560 resultados para residential building industry
Resumo:
The rising problems associated with construction such as decreasing quality and productivity, labour shortages, occupational safety, and inferior working conditions have opened the possibility of more revolutionary solutions within the industry. One prospective option is in the implementation of innovative technologies such as automation and robotics, which has the potential to improve the industry in terms of productivity, safety and quality. The construction work site could, theoretically, be contained in a safer environment, with more efficient execution of the work, greater consistency of the outcome and higher level of control over the production process. By identifying the barriers to construction automation and robotics implementation in construction, and investigating ways in which to overcome them, contributions could be made in terms of better understanding and facilitating, where relevant, greater use of these technologies in the construction industry so as to promote its efficiency. This research aims to ascertain and explain the barriers to construction automation and robotics implementation by exploring and establishing the relationship between characteristics of the construction industry and attributes of existing construction automation and robotics technologies to level of usage and implementation in three selected countries; Japan, Australia and Malaysia. These three countries were chosen as their construction industry characteristics provide contrast in terms of culture, gross domestic product, technology application, organisational structure and labour policies. This research uses a mixed method approach of gathering data, both quantitative and qualitative, by employing a questionnaire survey and an interview schedule; using a wide range of sample from management through to on-site users, working in a range of small (less than AUD0.2million) to large companies (more than AUD500million), and involved in a broad range of business types and construction sectors. Detailed quantitative (statistical) and qualitative (content) data analysis is performed to provide a set of descriptions, relationships, and differences. The statistical tests selected for use include cross-tabulations, bivariate and multivariate analysis for investigating possible relationships between variables; and Kruskal-Wallis and Mann Whitney U test of independent samples for hypothesis testing and inferring the research sample to the construction industry population. Findings and conclusions arising from the research work which include the ranking schemes produced for four key areas of, the construction attributes on level of usage; barrier variables; differing levels of usage between countries; and future trends, have established a number of potential areas that could impact the level of implementation both globally and for individual countries.
Resumo:
This paper seeks to identify the approaches undertaken in implementing equal employment opportunity in the transport industry in Australia and the links between these approaches and indicators of increased participation of women. This male dominated industry employs limited numbers of women with fewer numbers of women in management. The study analyses data from a unique set of equal opportunity progress reports from all organisations in the transport industry that are required to provide public reports under Australian legislation. The findings indicate a correlation between some approaches to equal opportunity and increased numbers of women in some areas. The study is equally remarkable for what it does not find. Despite widespread equal opportunity implementation across a broad number of employment measures there are limited measures that predict increases in the numbers of women in management or in non-traditional roles. This study differs from others in that it identifies issues specific to one industry and links organisational approach to equal opportunity with the employment status of both women and men.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
Using Agents for Mining Maintenance Data while interacting in 3D Objectoriented Virtual Environments
Resumo:
This report demonstrates the development of: (a) object-oriented representation to provide 3D interactive environment using data provided by Woods Bagot; (b) establishing basis of agent technology for mining building maintenance data, and (C) 3D interaction in virtual environments using object-oriented representation. Applying data mining over industry maintenance database has been demonstrated in the previous report.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
Resumo:
The objective of the project “Value Alignment Process for Project Delivery” is to provide a catalyst and tools for reform in the building and construction industry to transform business-as-usual performance into exceptional performance. The outcomes of this project will be beneficial to not only the construction industry, but to the community as a whole because a more sophisticated industry can deliver more effective use of assets, financing, operating and maintenance of facilities to suit the community’s needs. The research project consists of a study into best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best approach for a specific project. These resources will be focused on promoting the principles that underlie best practice project delivery, rather than on identifying a particular delivery system. The need for such tools and resources becomes more and more acute as the environment within which the construction industry operates becomes more and more complex, and as business and political imperatives shift to encompass or represent diverse stakeholder interests. To this end, this literature review looks at why it is essential to achieve transformation in the Australian construction industry in the context of its importance to the Australian economy. It seeks to investigate the concepts of ‘alignment’ and value’ as they pertain to construction industry processes and relationships. It comprehensively reviews drivers of project excellence and best practice project delivery principles and looks at how clients approach selection of project delivery systems. It critiques existing project delivery strategies and gives an overview of recent best practice initiatives. The literature review represents a milestone against the Project Agreement and forms a foundation document for this research project
Resumo:
The new edition of this widely used and respected introductory accounting textbook continues to provide students and academics with a well written and accessible resource, with ample illustrations and applications to business for a first study of accounting. The text effectively maintains the balance between a 'user' and 'preparer' perspective by integrating real financial information and business decisions throughout. Through the use of real company information and financial statements students will quickly appreciate the use and users of accounting information. The textbook clearly outlines to students how a financial statement - such as a balance sheet, income statement, cash flow statement - communicates the financing, operating, and investing activities of a business. The text builds a strong conceptual understanding and develops skills in the application of accounting principles and techniques, providing students with a solid foundation for further studies in accounting. The integral role of financial statements for decision making is also emphasised in this text and is reinforced throughout by the Decision Toolkit in each chapter. Students are provided with an extensive set of tools necessary to make business decisions based on financial information.
Resumo:
“SOH see significant benefit in digitising its drawings and operation and maintenance manuals. Since SOH do not currently have digital models of the Opera House structure or other components, there is an opportunity for this national case study to promote the application of Digital Facility Modelling using standardized Building Information Models (BIM)”. The digital modelling element of this project examined the potential of building information models for Facility Management focusing on the following areas: • The re-usability of building information for FM purposes • BIM as an Integrated information model for facility management • Extendibility of the BIM to cope with business specific requirements • Commercial facility management software using standardised building information models • The ability to add (organisation specific) intelligence to the model • A roadmap for SOH to adopt BIM for FM The project has established that BIM – building information modelling - is an appropriate and potentially beneficial technology for the storage of integrated building, maintenance and management data for SOH. Based on the attributes of a BIM, several advantages can be envisioned: consistency in the data, intelligence in the model, multiple representations, source of information for intelligent programs and intelligent queries. The IFC – open building exchange standard – specification provides comprehensive support for asset and facility management functions, and offers new management, collaboration and procurement relationships based on sharing of intelligent building data. The major advantages of using an open standard are: information can be read and manipulated by any compliant software, reduced user “lock in” to proprietary solutions, third party software can be the “best of breed” to suit the process and scope at hand, standardised BIM solutions consider the wider implications of information exchange outside the scope of any particular vendor, information can be archived as ASCII files for archival purposes, and data quality can be enhanced as the now single source of users’ information has improved accuracy, correctness, currency, completeness and relevance. SOH current building standards have been successfully drafted for a BIM environment and are confidently expected to be fully developed when BIM is adopted operationally by SOH. There have been remarkably few technical difficulties in converting the House’s existing conventions and standards to the new model based environment. This demonstrates that the IFC model represents world practice for building data representation and management (see Sydney Opera House – FM Exemplar Project Report Number 2005-001-C-3, Open Specification for BIM: Sydney Opera House Case Study). Availability of FM applications based on BIM is in its infancy but focussed systems are already in operation internationally and show excellent prospects for implementation systems at SOH. In addition to the generic benefits of standardised BIM described above, the following FM specific advantages can be expected from this new integrated facilities management environment: faster and more effective processes, controlled whole life costs and environmental data, better customer service, common operational picture for current and strategic planning, visual decision-making and a total ownership cost model. Tests with partial BIM data – provided by several of SOH’s current consultants – show that the creation of a SOH complete model is realistic, but subject to resolution of compliance and detailed functional support by participating software applications. The showcase has demonstrated successfully that IFC based exchange is possible with several common BIM based applications through the creation of a new partial model of the building. Data exchanged has been geometrically accurate (the SOH building structure represents some of the most complex building elements) and supports rich information describing the types of objects, with their properties and relationships.
Resumo:
his report describes in detail a project aimed at providing a better understanding of the business drivers and barriers to the adoption of Building Information Modelling (BIM) in the Architecture Engineering and Construction (AEC) and facility management (FM) industry sectors. The objectives of the project were to investigate the nature of economic, process and industry constraints to BIM adoption and then - if possible - to identify business strategies, and cost/benefit models that may support adoption of BIM in AEC/FM industry. The research was based on case studies from the property, construction and facility management sectors as well as other industries and interviews with business leaders and users of advanced applications of CAD in the industry.
Resumo:
The determination of the most appropriate procurement method for capital works projects is a challenging task for the Department of Housing and Works (DHW) and other Western Australian State Government Agencies because of the array of assessment criteria that are considered and the procurement methods that are available. A number of different procurement systems can be used to deliver capital works projects such a traditional, design and construct and management. Sub-classifications of these systems have proliferated and continue to emerge in response to market demands. The selection of an inappropriate procurement method may lead to undesirable project outcomes. To facilitate DHW in selecting an appropriate procurement method for its capital works projects, a six step procurement method selection process is presented. The characteristics of the most common forms of procurement method used in Australia are presented. Case studies where procurement methods have been used for specific types of capital works in Western Australia are offered to provide a reference point and learning opportunity for procurement method selection.
Resumo:
A plethora of methods for procuring building projects are available to meet the needs of clients. Deciding what method to use for a given project is a difficult and challenging task as a client’s objectives and priorities need to marry with the selected method so as to improve the likelihood of the project being procured successfully. The decision as to what procurement system to use should be made as early as possible and underpinned by the client’s business case for the project. The risks and how they can potentially affect the client’s business should also be considered. In this report, the need for client’s to develop a procurement strategy, which outlines the key means by which the objectives of the project are to be achieved is emphasised. Once a client has established a business case for a project, appointed a principal advisor, determined their requirements and brief, then consideration as to which procurement method to be adopted should be made. An understanding of the characteristics of various procurement options is required before a recommendation can be made to a client. Procurement systems can be categorised as traditional, design and construct, management and collaborative. The characteristics of these systems along with the procurement methods commonly used are described. The main advantages and disadvantages, and circumstances under which a system could be considered applicable for a given project are also identified.
Resumo:
The Cooperative Research Centre (CRC) for Construction Innovation research project 2001-008-C: ‘Project Team Integration: Communication, Coordination and Decision Support’, is supported by a number of Australian industry, government and university based project partners including: Queensland University of Technology (QUT); Commonwealth Scientific Industrial Research Organisation (CSIRO), University of Newcastle; Queensland Department of Public Works (QDPW); and the Queensland Department of Main Roads (QDMR). Supporting the various research aims and objectives of the 2001-008-C (Part B) QUT / Industry Partner agreements, and as a major deliverable for the project, this report is not intended as a comprehensive statement of Architectural, Engineering and Contractor (AEC) industry best practice recommendations. Rather it should read as a set of research and industry recommended guidelines, based on extensive literature reviews and two years worth of investigative activities examining both public and private industry uptake of innovative information and communication technology (ICT) solutions, whilst highlighting the overall need for culture change.