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.

Subtropical design in South East Queensland : a handbook for planners, developers and decision makers

Subtropical Design in South East Queensland provides a direct link between climatic design, applied urban design and sustainable planning policy. The role that character and identity of a place plays in achieving environmental sustainability is explained. Values of local distinctiveness to do with climate, landscape and culture are identified and the environmental, social and economic benefits of applying subtropical design principles to planning are described. The handbook provides planners and urban designers with an understanding of how subtropical design principles apply within the different contexts of urban planning including the entire spectrum of urban scales from the regional scale, to the city, neighbourhood, street, individual building or site. Twelve interactive principles, and interrelated strategies, drawn predominantly from the body of knowledge of landscape architecture, architectural science and urban design are described in detail in text, and richly illustrated with diagrams and photographs.

Vulnerability, insurance and policy: The learner driver's standard of care

In Cook v Cook the Australian High Court held that the standard of reasonable care owed by a learner driver to an instructor, conscious of the driver’s lack of experience, was lower than that owed to other passengers and road users. Recently, in Imbree v McNeilly, the High Court declined to follow this principle, concluding that the driver’s status or relationship with the claimant should no longer influence or alter the standard of care owed. The decision therefore provides an opportunity to re-examine the rationale and policy behind current jurisprudence governing the standard of care owed by learner drivers. In doing so, this article considers the principles relevant to determining the standard and Imbree’s implications for other areas of tort law and claimant v defendant relationships. It argues that Imbree was influenced by changing judicial perceptions concerning the vulnerability of driving instructors and the relevance of insurance to tortious liability.

Working time alterations within the Australian construction industry

Purpose: The purpose of this paper is to provide a labour process theory interpretation of four case studies within the Australian construction industry. In each case study a working time intervention (a shift to a five-day working week from the industry standard six days) was implemented as an attempt to improve the work-life balance of employees. ----- ----- Design/methodology/approach: This paper was based on four case studies with mixed methods. Each case study has a variety of data collection methods which include questionnaires, short and long interviews, and focus groups. ----- ----- Findings: It was found that the complex mix of wage- and salary-earning staff within the construction industry, along with labour market pressures, means that changing to a five-day working week is quite a radical notion within the industry. However, there are some organisations willing to explore opportunities for change with mixed experiences. ----- ----- Practical implications: The practical implications of this research include understanding the complexity within the Australian construction industry, based around hours of work and pay systems. Decision-makers within the construction industry must recognize a range of competing pressures that mean that “preferred” managerial styles might not be appropriate. ----- ----- Originality/value:– This paper shows that construction firms must take an active approach to reducing the culture of long working hours. This can only be achieved by addressing issues of project timelines and budgets and assuring that take-home pay is not reliant on long hours of overtime.

Changing times in China

Brief travel article about Beijing, China, in the lead up to the Olympic Games.

Participation and e-democracy how to utilize web 2.0 for policy decision-making

This paper investigates in how to utilize ICT and Web 2.0 technologies and e-democracy software for policy decision-making. It introduces a cutting edge decision-making system that integrates the practice of e-petitions, e-consultation, e-rulemaking, e-voting, and proxy voting. The paper demonstrates how under precondition of direct democracy through the use this system the collective intelligence (CI) of a population would be gathered and used throughout the policy process.

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.

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Attribute exclusion strategies in airline choice : accounting for exogenous information on decision maker processing strategies in models of discrete choice

We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

A changing landscape : The mortgagee's power of sale in Queensland

In Australia, the extent of a mortgagee’s duty when exercising power of sale has long been the subject of conjecture. With the advent of the global financial crisis in the latter part of 2008, there has been some concern to ensure that the interests of mortgagors are adequately protected. In Queensland, concern of this type resulted in the enactment of the Property Law (Mortgagor Protection) Amendment Act 2008 (Qld). This amending legislation operates to both extend and strengthen the operation of s 85 of the Property Law Act 1974 (Qld) which regulates the mortgagee’s power of sale in Queensland. This article examines the impact of this amending legislation which was hastily introduced and passed by the Queensland Parliament without consultation and which introduces a level of prescription in relation to a sale under a prescribed mortgage which is without precedent elsewhere in Australia.

Teaching new dogs old tricks. How the move to 24/7 interactive, integrated multimedia, multi-platform news and feature delivery is not really changing the skills employers demand of graduates

The journalism revolution is upon us. In a world where we are constantly being told that everyone can be a publisher and challenges are emerging from bloggers, Twitterers and podcasters, journalism educators are inevitably reassessing what skills we now need to teach to keep our graduates ahead of the game. QUT this year tackled that question head-on as a curriculum review and program restructure resulted in a greater emphasis on online journalism. The author spent a week in the online newsrooms of each of two of the major players – ABC online news and thecouriermail.com to watch, listen and interview some of the key players. This, in addition to interviews with industry leaders from Fairfax and news.com, lead to the conclusion that while there are some new skills involved in new media much of what the industry is demanding is in fact good old fashioned journalism. Themes of good spelling, grammar, accuracy and writing skills and a nose for news recurred when industry players were asked what it was that they would like to see in new graduates. While speed was cited as one of the big attributes needed in online journalism, the conclusion of many of the players was that the skills of a good down-table sub or a journalist working for wire service were not unlike those most used in online newsrooms.

Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Changing personal epistemologies in early childhood pre-service teachers using an integrated teaching program

This study investigated changes in pre-service teachers’ personal epistemologies as they engaged in an integrated teaching program. Personal epistemology refers to individual beliefs about the nature of knowing and knowledge and has been shown to influence teaching practice. An integrated approach to teaching, based on both an implicit and explicit focus on personal epistemology, was developed by an academic team within a Bachelor of Education (Early Childhood). The teaching program integrated content across four units of study, modelling personal epistemologies implicitly through collaborative reflexive practice. The students were also required to engage in explicit reflections on their personal epistemologies. Quantitative measures of personal epistemology were collected at the beginning and end of the semester using the Epistemological Beliefs Survey (EBS) to assess changes across the teaching period. Results indicated that pre-service teachers’ epistemological beliefs about the integration of knowledge became more sophisticated over the course of the teaching period. Qualitative data included pre-service teachers’ responses to open ended questions and field experience journal reflections about their perceptions of the teaching program and were collected at the end of the semester. These data showed that pre-service teachers held different conceptions about learning as integration, which provided a more nuanced understanding of the EBS data. Understanding pre-service teachers’ epistemological beliefs provides promising directions for teacher preparation and professional enrichment.

Developing an IS-Impact decision tool : a literature based design science roadmap

This paper derives from research-in-progress intending both Design Research (DR) and Design Science (DS) outputs; the former a management decision tool based in IS-Impact (Gable et al. 2008) kernel theory; the latter being methodological learnings deriving from synthesis of the literature and reflection on the DR ‘case study’ experience. The paper introduces a generic, detailed and pragmatic DS ‘Research Roadmap’ or methodology, deriving at this stage primarily from synthesis and harmonization of relevant concepts identified through systematic archival analysis of related literature. The scope of the Roadmap too has been influenced by the parallel study aim to undertake DR applying and further evolving the Roadmap. The Roadmap is presented in attention to the dearth of detailed guidance available to novice Researchers in Design Science Research (DSR), and though preliminary, is expected to evolve and gradually be substantiated through experience of its application. A key distinction of the Roadmap from other DSR methods is its breadth of coverage of published DSR concepts and activities; its detail and scope. It represents a useful synthesis and integration of otherwise highly disparate DSR-related concepts.

Developing a multidimensional scale for ethical decision making

This article reports on the development of the managerial ethical profile (MEP) scale. The MEP scale is a multilevel, self-reporting scale measuring the perceived influence that different dimensions of common ethical frameworks have on managerial decision making. The MEP scale measures on eight subscales: economic egoism, reputational egoism, act utilitarianism, rule utilitarianism, self-virtue of self, virtue of others, act deontology, and rule deontology. Confirmatory factor analysis (CFA) was used to provide evidence of scale validity. Future research needs and the value of this measure for business ethics are discussed.