Effectiveness of constructability concept in the provision of infrastructure assets

The concept of constructability is to use construction knowledge and experience during all phases of a project, particularly in the earliest phases of planning and design. It facilitates project objectives before delivery stage, and decreases unnecessary costs during construction phase. Despite the extensive use, constructability concept fails to address many issues related to Operation and Maintenance (O&M) of construction projects. Extending constructability concept, to include the O&M issues, could lead to the projects that are not fitted for construction purposes only, but also fitted for use. This study reviews the literature of constructability implementation, its benefits and shortcomings during the infrastructure life cycle, as well as the delivery success factors of infrastructure projects. This contributes to the propose need of a model to improve the effectiveness and efficiency of infrastructure project by extending the concept of constructability to include O&M. Development of such a model can facilitate post-occupancy stakeholders’ participation in a constructability program. It will help infrastructure owners eliminate project reworks, and improve O&M effectiveness and efficiency.

Engaging operations management students by designing the unit with industry focus

Operations management is an area concerned with the production of goods and services ensuring that business operations are efficient in utilizing resource and effective to meet customer requirements. It deals with the design and management of products, processes, services and supply chains and considers the acquisition, development, and effective and efficient utilization of resources. Unlike other engineering subjects, content of these units could be very wide and vast. It is therefore necessary to cover the content that is most related to the contemporary industries. It is also necessary to understand what engineering management skills are critical for engineers working in the contemporary organisations. Most of the operations management books contain traditional Operations Management techniques. For example ‘inventory management’ is an important topic in operations management. All OM books deal with effective method of inventory management. However, new trend in OM is Just in time (JIT) delivery or minimization of inventory. It is therefore important to decide whether to emphasise on keeping inventory (as suggested by most books) or minimization of inventory. Similarly, for OM decisions like forecasting, optimization and linear programming most organisations now a day’s use software. Now it is important for us to determine whether some of these software need to be introduced in tutorial/ lab classes. If so, what software? It is established in the Teaching and Learning literature that there must be a strong alignment between unit objectives, assessment and learning activities to engage students in learning. Literature also established that engaging students is vital for learning. However, engineering units (more specifically Operations management) is quite different from other majors. Only alignment between objectives, assessment and learning activities cannot guarantee student engagement. Unit content must be practical oriented and skills to be developed should be those demanded by the industry. Present active learning research, using a multi-method research approach, redesigned the operations management content based on latest developments in Engineering Management area and the necessity of Australian industries. The redesigned unit has significantly helped better student engagement and better learning. It was found that students are engaged in the learning if they find the contents are helpful in developing skills that are necessary in their practical life.

Malaysia high-rise residential property management : 2004-2010 trends and scenario

Property management requires an understanding of infrastructure management, service life planning and quality management. Today, people are beginning to realize that effective property management in high-rise residential property can sustain the property value and maintaining high returns on their investment. The continuous growth of high-rise residential properties indicates that there is a need for an effective property management system to provide a sustainable high-rise residential property development. As intensive as these studies are, they do not attempt to investigate the correlation between property management systems with the trends of Malaysia high-rise residential property development. By examining the trends and scenario of Malaysia high-rise residential property development, this paper aims to gain an understanding of impacts from the effectiveness of property management in this scope area. Findings from this scoping paper will assist in providing a greater understanding and possible solutions for the current Malaysian property management systems for the expanding high-rise residential unit market. With current high rise units in excess of 1.3 million and increasing, the need for more cost effective management systems are of highly important to the Malaysian Property Industry.

Extending constructability concept to include operation and maintenance issues

The concept of constructability uses integration art of individual functions through a valuable and timely construction inputs into planning and design development stages. It results in significant savings in cost and time needed to finalize infrastructure projects. However, available constructability principles, developed by CII Australia (1993), do not cover Operation and Maintenance (O&M) phases of projects, whilst major cost and time in multifaceted infrastructure projects are spent in post-occupancy stages. This paper discusses the need to extend the constructability concept by examining current O&M issues in the provision of multifaceted building projects. It highlights available O&M problems and shortcomings of building projects, as well as their causes and reasons in different categories. This initial categorization is an efficient start point for testing probable present O&M issues in various cases of complex infrastructure building projects. This preliminary categorization serve as a benchmark to develop an extended constructability model that considers the whole project life cycle phases rather than a specific phase. It anticipates that the development of an extended constructability model can reduce significant number of reworks, mistakes, extra costs and time wasted during delivery stages of multifaceted building projects.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Novel corrosion sensor based on carbon nanotube composites for structural health monitoring

Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Hence, there is an urgent need to monitor our infrastructures to prolong their life span, at the same time catering for heavier and faster moving traffics. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for structural health monitoring. The CNTs, a key material in nanotechnology has aroused great interest in the research community due to their remarkable mechanical, electrochemical, piezoresistive and other physical properties. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties when subjected to chemical solutions, to simulate a chemical reaction due to corrosion and real life corrosion experimental tests. The electrical resistance of the sensor electrode was dramatically changed due to corrosion. The novel sensor is expected to effectively detect corrosion in structures based on the measurement of electrical impedances of the CNT composite.

An integrated knowledge management framework for managing sustainability knowledge in the Australian infrastructure sector

In Australia, it has been increasingly accepted that sustainability needs to be at the top of the agenda when contemplating infrastructure development. In practice however, many companies struggle to find effective ways to embrace sustainable ideas and implement them in real projects beyond minimum compliance. One of the reasons is the lack of underpinning knowledge and evidence to demonstrate and measure the linkage between sustainability implementations and the relevant outcomes. This is compounded by the fact that very often there are no common understandings between the stakeholders on sustainability and there is a big divide between research advancement and real-life applications. Therefore it is both feasible and timely to develop and expand the body of sustainability knowledge on infrastructure development and investigate better ways of communicating with and managing it within the infrastructure sector. Although knowledge management (KM) is a relatively new and emerging discipline, it has shown its value and promise in existing applications in the construction industry. Considering the existing KM mechanisms and tools employed in practice, this research is aimed at establishing a specific KM approach to facilitate sustainability knowledge identification, acquisition, sharing, maintenance and application within the infrastructure sector, and promote integrated decision-making for sustainable infrastructure development. A triangulation of questionnaire survey, semi-structured interviews and case studies was employed in this research to collect required qualitative and quantitative data. The research studied the unique characteristics of the infrastructure sector, the nature of sustainability knowledge, and evaluated and validated the critical elements, key processes, and priority issues of KM for the Australian infrastructure sector. A holistic KM framework was developed to set the overall context for managing sustainability knowledge in the infrastructure sector by outlining (1) the main aims and outcomes of managing sustainability knowledge, (2) the key knowledge activities, (3) effective KM strategies and instruments, and (4) KM enablers. Because of the highly project-oriented nature of the infrastructure sector, knowledge can only add value when it is being used in real projects. Implementation guidelines were developed to help the industry practitioners and project teams to apply sustainability knowledge and implement KM in infrastructure project scenarios. This research provides the Australian infrastructure sector with tools to better understand KM, helps the industry practitioners to prioritize attention on relevant sustainability issues, and recommends effective practices to manage sustainability knowledge, especially in real life implementation of infrastructure projects.

Relationship management as a strategy for supply chain engagement in the civil engineering construction industry

Many studies into construction procurement methods reveal evidence of a need to change the culture and attitude in the construction industry, transition from traditional adversarial relationships to cooperative and collaborative relationships. At the same time there is also increasing concern and discussion on alternative procurement methods, involving a movement away from traditional procurement systems. Relational contracting approaches, such as partnering and relationship management, are business strategies that align the objectives of clients, commercial participants and stakeholders. It provides a collaborative environment and a framework for all participants to adapt their behaviour to project objectives and allows for engagement of those subcontractors and suppliers down the supply chain. The efficacy of relationship management in the client and contractor groups is proven and well documented. However, the industry has a history of slow implementation of relational contracting down the supply chain. Furthermore, there exists little research on relationship management conducted in the supply chain context. This research aims to explore the association between relational contracting structures and processes and supply chain sustainability in the civil engineering construction industry. It endeavours to shed light on the practices and prerequisites for relationship management implementation success and for supply sustainability to develop. The research methodology is a triangulated approach based on Cheung.s (2006) earlier research where questionnaire survey, interviews and case studies were conducted. This new research includes a face-to-face questionnaire survey that was carried out with 100 professionals from 27 contracting organisations in Queensland from June 2008 to January 2009. A follow-up survey sub-questionnaire, further examining project participants. perspectives was sent to another group of professionals (as identified in the main questionnaire survey). Statistical analysis including multiple regression, correlation, principal component factor analysis and analysis of variance were used to identify the underlying dimensions and test the relationships among variables. Interviews and case studies were conducted to assist in providing a deeper understanding as well as explaining findings of the quantitative study. The qualitative approaches also gave the opportunity to critique and validate the research findings. This research presents the implementation of relationship management from the contractor.s perspective. Findings show that the adaption of relational contracting approach in the supply chain is found to be limited; contractors still prefer to keep the suppliers and subcontractors at arm.s length. This research shows that the degree of match and mismatch between organisational structuring and organisational process has an impact on staff.s commitment level and performance effectiveness. Key issues affecting performance effectiveness and relationship effectiveness include total influence between parties, access to information, personal acquaintance, communication process, risk identification, timely problem solving and commercial framework. Findings also indicate that alliance and Early Contractor Involvement (ECI) projects achieve higher performance effectiveness at both short-term and long-term levels compared to projects with either no or partial relationship management adopted.

Preliminary study on bridge health prediction using Dynamic Objective Oriented Bayesian Network (DOOBN)

The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

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.

Market Trend Analysis of Purpose Built Office (PBO) in Malaysia

The purpose of this paper is to explore the trend of Purpose Built Office (PBO) supply and occupancy in Malaysia. In achieving this, the number of PBO supply by the private sector in the market is compared with the government sector to gain an understanding of the current emerging market for the PBO. There have been limited studies in Malaysia comparing the trend supply and occupancy of PBOs by both sectors. This paper outcome will illustrate the needs for public sector asset management in Malaysia, particularly for PBOs. An analytical framework is developed using time series to measure the level of supply and occupancy of PBO by both sectors, indicating the percentage of government’s PBO compared to the total numbers of PBOs in the market from 2004 to 2010

Simulation of AE wave propagation in thin plate for source identification

In most materials, short stress waves are generated during the process of plastic deformation, phase transformation, crack formation and crack growth. These phenomena are applied in acoustic emission (AE) for the detection of material defects in wide spectrum areas, ranging from non-destructive testing for the detection of materials defects to monitoring of microeismical activity. AE technique is also used for defect source identification and for failure detection. AE waves consist of P waves (primary/longitudinal waves), S waves (shear/transverse waves) and Rayleight (surface) waves as well as reflected and diffracted waves. The propagation of AE waves in various modes has made the determination of source location difficult. In order to use the acoustic emission technique for accurate identification of source location, an understanding of wave propagation of the AE signals at various locations in a plate structure is essential. Furthermore, an understanding of wave propagation can also assist in sensor location for optimum detection of AE signals. In real life, as the AE signals radiate from the source it will result in stress waves. Unless the type of stress wave is known, it is very difficult to locate the source when using the classical propagation velocity equations. This paper describes the simulation of AE waves to identify the source location in steel plate as well as the wave modes. The finite element analysis (FEA) is used for the numerical simulation of wave propagation in thin plate. By knowing the type of wave generated, it is possible to apply the appropriate wave equations to determine the location of the source. For a single plate structure, the results show that the simulation algorithm is effective to simulate different stress waves.

Integrated approach for HP-LNG pump diagnosis and prognostics based on health state probability estimation

This paper presents an innovative prognostics model based on health state probability estimation embedded in the closed loop diagnostic and prognostic system. To employ an appropriate classifier for health state probability estimation in the proposed prognostic model, the comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault levels of three faults in HP-LNG pump. Two sets of impeller-rubbing data were employed for the prediction of pump remnant life based on estimation of discrete health state probability using an outstanding capability of SVM and a feature selection technique. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Project management governance : a situational approach

The purpose of this paper is to show how project management governance is addressed through the use of a specific meta-method. Governance is defined here on two criteria: accountability and performance. Accountability is promoted through transparency and performance is promoted by responsive and responsible decision-making. According to a systemic perspective, transparency and decision-making involve having information, tacit or explicit knowledge, as well as understanding of the context, the different parameters and variables, their interaction and conditions of change. Although this method of methods was built according a heuristic process involving 25 years of various researches and consulting activities, it seems appropriate to draw its foundations. I clarify first my epistemological position and the notion of project and project management, as Art and Science. This lead me to define a "Be" / "Have" posture to this regards. Then, the main theoretical roots of MAP Method are exposed: Boisot' s Social Learning Cycle, Praxeology and Theory of Convention. Then we introduced the main characteristics of the method and the 17 methods and tools constituting MAP "tool box", thus with regard to the project management governance perspective. Finally, I discuss the integration of two managerial modes (operational and project modes) and the consequence in term of governance in a specific socio-techno-economic project/context ecosystem.