have been developed in past decades. They have been used in the fields of economics, engineering, computer science and biology due to their efficiency in solving design optimization problems. In addition, research in multi-objective (MO) and multidisciplinary design optimization (MDO) has focused on developing robust and efficient optimization methods to produce a set of high quality solutions with low computational cost. In this paper, two optimization techniques are considered; the first optimization method uses multi-fidelity hierarchical Pareto optimality. The second optimization method uses the combination of two Game Strategies; Nash-equilibrium and Pareto optimality. The paper shows how Game Strategies can be hybridised and coupled to Multi-Objective Evolutionary Algorithms (MOEA) to accelerate convergence speed and to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid-Game Strategies are clearly demonstrated