Risk assessment in life-cycle costing for road asset management

Queensland Department of Main Roads, Australia, spends approximately A$ 1 billion annually for road infrastructure asset management. To effectively manage road infrastructure, firstly road agencies not only need to optimise the expenditure for data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. This paper presents the results of case studies in using the probability-based method for an integrated approach (i.e. assessing optimal costs of pavement strength data collection; calibrating deterioration prediction models that suit local condition and assessing risk-adjusted budget estimates for road maintenance and rehabilitation for assessing life-cycle budget estimates). The probability concept is opening the path to having the means to predict life-cycle maintenance and rehabilitation budget estimates that have a known probability of success (e.g. produce budget estimates for a project life-cycle cost with 5% probability of exceeding). The paper also presents a conceptual decision-making framework in the form of risk mapping in which the life-cycle budget/cost investment could be considered in conjunction with social, environmental and political issues.

Framework of whole life cycle costing for Malaysian high rise residential property development

This project was an initial stage in formulating and management of the optimum budget allocation during the operational, maintenance and rehabilitation phases in high rise residential property development in Malaysia. The principal objective of this project is to develop a framework of Whole Life Cycle Costing for high rise residential property development that will enhance the quality and cost effectiveness of this building type in Malaysia. The researcher investigated 13 building components from 6 high rise residential property developments in Johor, Malaysia to determine the affect and economic impact of component initial cost and quality by applying them to a Whole Life Cycle Cost model approach. The results provide valuable data in respect to the overall cost of specific components over the whole life of a large high rise building. In addition, Dr. Mat Noor also determined the impact and satisfaction of quality of building components through WLCC.

Managing cost implications for highway infrastructure sustainability

Highway construction works have significant bearings on all aspects of sustainability. With the increasing level of public awareness and government regulatory measures, the construction industry is experiencing a cultural shift to recognise, embrace and pursue sustainability. Stakeholders are now keen to identify sustainable alternatives and the financial implications of including them on a lifecycle basis. They need tools that can aid the evaluation of investment options. To date, however, there have not been many financial assessments on the sustainability aspects of highway projects. This is because the existing life-cycle costing analysis (LCCA) models tend to focus on economic issues alone and are not able to deal with sustainability factors. This paper provides insights into the current practice of life-cycle cost analysis, and the identification and quantification of sustainability-related cost components in highway projects through literature review, questionnaire surveys and semi-structured interviews. The results can serve as a platform for highway project stakeholders to develop practical tools to evaluate highway investment decisions and reach an optimum balance between financial viability and sustainability deliverables.

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Managing financial implications for sustainable highway infrastructure delivery

Highway construction works have significant bearings on all aspects of sustainability. As they typically involve huge capital funds, stakeholders tend to place all interests on the financial justifications of the project, especially when embedding sustainability principles and practices may demand significant initial investment. Increasing public awareness and government policies demand that infrastructure projects respond to environmental challenges and people start to realise the negative consequences of not to pursue sustainability. Stakeholders are now keen to identify sustainable alternatives and financial implications of including them on a whole lifecycle basis. Therefore tools that aid the evaluation of investment options, such as provision of environmentally sustainable features in roads and highways, are highly desirable. Life-cycle cost analysis (LCCA) is generally recognised as a valuable approach for investment decision making for construction works. However to date it has limited application because the current LCCA models tend to focus on economic issues alone and are not able to deal with sustainability factors. This paper reports a research on identifying sustainability related factors in highway construction projects, in quantitative and qualitative forms of a multi-criteria analysis. These factors are then incorporated into existing LCCA models to produce a new sustainability based LCCA model with cost elements specific to sustainability measures. This presents highway project stakeholders a practical tool to evaluate investment decisions and reach an optimum balance between financial viability and sustainability deliverables.

People capabilities for promoting sustainability in facilities management practices

Sustainability needs to be embedded throughout the life-cycle of a construction project. From project conception, planning, design, construction stage, operation and maintenance to demolition, each phase of development should embrace principles of sustainability and the stakeholder involved should be empowered with the necessary skills. Past research explored the importance of ensuring sustainability measures during the occupancy phase based on considerations of Life-Cycle Cost Analysis and a project’s long-term detrimental impact on the environment. Facility managers are in a unique position to promote sustainability over longer periods of project engagement and can apply a high level of influence on the built assets through management and upgrades. There is growing interest among facility managers in incorporating sustainability measures into day-to-day practice. More, however, needs to be done. Previous studies have identified barriers such as the lack of sustainability knowledge and skills, poor access to information, and unwillingness to change among facility management (FM) practitioners and stakeholders. This inhibits proper implementation of sustainable practices in the FM sector. A number of key factors, such as knowledge discrepancy, time constraints, diversity of FM functions and a lack of incentives, require urgent remedy. The capability of FM professionals and stakeholders will be a key enabler in managing the sustainability agenda, as it is central to the improvement of competency and innovation in an organization. Compared to the attempts at developing sustainability guidelines and performance measurement, research efforts relating to people capabilities and skills are still lagging behind. This paper discusses the progress to date of a research project aimed at formulating a people capabilities framework for sustainable FM practices based on expert opinions and industry feedback. Through literature review, the paper explores the challenges of incorporating sustainability principles into general FM practices before focusing specifically on FM personnel capabilities that may impact on the implementation of a holistic sustainability agenda in real life practice. The results of an industry survey are used to propose an action framework to identify, promote and utilise people capabilities in order to promote sustainability integration in FM practices. The paper provides a useful information source for FM personnel and organizations to bridge the gap between extensive tools on sustainable design and construction assessment at the front end and the need to maintain focus throughout the project life-cycle.

Life-cycle management of construction projects based on virtual prototyping technology

Life-cycle management (LCM) has been employed in the management of construction projects for many years in order to reduce whole life cost, time, risk and improve the service to owners. However, owing to lack of an effective information sharing platform, the current LCM of construction projects is not effectively used in the construction industry. Based upon the analysis of the information flow of LCM, a virutal prototyping (VP)-based communication and collaboration information platform is proposed. Following this, the platform is customized using DASSAULT sofware. The whole process of implementing the VP-based LCM are also discussed and, from a simple case study, it is demonstrated that the VP-based communication and collaboration information platform is an effective tool to support the LCM of construction projects.

Sustainability in road transport : an integrated life cycle analysis for estimating emissions

Despite of a significant contribution of transport sector in the global economy and society, it is one of the largest sources of global energy consumption, green house gas emissions and environmental pollutions. A complete look onto the whole life cycle environmental inventory of this sector will be helpful to generate a holistic understanding of contributory factors causing emissions. Previous studies were mainly based on segmental views which mostly compare environmental impacts of different modes of transport, but very few consider impacts other than the operational phase. Ignoring the impacts of non-operational phases, e.g., manufacture, construction, maintenance, may not accurately reflect total contributions on emissions. Moreover an integrated study for all motorized modes of road transport is also needed to achieve a holistic estimation. The objective of this study is to develop a component based life cycle inventory model which considers impacts of both operational and non-operational phases of the whole life as well as different transport modes. In particular, the whole life cycle of road transport has been segmented into vehicle, infrastructure, fuel and operational components and inventories have been conducted on each component. The inventory model has been demonstrated using the road transport of Singapore. Results show that total life cycle green house gas emissions from the road transport sector of Singapore is 7.8 million tons per year, among which operational phase and non-operational phases contribute about 55% and about 45%, respectively. Total amount of criteria air pollutants are 46, 8.5, 33.6, 13.6 and 2.6 thousand tons per year for CO, SO2, NOx, VOC and PM10, respectively. From the findings, it can be deduced that stringent government policies on emission control measures have a significant impact on reducing environmental pollutions. In combating global warming and environmental pollutions the promotion of public transport over private modes is an effective sustainable policy.

Simple rules to contain an invasive species with a complex life cycle and high dispersal capacity

Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. Synthesis and applications.In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.

Environmental sustainability of urban road transport : an integrated analysis for life cycle emission impact

Despite of significant contributions of urban road transport to global economy and society, it is one of the largest sources of local and global emission impact. In order to address the environmental concerns of urban road transport it is imperative to achieve a holistic understanding of contributory factors causing emissions which requires a complete look onto its whole life cycle. Previous studies were mainly based on segmental views which mostly studied environmental impacts of individual transport modes and very few considered impacts other than operational phase. This study develops an integrated life cycle inventory model for urban road transport emissions from a holistic modal perspective. Singapore case was used to demonstrate the model. Results show that total life cycle greenhouse gas emission from Singapore’s road transport sector is 7.8 million tons per year. The total amount of criteria air pollutants are also estimated in this study.

Life cycle analysis for sustainability assessment of road projects

Road infrastructure has been considered as one of the most expensive and extensive infrastructure assets of the built environment globally. This asset also impacts the natural environment significantly during different phases of life e.g. construction, use, maintenance and end-of-life. The growing emphasis for sustainable development to meet the needs of future generations requires mitigation of the environmental impacts of road infrastructure during all phases of life e.g. construction, operation and end-of-life disposal (as required). Life-cycle analysis (LCA), a method of quantification of all stages of life, has recently been studied to explore all the environmental components of road projects due to limitations of generic environmental assessments. The LCA ensures collection and assessment of the inputs and outputs relating to any potential environmental factor of any system throughout its life. However, absence of a defined system boundary covering all potential environmental components restricts the findings of the current LCA studies. A review of the relevant published LCA studies has identified that environmental components such as rolling resistance of pavement, effect of solar radiation on pavement(albedo), traffic congestion during construction, and roadway lighting & signals are not considered by most of the studies. These components have potentially higher weightings for environment damage than several commonly considered components such as materials, transportation and equipment. This paper presents the findings of literature review, and suggests a system boundary model for LCA study of road infrastructure projects covering potential environmental components.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

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.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

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.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.

Responding to sustainability challenge and cost implications in highway construction projects

Highway construction often requires a significant capital input; therefore it often causes serious financial implications for developers, owners and operators. The recent industry-wide focus on sustainability has added a new dimension to the evaluation of highway projects, particularly on the economical scale of ‘going green’. Comprehensive analysis of the whole-of-life highway development that responds to sustainability challenges is one of the primary concerns for stakeholders. Principles of engineering economics and life cycle costing have been used to determine the incremental capacity investments for highway projects. However, the consideration of costs and issues associated with sustainability is still very limited in current studies on highway projects. Previous studies have identified that highway project investments are primarily concerned with direct market costs that can be quantified through life cycle costing analysis (LCCA). But they tend to ignore costs that are difficult to calculate, as those related to environmental and social elements. On a more positive note, these studies proved that the inclusion of such costs is an essential part of the overall development investment and a primary concern for decision making by the stakeholders. This paper discusses a research attempt to identify and categorise sustainability cost elements for highway projects. Through questionnaire survey, a set of sustainability cost elements on highway projects has been proposed. These cost elements are incorporated into the extension of some of the existing Life Cycle Costing Analysis (LCCA) models in order to produce a holistic financial picture of the highway project. It is expected that a new LCCA model will be established to serve as a suitable tool for decision making for highway project stakeholders.