968 resultados para Assets


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The decision as to which procurement system to adopt is a complex and challenging task for clients of construction projects. Despite a plethora of tools and techniques available for selecting a procurement method, clients are still uncertain about what method to adopt for a given construction project to achieve success. This paper examines ‘how and why’ procurement methods are selected by public sector clients in Queensland (QLD) and Western Australia (WA). Findings from workshops with senior managers in procurement selection revealed that traditional lump sum methods (TLS) are preferred even though alternative forms could be better suited for a given project. Participants of the workshops agreed that alternative procurement forms should be considered for projects but an embedded culture of uncertainty avoidance meant the selection of TLS methods. It was perceived that only a limited number of contractors operating in the marketplace have the resources and experience to deliver projects using the non-traditional methods.

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Designing and estimating civil concrete structures is a complex process which to many practitioners is tied to manual or semi-manual processes of 2D design and cannot be further improved by automated, interacting design-estimating processes. This paper presents a feasibility study for the development an automated estimator for concrete bridge design. The study offers a value proposition: an efficient automated model-based estimator can add value to the whole bridge design-estimating process, i.e., reducing estimation errors, shortening the duration of success estimates, and increasing the benefit of doing cost estimation when compared with the current practice. This is then followed by a description of what is in an efficient automated model-based estimator and how it should be used. Finally the process of model-based estimating is compared with the current practice to highlight the values embedded in the automated processes.

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This paper provides an overview of the Australian Government’s Facilities Management (FM) Action Agenda as announced in 2004 as a key policy plank designed to facilitate growth of the FM industry. The resulting consultation with industry leaders has seen the criterion and release in April 2005 of the FM Action Agenda’s strategic plan entitled ‘Managing the Built Environment’. This framework, representing a collaboration between the Australian Government, public and private sector stakeholders and Facility Management Association of Australia (FMA Australia) and other allied bodies, sets out to achieve the vision of a more “…productive and sustainable built environment…” through improved innovation, education and standards. The 36 month implementation phase is now underway and will take a multi-pronged approach to enhancing the recognition of the FM industry and removing impediments to its growth with a 20 point action plan across the following platforms: • Innovation – Improved appreciation of facility life cycles, and greater understanding of the key drivers of workplace productivity, and the improved application of information technology. • Education and Training – Improved access to dedicated FM education and training opportunities and creation clear career pathways into the profession. • Regulatory Reform – Explore opportunities to harmonise cross jurisdictional regulatory compliance requirements that have an efficiency impact on FM. • Sustainability – Improved utilization of existing knowledge and the development of tools and opportunities to improve the environmental performance of facilities. Additional information is available at www.fma.com.au

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The paper presents an interim summary of research and case studies being undertaken in the Sydney Opera House FM Exemplar Project covering procurement, benchmarking and building information models. The final outcomes of the FM Exemplar Project will be presented through various forums open to all FM practitioners and published in Australia and elsewhere through relevant journals. Sydney Opera House is an Australian icon, attracting some 4.5 million visitors per year who admire its built form and enjoy an evening of theatre. The building is the attraction, part of the experience. Therefore, facilities management is critical to the success of the Sydney Opera House enterprise and an ideal subject for the study of facilities management. Significantly the three research themes are heavily intertwined – effective risk sharing in procurement requires historic information and benchmarks for future performance, benchmarking gathers vast quantities of data that can only be exploited if properly related to one another and a building information model provides the means to manage such data. The case studies are emerging as real-life examples of how one organisation is addressing FM issues common to many, and will provide useful lessons for practitioners pursing similar strategies in their own organisations.

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Facility managers have to acquire, integrate, edit and update diverse facility information ranging from building elements & fabric data, operational costs, contract types, room allocation, logistics, maintenance, etc. With the advent of standardized Building Information Models (BIM) such as the Industry Foundation Classes (IFC) new opportunities are available for Facility Managers to manage their FM data. The usage of IFC supports data interoperability between different software systems including the use of operational data for facility management systems. Besides the re-use of building data, the Building Information Model can be used as an information framework for storing and retrieving FM related data. Currently several BIM driven FM systems are available including IFC compliant ones. These systems have the potential to not only manage primary data more effectively but also to offer practical systems for detailed monitoring, and analysis of facility performance that can underpin innovative and more cost effective management of complex facilities.

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The effective management of bridge stock involves making decisions as to when to repair, remedy, or do nothing, taking into account the financial and service life implications. Such decisions require a reliable diagnosis as to the cause of distress and an understanding of the likely future degradation. Such diagnoses are based on a combination of visual inspections, laboratory tests on samples and expert opinions. In addition, the choice of appropriate laboratory tests requires an understanding of the degradation mechanisms involved. Under these circumstances, the use of expert systems or evaluation tools developed from “realtime” case studies provides a promising solution in the absence of expert knowledge. This paper addresses the issues in bridge infrastructure management in Queensland, Australia. Bridges affected by alkali silica reaction and chloride induced corrosion have been investigated and the results presented using a mind mapping tool. The analysis highights that several levels of rules are required to assess the mechanism causing distress. The systematic development of a rule based approach is presented. An example of this application to a case study bridge has been used to demonstrate that preliminary results are satisfactory.

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Reinforced concrete structures are susceptible to a variety of deterioration mechanisms due to creep and shrinkage, alkali-silica reaction (ASR), carbonation, and corrosion of the reinforcement. The deterioration problems can affect the integrity and load carrying capacity of the structure. Substantial research has been dedicated to these various mechanisms aiming to identify the causes, reactions, accelerants, retardants and consequences. This has improved our understanding of the long-term behaviour of reinforced concrete structures. However, the strengthening of reinforced concrete structures for durability has to date been mainly undertaken after expert assessment of field data followed by the development of a scheme to both terminate continuing degradation, by separating the structure from the environment, and strengthening the structure. The process does not include any significant consideration of the residual load-bearing capacity of the structure and the highly variable nature of estimates of such remaining capacity. Development of performance curves for deteriorating bridge structures has not been attempted due to the difficulty in developing a model when the input parameters have an extremely large variability. This paper presents a framework developed for an asset management system which assesses residual capacity and identifies the most appropriate rehabilitation method for a given reinforced concrete structure exposed to aggressive environments. In developing the framework, several industry consultation sessions have been conducted to identify input data required, research methodology and output knowledge base. Capturing expert opinion in a useable knowledge base requires development of a rule based formulation, which can subsequently be used to model the reliability of the performance curve of a reinforced concrete structure exposed to a given environment.

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n design of bridge structures, it is common to adopt a 100 year design life. However, analysis of a number of case study bridges in Australia has indicated that the actual design life can be significantly reduced due to premature deterioration resulting from exposure to aggressive environments. A closer analysis of the cost of rehabilitation of these structures has raised some interesting questions. What would be the real service life of a bridge exposed to certain aggressive environments? What is the strategy of conducting bridge rehabilitation? And what are the life cycle costs associated with rehabilitation? A research project funded by the CRC for Construction Innovation in Australia is aimed at addressing these issues. This paper presents a concept map for assisting decision makers to appropriately choose the best treatment for bridge rehabilitation affected by premature deterioration through exposure to aggressive environments in Australia. The decision analysis is referred to a whole of life cycle cost analysis by considering appropriate elements of bridge rehabilitation costs. In addition, the results of bridges inspections in Queensland are presented

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There are about 2500 bridges in Queensland, Australia. Majority of these structures require significant repairs around the halfway mark of their design life with probably 1% or less reaching a 100 year design life. (Carse, 2005). This is due to the fact that bridges constructed in aggressive environments such as the coastal regions experience accelerated deterioration. As a result, maintaining the service delivery of these assets has become one of the important issues for the Queensland Department of Main Roads (QDMR).

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The Automated Estimator and LCADesign are two early examples of nD modelling software which both rely on the extraction of quantities from CAD models to support their further processing. The issues of building information modelling (BIM), quantity takeoff for different purposes and automating quantity takeoff are discussed by comparing the aims and use of the two programs. The technical features of the two programs are also described. The technical issues around the use of 3D models is described together with implementation issues and comments about the implementation of the IFC specifications. Some user issues that emerged through the development process are described, with a summary of the generic research tasks which are necessary to fully support the use of BIM and nD modelling.

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An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.