The identification of Malaysian contractor satisfaction dimensions : a strategy for continuous improvement

The unique characteristics of the construction industry - such as the fragmentation of its processes, varied scope of works and diversity of its participants - are contributory factors to poor project performance. Several issues are unresolved due to the lack of a comprehensive technique to measure project outcomes including: inefficient decision making, insufficient communication, uncertain site conditions, a continuously changing environment, inharmonious working relationships, mismatched objectives within the project team and a blame culture. One approach to overcoming these problems appears to be to measure performance by gauging contractor satisfaction (Co-S) levels, but this has not been widely investigated as yet. Additionally, the key Co-S dimensions at the project level are still not fully identified. ----- ----- This paper concerns a study of satisfaction dimensions, primarily by a postal questionnaire survey of construction contractors registered by the Malaysian Construction Industry Development Board (CIDB). Eight satisfaction dimensions are identified that are significantly and substantially relate to these contractors - comprising: project cost performance, schedule performance, product performance, design satisfaction, site safety, project profitability, business performance and relationships between participants. -Each of these dimensions is accorded different priority levels of satisfaction by different contractors. ----- ----- The output of this study will be useful in raising the awareness and understanding of project teams regarding contractors’ needs, mutual objectives and open communication to help to deliver a successful project.

The use of supply chain management to reduce delays : Malaysian public sector construction projects

Construction delays are a critical problem for Malaysian public sector projects. These delays have been blamed mainly on inefficient traditional construction practices that continue to dominate the current industry. This paper reports the progress to date of a Ph.D. research project aimed at developing a framework to utilize Supply Chain Management (SCM) tools to improve the time performance of Malaysian Government projects. The potential of SCM has been identified for public sector governance and its use in Malaysia is now being considered within the strategy of the Malaysian Construction Industry Master Plan (2006-2015). Encouraged by success in the UK, there is a cautious optimism concerning the successful application of SCM in Malaysia. This paper considers delay as a problem in Malaysian public sector projects, establishes the need to embrace SCM and then elucidates the need and strategies for the development of a delay reduction framework. A literature review, survey mechanism and structured interview schedule will be undertaken to achieve the research objectives. The final research outcome will be a framework that addresses root delay contributors (“pathogens”) and applies SCM tools for their mitigation.

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.

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.

Workflow support for scheduling in surgical care processes

Real-world business processes rely on the availability of scarce, shared resources, both human and non-human. Current workflow management systems support allocation of individual human resources to tasks but lack support for the full range of resource types used in practice, and the inevitable constraints on their availability and applicability. Based on past experience with resource-intensive workflow applications, we derive generic requirements for a workflow system which can use its knowledge of resource capabilities and availability to help create feasible task schedules. We then define the necessary architecture for implementing such a system and demonstrate its practicality through a proof-of-concept implementation. This work is presented in the context of a real-life surgical care process observed in a number of German hospitals.

A superannuation fund as a buyer?

In Bennett v Stewart McMurdo J considered the operation of a contract where the buyer was described as a superannuation fund. The Bennetts signed a standard REIQ contract as buyers of the Stewarts’ house and land. However, the reference schedule to the contract document contained these words next to the word ‘buyer’: ‘Bennett Superannuation Fund’ The Bennetts wished to enforce the contract. In response, the Stewarts (the sellers) raised two issues: • As the ‘Bennett Superannuation Fund’ was a trust and not a distinct legal entity capable of making a contract, the contract did not specify who was the buyer, so that the contract was void for uncertainty; and • The contract was unenforceable as there was no sufficient note or memorandum for the purposes of s 59 of the Property Law Act 1974 (Qld) as s 59 requires, amongst other things, an identification of the parties. McMurdo J did not accept either of these arguments and made an order for specific performance in favour of the Bennetts. Looking at each issue separately:

Changes to the REIQ contract and conveyancing case law update

The Reference Schedule to the REIQ houses and land contract and the lots in a Community Titles Scheme (“CTS”) contract has been amended to contain provision for disclosure concerning the installation of an approved safety switch. This section will not be required to be completed if the land is vacant (in the case of the houses and land contract) or if the present use is a commercial use (in the case of the lots in a CTS contract).

Stakes and motivation in tournaments : playing when there is nothing to play for but pride

Tournaments are an effective means of incentivising participants to ensure an optimal level of effort. However, situations can occur in tournaments where the final outcome of a given competitor does not depend on his/her future performance. Specifically, we study these specific situations in a data set of the group stages of European football club competitions from 1992 to 2009. We identify situations where teams are already sure to finish either first or last at the penultimate stage in the group. We show that such situations affect team performance in the last match, typically decreasing the performance of a team sure to finish first and increasing the performance of a team sure to finish last. The first finding is in line with the economic predictions yet provides interesting implications, namely that the schedule of the match order plays a significant role in the overall performance of the team. The second, counter-intuitive, finding is not well accommodated into the existing economics framework and thus we discuss two alternative explanations, one based on social pressure and the other on pride.

Group maintenance scheduling : a case study for a pipeline network

This paper presents a group maintenance scheduling case study for a water distributed network. This water pipeline network presents the challenge of maintaining aging pipelines with the associated increases in annual maintenance costs. The case study focuses on developing an effective maintenance plan for the water utility. Current replacement planning is difficult as it needs to balance the replacement needs under limited budgets. A Maintenance Grouping Optimization (MGO) model based on a modified genetic algorithm was utilized to develop an optimum group maintenance schedule over a 20-year cycle. The adjacent geographical distribution of pipelines was used as a grouping criterion to control the searching space of the MGO model through a Judgment Matrix. Based on the optimum group maintenance schedule, the total cost was effectively reduced compared with the schedules without grouping maintenance jobs. This optimum result can be used as a guidance to optimize the current maintenance plan for the water utility.

Constructability improvement in sea water intake structure

Purpose The purpose of this paper is to explore the process, and analyse the implementation of constructability improvement and innovation result during the planning and design for sea water intake structure of fertilizer plant project. Design/methodology/approach The research methodology approach is case study method at project level. This constructability improvement process was investigated by using constructability implementation check lists, direct observation, documented lesson learned analysis and key personnel interviews. Findings The case study shows that the implementation of constructability during planning and design stage for this sea water intake structure has increased the project performance as well as improved the schedule by 5 months (14.21%) and reduced the project cost by 15.35%. Research limitations/implications This case study was limited to three (3) previous sea water intake projects as references and one (1) of new method sea water intake structure at fertilizer plant project. Practical implications A constructability improvement check list using theory and lesson learned for the specific construction project was documented. Originality/value The findings support the relevant study of constructability and provide specific lesson learned for three (3) previous project and one (1) of the new innovation method of the construction project and documented by the company.

Subjective and Objective Indicators of Recovery in Severe Mental Illness: a Cross-Sectional Study

Background: This study aimed to determine whether subjective dimensions of recovery such as empowerment are associated with self-report of more objective indicators such as level of participation in the community and income from employment. A secondary aim was to investigate the extent to which diagnosis or other consumer characteristics mediated any relationship between these variables. Methods: The Community Integration Measure, the Empowerment Scale, the Recovery Assessment Scale, and the Camberwell Assessment of Needs Short Appraisal Schedule were administered to a convenience sample of 161 consumers with severe mental illness. Results: The majority of participants had a primary diagnosis of schizophreniform, anxiety/depression or bipolar affective disorder. The Empowerment Scale was quite strongly correlated with the Recovery Assessment Scale and the Community Integration Measure. Participants with a diagnosis of bipolar affective disorder had signifi cantly higher recovery and empowerment scores than participants with schizophrenia or depression. Both empowerment and recovery scores were significantly higher for people engaged in paid employment than for those receiving social security benefits. Conclusions: The measurement of subjective dimensions of recovery such as empowerment has validity in evaluation of global recovery for people with severe mental illness. A diagnosis of bipolar disorder is associated with higher scores on subjective and objective indicators of recovery.

A sequential Monte Carlo approach to design for population pharmacokinetics studies

Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of phase III clinical trials where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalogue of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical phase III clinical trial.

Determinants of rapid weight gain during infancy: Baseline results from the NOURISH randomised controlled trial.

Background: Rapid weight gain in infancy is an important predictor of obesity in later childhood. Our aim was to determine which modifiable variables are associated with rapid weight gain in early life. Methods: Subjects were healthy infants enrolled in NOURISH, a randomised, controlled trial evaluating an intervention to promote positive early feeding practices. This analysis used the birth and baseline data for NOURISH. Birthweight was collected from hospital records and infants were also weighed at baseline assessment when they were aged 4-7 months and before randomisation. Infant feeding practices and demographic variables were collected from the mother using a self administered questionnaire. Rapid weight gain was defined as an increase in weight-for-age Z-score (using WHO standards) above 0.67 SD from birth to baseline assessment, which is interpreted clinically as crossing centile lines on a growth chart. Variables associated with rapid weight gain were evaluated using a multivariable logistic regression model. Results: Complete data were available for 612 infants (88% of the total sample recruited) with a mean (SD) age of 4.3 (1.0) months at baseline assessment. After adjusting for mother's age, smoking in pregnancy, BMI, and education and infant birthweight, age, gender and introduction of solid foods, the only two modifiable factors associated with rapid weight gain to attain statistical significance were formula feeding [OR=1.72 (95%CI 1.01-2.94), P= 0.047] and feeding on schedule [OR=2.29 (95%CI 1.14-4.61), P=0.020]. Male gender and lower birthweight were non-modifiable factors associated with rapid weight gain. Conclusions: This analysis supports the contention that there is an association between formula feeding, feeding to schedule and weight gain in the first months of life. Mechanisms may include the actual content of formula milk (e.g. higher protein intake) or differences in feeding styles, such as feeding to schedule, which increase the risk of overfeeding. Trial Registration: Australian Clinical Trials Registry ACTRN12608000056392

Phase two of the National Credit Reforms : examining the regulation of payday lenders

This study seeks to analyse the adequacy of the current regulation of the payday lending industry in Australia, and consider whether there is a need for additional regulation to protect consumers of these services. The report examines the different regulatory approaches adopted in comparable OECD countries, and reviews alternative models for payday regulation, in particular, the role played by responsible lending. The study also examines the consumer protection mechanisms now in existence in Australia in the National Consumer Credit Protection Act 2009 (Cth) (NCCP) and the National Credit Code (NCC) contained in Schedule 1 of that Act and in the Australian Securities and Investments Commission Act 2001 (Cth).

Application of operations research techniques to improve efficiency in the emergency department

The main aim of this thesis is to analyse and optimise a public hospital Emergency Department. The Emergency Department (ED) is a complex system with limited resources and a high demand for these resources. Adding to the complexity is the stochastic nature of almost every element and characteristic in the ED. The interaction with other functional areas also complicates the system as these areas have a huge impact on the ED and the ED is powerless to change them. Therefore it is imperative that OR be applied to the ED to improve the performance within the constraints of the system. The main characteristics of the system to optimise included tardiness, adherence to waiting time targets, access block and length of stay. A validated and verified simulation model was built to model the real life system. This enabled detailed analysis of resources and flow without disruption to the actual ED. A wide range of different policies for the ED and a variety of resources were able to be investigated. Of particular interest was the number and type of beds in the ED and also the shift times of physicians. One point worth noting was that neither of these resources work in isolation and for optimisation of the system both resources need to be investigated in tandem. The ED was likened to a flow shop scheduling problem with the patients and beds being synonymous with the jobs and machines typically found in manufacturing problems. This enabled an analytic scheduling approach. Constructive heuristics were developed to reactively schedule the system in real time and these were able to improve the performance of the system. Metaheuristics that optimised the system were also developed and analysed. An innovative hybrid Simulated Annealing and Tabu Search algorithm was developed that out-performed both simulated annealing and tabu search algorithms by combining some of their features. The new algorithm achieves a more optimal solution and does so in a shorter time.