Factors that influence Australian community buildings' sustainable management

© 2017 Emerald Publishing Limited. Purpose - Australia has a huge stock of community buildings built up over decades. Their replacements consume a large sum of money from country's economy which has called for a strategy for their sustainable management. For this, a comprehensive decision-making structure is an utmost requirement. The purpose of this paper is to capture their sustainable management from four aspects, i.e. environmental, economic, social and functional. Design/methodology/approach - The design process follows an extensive review of environmental and life cycle assessments and company context documents. Extracted factors are tailored to community buildings management following expert consultation. However, the resulted list of factors is extremely large, and "factor analysis" technique is used to group the factors. For this, an industry-wide questionnaire across Australian local councils is employed to solicit opinions of the list of factors. Findings - The analysis has pinpointed 18 key parameters (criteria) to represent all four aspects. This paper presents the preliminary findings of the factors and the analysis results based on the questionnaire responses. Practical implications - The final decision-making structure incorporates all these aspects and criteria. This can be used to develop a decision-making model which produces a sustainability index for building components. Asset managers can mainly use the sustainability index to prioritise their maintenance activities and eventually, to find out cost-optimisation options for them. Originality/value - Most notably, this is the first study to apply all four sustainability aspects (environmental, economic, social and functional) to develop a decision-making structure for Australian community buildings' sustainable management

Factors that influence Australian community buildings' sustainable management

© 2017 Emerald Publishing Limited. Purpose - Australia has a huge stock of community buildings built up over decades. Their replacements consume a large sum of money from country's economy which has called for a strategy for their sustainable management. For this, a comprehensive decision-making structure is an utmost requirement. The purpose of this paper is to capture their sustainable management from four aspects, i.e. environmental, economic, social and functional. Design/methodology/approach - The design process follows an extensive review of environmental and life cycle assessments and company context documents. Extracted factors are tailored to community buildings management following expert consultation. However, the resulted list of factors is extremely large, and "factor analysis" technique is used to group the factors. For this, an industry-wide questionnaire across Australian local councils is employed to solicit opinions of the list of factors. Findings - The analysis has pinpointed 18 key parameters (criteria) to represent all four aspects. This paper presents the preliminary findings of the factors and the analysis results based on the questionnaire responses. Practical implications - The final decision-making structure incorporates all these aspects and criteria. This can be used to develop a decision-making model which produces a sustainability index for building components. Asset managers can mainly use the sustainability index to prioritise their maintenance activities and eventually, to find out cost-optimisation options for them. Originality/value - Most notably, this is the first study to apply all four sustainability aspects (environmental, economic, social and functional) to develop a decision-making structure for Australian community buildings' sustainable management

Prioritising sustainability factors for australian community buildings’ management using analytical hierarchy process (AHP)

The essence of Australian community buildings’ sustainable management drives through a previously established decision-making structure with four sustainability aspects and accompanying 18 criteria. Informed decisions are supported with a decision-making model that generates sustainability impacts of building components based on this decision-making structure. Building components’ individual impacts can be assigned using a numbering scale incorporated with linguistic terms. However, similar importance given to each aspect or criterion is arguable when the combined effect is considered. Hence, they should be given different weightings and their combination with individual impacts will produce final sustainability impacts. For calculating weightings, the study uses Analytical Hierarchy Process (AHP), widely used technique in Multi Attribute Decision-Making (MADM). The study also conducted an industry-wide questionnaire across Australian local councils because pair-wise comparison data is essential for weighting calculation. This paper presents the survey data and analysis results that captured weightings of sustainability aspects and criteria. © 2018 The Author(s). Published by VGTU Press

Determining the best intervention times of whole building assets for renewals during the planned period

The objective of service life analysis is to establish and explain the performance-over-time functions, which describes how the measured values of chosen performance characteristics are expected to vary with time. Applicable to buildings, the most viable method of capturing the performance is according to their condition; furthermore, referring to the minimum acceptable condition of the given building or component. Below this level, performance is considered not to be acceptable for the intended function, although the building or component can still be functional or operational. A deterioration curve represents the condition degradation over time, which can be regarded as a performance indicator over time. Referring to the deterioration curve produced regardless of deterministic or probabilistic way, the current study conducts a theoretical investigation of best intervention periods for renewals of whole building assets. Theoretical investigation is mainly underpinned by the relevant variables of the prediction curve such as useful life, remaining useful life, planned duration, minimum acceptable condition for performance, current year and last year of the planned duration and the first and last time that the intervention can be done effectively. Given that three interventions are the maximum number of interventions expected to occur during the planned period, eight scenarios of interventions come into effect. Hence, theoretical investigation has been applied to each scenario. The study has also used actual case study data hypothetically applied them to each scenario for further clarification of theoretical findings. The outcomes essentially guide building/ facility owners and managers for better informed decision-making of their building renewals

Factor analysis for establishing a decision making framework for the sustainable management of community buildings in Australia

Community buildings are the second largest infrastructure asset owned by the governments in Australia. Mostly built in 1970s, these buildings have popularly seen significant deterioration of structure and service components, which stymied the delivery of essential services to the local communities. The sustainable management of these buildings is urgent and critical, which has to take into account the economic benefits, environmental and social impacts, as well as buildings condition and functional usages. An industry wide questionnaire survey was undertaken to examine factors influencing the sustainable management of community buildings. Through factor analysis, the research pinpointed 18 key parameters related to the environmental, social, economic and functional aspects of community buildings, which local council asset managers have to contemplate in order to plan the building management well and make an informed decision. This paper presents the preliminary findings of the survey research and further highlights the future work towards the development of fuzzy AHP based decision making model. Copyright © 2012 IEEE

Deterioration prediction of superstructure elements of community buildings in Australia using a probabilistic approach

Buildings are complex infrastructure assets and optimization of maintenance and rehabilitation actions require a well-considered asset management model. Community Buildings as one of the major investments of the local government in Australia have a large proportion of demand, expectation, and consideration among the local council’s assets. The following paper introduces a building asset management (BAM) framework and a building element hierarchy which facilitates the building asset management and inspection strategies. Data gathering and preparation will be discussed followed by the calibration of a probabilistic deterioration prediction approach based on the Markov process. The Markov transition matrices have been derived for building elements based on the condition data sourced from local councils. The transition matrices for superstructure elements are presented, reviewed, and compared. © Springer-Verlag London 2014

A risk assessment method to quantitatively investigate the methane explosion in underground coal mine

Methane explosion in underground coal mine is one of the most deadly hazards to the miners and the surrounding environment. An improved analytical hierarchy process (IAHP) was developed to investigate the influencing factors of methane explosion quantitatively. IAHP was validated by statistical data, showing its advantages in reducing bias. Both IAHP results and statistical data indicated that electrical spark, blasting and friction spark were the leading ignition sources. Blasting operation, digging process, explosive charge and gas detect procedure showed the highest influencing weights to methane explosion. A case/example was provided to determine the safety level of an underground coal mine. Implementations were provided to avoid methane explosion in underground coal mines, such as avoiding high methane concentration (10–15 vol.%), taking care of rocks with more than 30% quartz and larger than 70 m particle size, and using high melting point tool/equipment, and limiting coal pick speed within 1.5 m/s

Decision making for the sustainable management of community buildings in Australia using fuzzy logic

© The Hong Kong Polytechnic University. Community buildings serve a large part of built environment in Australia. Due to the fact of ageing and lack of maintenance, degradation rate of these assets has been increasing in recent years. This phenomenon and the non-existence of a reliable asset management tool in the current practice of building management have assured a necessity of developing a decision making model to address those issues to achieve sustainable management of community buildings. The majority of decisions made in community building management appeared to be inconsistent and subjective. The aim of this paper is to establish an analytical model to minimize this inconsistency and subjectivity to be precise enough through introducing logic into encapsulating and addressing this uncertain nature. Fuzzy logic has been introduced to deal with this uncertainty and finally develop the model. Based on renewal and maintenance actions decision making has been considered in four main aspects including environmental, economic, social and functional related issues. Then it will be further explored to ascertain critical parameters influencing to those main factors. Expert opinion will be used to finalise these critical parameters through questionnaire surveys. The process is running in two different fuzzy applications consisting of analytical hierarchical process (AHP) and fuzzy inference system (FIS). AHP is used to measure the aggregate impact of critical parameters. The overall impact on decision making by its four main factors is evaluated using either FIS or AHP. A criticality index has been developed to support the decision making, and future actions will be planned accordingly. Example calculations and case study data have been demonstrated throughout the paper to showcase and validate the model

Nonparametric survival analysis of the loss rate of undergraduate engineering students

Backround: As presented by Willet and Singer (1991), survival analysis can sensitively reveal rich information about when students leave their majors. Although survival analysis has been used to investigate student and faculty retention, it has not been applied to undergraduate engineering student retention. Purpose (Hypothesis): The impact of cohort, gender, ethnicity, and SAT math and verbal scores on the loss rate of undergraduate engineering students was investigated to answer the questions: Does the profile of risk of dropout differ among groups with different backgrounds? When are students most likely to leave engineering? Which SAT scores better predict the risk of dropout? Design/Method: Using a large longitudinal database that includes 100, 179 engineering students from nine universities and spans 19 years, nonparametric survival analysis was adopted to obtain nonparametric estimates of survival and associated hazard fiinctions, and complete rank tests for the association of variables. Results: There are significant differences for early semesters: White or female students tend to leave engineering earlier than other populations. Engineering students leave engineering during the third semester the most, although students who have an SAT math score less than 550 tend to leave engineering during the second semester. SAT math score better predicts the risk of dropout than SAT verbal score. Conclusions: The results of this study support using survival analysis to better understand factors that determine student success since student retention is a dynamic problem. Survival analysis allows characteristics such as risk to be evaluated by semester, giving insight to when interventions might be most effective

A proposed decision-making model to prioritize building elements maintenance actions toward achieving sustainability in community buildings in Australia

© Springer-Verlag London 2014. Sustainable management of community buildings is a challenging task in Australia. Maintenance and renewal of building assets is a prominent issue as a large number of buildings owned by local councils were built in 1970s and become aged and deteriorated. Each building consists of a massive load of building components which adds complexity into their management. Limited asset management models in favor of buildings’ decision making have further widened the gap in finding a reliable decision-making model for building maintenance and renewals. On the other hand, a majority of asset management models available are unable to cope with the uncertainty associated with the data collection which makes the results inconsistent and subjective. This paper presents a useful tool minimizing aforementioned problems and making asset planner’s life easier to prioritize maintenance actions. The model is a multi-criteria decision-making model (MCDM) which is combined with two analytical tools, i.e., analytical hierarchical process (AHP) and fuzzy inference system (FIS). The model is based on a four level hierarchical structure, which includes a goal, aspects, criteria, and attribute factors representing the level one to level four in the hierarchy respectively. Decision Criticality Index (DCI) has been introduced in order to understand the importance of the decision. The concept which is used in the traffic light system is adapted to categorize maintenance options according to color codes depending on DCI value range and the duration of maintenance plan. Example calculations based on case study and hypothetical data have been demonstrated throughout the paper to showcase and validate the model