514 resultados para Asset reversibility


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Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

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This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

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Rural land is still a major property asset class and rural commodity production is an important domestic and export market in all economies. This paper carries out a comprehensive analysis of both rural production and land prices in four major rural production countries. The study compares rural property values in Unites States, Canada, Australia and New Zealand over a period 1990 to 2005 and analyzes and compares the capital return and total return performance for rural land in these four countries. The analysis allows a comparison of farm land returns for both a subsidised and non-subsidised farming policy to determine if levels of farm support result in variations in farm profitability and therefore farm land values.

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Most infrastructure projects share the same characteristics in term of management aspects and shortcomings. Human factor is believed to be the major drawbacks due to the nature of unstructured problems which can further contribute to management conflicts. This growing complexity in infrastructure projects has shift the paradigm of policy makers to adopt Information Communication Technology (ICT) as a driving force. For this reason, it is vital to fully maximise and utilise the recent technologies to accelerate management process particularly in planning phase. Therefore, a lot of tools have been developed to assist decision making in construction project management. The variety of uncertainties and alternatives in decision making can be entertained by using useful tool such as Decision Support System (DSS). However, the recent trend shows that most DSS in this area only concentrated in model development and left few fundamentals of computing. Thus, most of them were found complicated and less efficient to support decision making within project team members. Due to the current incapability of many software aspects, it is desirable for DSS to provide more simplicity, better collaborative platform, efficient data manipulation and reflection to user needs. By considering these factors, the paper illustrates four challenges for future DSS development i.e. requirement engineering, communication framework, data management and interoperability, and software usability

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Effective knowledge transfer can prevent the reinvention of systems and ideas as well as the repetition of errors. Doing so will save substantial time, as well as contribute to better performance of projects and project-based organisations (PBOs). Despite the importance of knowledge, PBOs face serious barriers to the effective transfer of knowledge, while their characteristics, such as unique and innovative approaches taken during every project, mean they have much to gain from knowledge transfer. As each new project starts, there is the strong potential to reinvent the process, rather than utilise learning from previous projects. In fact, rework is one of the primary factors contributing to construction industry's poor performance and productivity. Current literature has identified several barriers to knowledge transfer in organisational settings in general, and not specifically PBOs. However, PBOs significantly differ from other types of organisations. PBOs operate mainly on temporary projects, where time is a crucial factor and people are more mobile than in other organisational settings. The aim of this research is to identify the key barriers that prevent effective knowledge transfer for PBOs, exclusively. Interviews with project managers and senior managers of PBOs complement the analysis of the literature and provide professional expertise. This research is crucial to gaining a better understanding of obstacles that hinder knowledge transfer in projects. The main contribution of this research is exclusive for PBO, list of key barriers that organisation and project managers need to consider to ensure effective knowledge transfer and better project management.

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The research on project learning has recognised the significance of knowledge transfer in project based organisations (PBOs). Effective knowledge transfer across projects avoids reinventions, enhances knowledge creation and saves lots of time that is crucial in project environment. In order to facilitate knowledge transfer, many PBOs have invested lots of financial and human resources to implement IT-based knowledge repository. However, some empirical studies found that employees would rather turn for knowledge to colleagues despite their ready access to IT-based knowledge repository. Therefore, it is apparent that social networks play a pivotal role in the knowledge transfer across projects. Some scholars attempt to explore the effect of network structure on knowledge transfer and performance, however, focused only on egocentric networks and the groups’ internal social networks. It has been found that the project’s external social network is also critical, in that the team members can not handle critical situations and accomplish the projects on time without the assistance and knowledge from external sources. To date, the influence of the structure of a project team’s internal and external social networks on project performance, and the interrelation between both networks are barely known. In order to obtain such knowledge, this paper explores the interrelation between the structure of a project team’s internal and external social networks, and their effect on the project team’s performance. Data is gathered through survey questionnaire distributed online to respondents. Collected data is analysed applying social network analysis (SNA) tools and SPSS. The theoretical contribution of this paper is the knowledge of the interrelation between the structure of a project team’s internal and external social networks and their influence on the project team’s performance. The practical contribution lies in the guideline to be proposed for constructing the structure of project team’s internal and external social networks.

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Agricultural production is one of the major industries in New Zealand and accounts for over 60% of all export trade. The farming industry comprises 70,000 entities ranging in size from small individual run farms to large corporate operations. The reliance of the New Zealand economy to the international rural sector has seen considerable volatility in the rural land markets over the past four decades, with significant shifts in rural land prices based on location, land use and underlying international rural commodity prices. With the increasing attention being paid to the rural sector, especially in relation to food production and bio-fuels, there has been an increasing corporate interest in rural land ownership in relatively low subsidised agricultural producing countries such as New Zealand and Australia. A factor that has limited this participation of institutional investors previously has been a lack of reliable and up-to-date investment performance data for this asset class. This paper is the initial starting phase in the development of a New Zealand South Island rural land investment performance index and covers the period 1990-2007. The research in this paper analyses all rural sales transactions in the South Island and develops a capital return index for rural property based on major rural property land use. Additional work on this index will cover both total return performance and geographic location.

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Although timber plantations and forests are classified as forms of agricultural production, the ownership of this land classification is not limited to rural producers. Timber plantations and forests are now regarded as a long-term investment with both institutional and absentee owners. While the NCREIF property indices have been the benchmarks for the measurement of the performance of the commercial property market in the UK, for many years the IPD timberland index has recently emerged as the U.K. forest and timberland performance indicator. The IPD Forest index incorporates 126 properties over five regions in the U.K. This paper will utilise the IPD Forestry Index to examine the performance of U.K. timber plantations and forests over the period 1981-2004. In particular, issues to be critically assessed include plantation and forest performance analysis, comparative investment analysis, and the role of plantations and forests in investment portfolios, the risk reduction and portfolio benefits of plantations and forests in mixed-asset portfolios and the strategic investment significance of U.K. timberlands.

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This research is aimed at addressing problems in the field of asset management relating to risk analysis and decision making based on data from a Supervisory Control and Data Acquisition (SCADA) system. It is apparent that determining risk likelihood in risk analysis is difficult, especially when historical information is unreliable. This relates to a problem in SCADA data analysis because of nested data. A further problem is in providing beneficial information from a SCADA system to a managerial level information system (e.g. Enterprise Resource Planning/ERP). A Hierarchical Model is developed to address the problems. The model is composed of three different Analyses: Hierarchical Analysis, Failure Mode and Effect Analysis, and Interdependence Analysis. The significant contributions from the model include: (a) a new risk analysis model, namely an Interdependence Risk Analysis Model which does not rely on the existence of historical information because it utilises Interdependence Relationships to determine the risk likelihood, (b) improvement of the SCADA data analysis problem by addressing the nested data problem through the Hierarchical Analysis, and (c) presentation of a framework to provide beneficial information from SCADA systems to ERP systems. The case study of a Water Treatment Plant is utilised for model validation.

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In recent years, practitioners and researchers alike have turned their attention to knowledge management (KM) in order to increase organisational performance (OP). As a result, many different approaches and strategies have been investigated and suggested for how knowledge should be managed to make organisations more effective and efficient. However, most research has been undertaken in the for-profit sector, with only a few studies focusing on the benefits nonprofit organisations might gain by managing knowledge. This study broadly investigates the impact of knowledge management on the organisational performance of nonprofit organisations. Organisational performance can be evaluated through either financial or non-financial measurements. In order to evaluate knowledge management and organisational performance, non-financial measurements are argued to be more suitable given that knowledge is an intangible asset which often cannot be expressed through financial indicators. Non-financial measurement concepts of performance such as the balanced scorecard or the concept of Intellectual Capital (IC) are well accepted and used within the for-profit and nonprofit sectors to evaluate organisational performance. This study utilised the concept of IC as the method to evaluate KM and OP in the context of nonprofit organisations due to the close link between KM and IC: Indeed, KM is concerned with managing the KM processes of creating, storing, sharing and applying knowledge and the organisational KM infrastructure such as organisational culture or organisational structure to support these processes. On the other hand, IC measures the knowledge stocks in different ontological levels: at the individual level (human capital), at the group level (relational capital) and at the organisational level (structural capital). In other words, IC measures the value of the knowledge which has been managed through KM. As KM encompasses the different KM processes and the KM infrastructure facilitating these processes, previous research has investigated the relationship between KM infrastructure and KM processes. Organisational culture, organisational structure and the level of IT support have been identified as the main factors of the KM infrastructure influencing the KM processes of creating, storing, sharing and applying knowledge. Other research has focused on the link between KM and OP or organisational effectiveness. Based on existing literature, a theoretical model was developed to enable the investigation of the relation between KM (encompassing KM infrastructure and KM processes) and IC. The model assumes an association between KM infrastructure and KM processes, as well as an association between KM processes and the various levels of IC (human capital, structural capital and relational capital). As a result, five research questions (RQ) with respect to the various factors of the KM infrastructure as well as with respect to the relationship between KM infrastructure and IC were raised and included into the research model: RQ 1 Do nonprofit organisations which have a Hierarchy culture have a stronger IT support than nonprofit organisations which have an Adhocracy culture? RQ 2 Do nonprofit organisations which have a centralised organisational structure have a stronger IT support than nonprofit organisations which have decentralised organisational structure? RQ 3 Do nonprofit organisations which have a stronger IT support have a higher value of Human Capital than nonprofit organisations which have a less strong IT support? RQ 4 Do nonprofit organisations which have a stronger IT support have a higher value of Structural Capital than nonprofit organisations which have a less strong IT support? RQ 5 Do nonprofit organisations which have a stronger IT support have a higher value of Relational Capital than nonprofit organisations which have a less strong IT support? In order to investigate the research questions, measurements for IC were developed which were linked to the main KM processes. The final KM/IC model contained four items for evaluating human capital, five items for evaluating structural capital and four items for evaluating relational capital. The research questions were investigated through empirical research using a case study approach with the focus on two nonprofit organisations providing trade promotions services through local offices worldwide. Data for the investigation of the assumptions were collected via qualitative as well as quantitative research methods. The qualitative study included interviews with representatives of the two participating organisations as well as in-depth document research. The purpose of the qualitative study was to investigate the factors of the KM infrastructure (organisational culture, organisational structure, IT support) of the organisations and how these factors were related to each other. On the other hand, the quantitative study was carried out through an online-survey amongst staff of the various local offices. The purpose of the quantitative study was to investigate which impact the level of IT support, as the main instrument of the KM infrastructure, had on IC. Overall several key themes were found as a result of the study: • Knowledge Management and Intellectual Capital were complementary with each other, which should be expressed through measurements of IC based on KM processes. • The various factors of the KM infrastructure (organisational culture, organisational structure and level of IT support) are interdependent. • IT was a primary instrument through which the different KM processes (creating, storing, sharing and applying knowledge) were performed. • A high level of IT support was evident when participants reported higher level of IC (human capital, structural capital and relational capital). The study supported previous research in the field of KM and replicated the findings from other case studies in this area. The study also contributed to theory by placing the KM research within the nonprofit context and analysing the linkage between KM and IC. From the managerial perspective, the findings gave clear indications that would allow interested parties, such as nonprofit managers or consultants to understand more about the implications of KM on OP and to use this knowledge for implementing efficient and effective KM strategies within their organisations.

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Industrial property is commonly located in a designated ‘industrial’ precinct. An industrial property has a specific design and a number of services to support industrial activities including manufacture, distribution and transportation. Although it has a unique characteristic, certain industrial factor might operate differently in different countries. The aim of this paper is to provide a comparison between the Sydney and Hong Kong industrial property characteristics and to highlight their similarities and differences. This exploratory research used secondary data to provide background information of government policy and market conditions. Two case studies were use to illustrate similarities, trends, differences and to explore town planning, specific property characteristics including location, design and layout. Then, analyse whether these factors influence the performance and value of an industrial asset. The location of industrial properties varies between each country and depends heavily on infrastructure. It was noted that the town planning restrictions not only vary between markets and cities but also between property lots. The market conditions of both industrial markets were investigated and the supply and demand and rental levels in both cities were distinctly opposite.

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Although timber plantations and forests are classified as forms of agricultural production, the ownership of this land classification is not limited to rural producers. Timber plantations and forests are now regarded as a long-term investment with both institutional and absentee owners. While the NCREIF property indices have been the benchmarks for the measurement of the performance of the commercial property market in the UK, for many years the IPD timberland index has recently emerged as the U.K. forest and timberland performance indicator. The IPD Forest index incorporates 126 properties over five regions in the U.K. This paper will utilise the IPD Forestry Index to examine the performance of U.K. timber plantations and forests over the period 1981-2004. In particular, issues to be critically assessed include plantation and forest performance analysis, comparative investment analysis, and the role of plantations and forests in investment portfolios, the risk reduction and portfolio benefits of plantations and forests in mixed-asset portfolios and the strategic investment significance of U.K. timberlands.

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Timberland is now regarded as a long-term investment with both institutional investors and absentee owners. This paper utilises the NCREIF Timberland index to examine the performance of US timberland over the period of 1987-1999. US timberland was found to provide significant risk reduction and portfolio diversification benefits in the portfolio resulting from the low risk and low correlation with stocks and bonds. Timberland was also found to make a significant contribution to a portfolio of stocks, bonds and real estate, particularly at low to midrange portfolio risk levels.

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Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

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Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).