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.

Human resource behaviour simulation in business processes

The structure and dynamics of a modern business environment are very hard to model using traditional methods. Such complexity raises challenges to effective business analysis and improvement. The importance of applying business process simulation to analyze and improve business activities has been widely recognized. However, one remaining challenge is the development of approaches to human resource behavior simulation. To address this problem, we describe a novel simulation approach where intelligent agents are used to simulate human resources by performing allocated work from a workflow management system. The behavior of the intelligent agents is driven a by state transition mechanism called a Hierarchical Task Network (HTN). We demonstrate and validate our simulator via a medical treatment process case study. Analysis of the simulation results shows that the behavior driven by the HTN is consistent with design of the workflow model. We believe these preliminary results support the development of more sophisticated agent-based human resource simulation systems.

An empirical study of applying ISO 9001 elements in large size Indonesian contractors

The effective implementation of such an ISO 9001 Quality Management System (QMS) in construction companies requires a proper and full implementation of the system to allow companies to improve the way they operate, by this means increasing profitability and market share, producing innovative and sustainable construction products, or improving employee and customer satisfaction. In light of this, this paper discusses the current status of QMS implementation, particularly related to the twenty elements of ISO 9001 within the grade 7 (G-7) category of Indonesian construction companies. A survey was conducted involving 403 respondents from 77 companies, to solicit an evaluation of the current implementation levels of the ISO 9001 elements. The survey findings indicated that for a large percentage of the sector surveyed they had ‘not so fully implemented’ the elements. Scrutiny of the data had also indicated elements that are ‘minimally implemented’, whilst none of the elements fell in the category of ‘fully implemented’. Based on these findings, it is suggested that the G-7 contractors may need to fully commit to practicing control of customer-supplied product and statistical techniques in order to enhance an effective implementation of ISO 9001 elements for ensuring better quality performance. These two elements are recognized as the least implemented of the quality elements.

ThinkLifecycle

Exhibited at The Fashioning the Future Awards Showcase exhibition Fashioning the Future Awards is the leading international cross-disciplinary platform for celebrating innovative initiatives towards fashion design for sustainability, its development and communication. The 2011 awards are a showcase for exceptional work that celebrates ‘Unique’ ways to create our futures. Fashioning the Future is designed and coordinated by the Centre for Sustainable Fashion at London College of Fashion. Unique Enterprise Award The Unique Enterprise Award was offered for the consideration of the opportunities that arise from the necessity to solve the issues around water, waste, wellbeing, energy, equality and biodiversity. Winner Alice Payne According to Alice Payne there is no one-size-fits-all approach to creating a sustainable fashion system. Existing companies will need to evolve, change the way they design and produce garments, offer services rather than products, and engage with the end user to consider the end of life and future lives of their garments. The ThinkLifecycle content management system (CMS) acts as a bridge between existing industry practices and new, redirected practice in which sustainability is at the forefront of commercial thinking. Its chief aim is to embed lifecycle thinking within a company at a daily, operational level.

Improving trust and securing data accessibility for e-health decision making by using data encryption techniques

In the medical and healthcare arena, patients‟ data is not just their own personal history but also a valuable large dataset for finding solutions for diseases. While electronic medical records are becoming popular and are used in healthcare work places like hospitals, as well as insurance companies, and by major stakeholders such as physicians and their patients, the accessibility of such information should be dealt with in a way that preserves privacy and security. Thus, finding the best way to keep the data secure has become an important issue in the area of database security. Sensitive medical data should be encrypted in databases. There are many encryption/ decryption techniques and algorithms with regard to preserving privacy and security. Currently their performance is an important factor while the medical data is being managed in databases. Another important factor is that the stakeholders should decide more cost-effective ways to reduce the total cost of ownership. As an alternative, DAS (Data as Service) is a popular outsourcing model to satisfy the cost-effectiveness but it takes a consideration that the encryption/ decryption modules needs to be handled by trustworthy stakeholders. This research project is focusing on the query response times in a DAS model (AES-DAS) and analyses the comparison between the outsourcing model and the in-house model which incorporates Microsoft built-in encryption scheme in a SQL Server. This research project includes building a prototype of medical database schemas. There are 2 types of simulations to carry out the project. The first stage includes 6 databases in order to carry out simulations to measure the performance between plain-text, Microsoft built-in encryption and AES-DAS (Data as Service). Particularly, the AES-DAS incorporates implementations of symmetric key encryption such as AES (Advanced Encryption Standard) and a Bucket indexing processor using Bloom filter. The results are categorised such as character type, numeric type, range queries, range queries using Bucket Index and aggregate queries. The second stage takes the scalability test from 5K to 2560K records. The main result of these simulations is that particularly as an outsourcing model, AES-DAS using the Bucket index shows around 3.32 times faster than a normal AES-DAS under the 70 partitions and 10K record-sized databases. Retrieving Numeric typed data takes shorter time than Character typed data in AES-DAS. The aggregation query response time in AES-DAS is not as consistent as that in MS built-in encryption scheme. The scalability test shows that the DBMS reaches in a certain threshold; the query response time becomes rapidly slower. However, there is more to investigate in order to bring about other outcomes and to construct a secured EMR (Electronic Medical Record) more efficiently from these simulations.

Project manager competencies in a knowledge-based society

The construction phase of building projects is often a crucial influencing factor in success or failure of projects. Project managers are believed to play a significant role in firms’ success and competitiveness. Therefore, it is important for firms to better understand the demands of managing projects and the competencies that project managers require for more effective project delivery. In a survey of building project managers in the state of Queensland, Australia, it was found that management and information management system are the top ranking competencies required by effective project managers. Furthermore, a significant number of respondents identified the site manager, construction manager and client’s representative as the three individuals whose close and regular contacts with project managers have the greatest influence on the project managers’ performance. Based on these findings, an intra-project workgroups model is proposed to help project managers facilitate more effective management of people and information on building projects.

Workflow resource pattern modelling and visualization

Workflow patterns have been recognized as the theoretical basis to modeling recurring problems in workflow systems. A form of workflow patterns, known as the resource patterns, characterise the behaviour of resources in workflow systems. Despite the fact that many resource patterns have been discovered, people still preclude them from many workflow system implementations. One of reasons could be obscurityin the behaviour of and interaction between resources and a workflow management system. Thus, we provide a modelling and visualization approach for the resource patterns, enabling a resource behaviour modeller to intuitively see the specific resource patterns involved in the lifecycle of a workitem. We believe this research can be extended to benefit not only workflow modelling, but also other applications, such as model validation, human resource behaviour modelling, and workflow model visualization.

Emergency Health Services (EHS) : demand and service delivery models. [Monograph 2 : Queensland EHS users’ profile]

Emergency health is a critical component of Australia’s health system and one which is increasingly congested from growing demand and blocked access to inpatient beds. The Emergency Health Services Queensland (EHSQ) study aims to identify the factors driving increased demand for emergency health and to evaluate strategies which may safely reduce the future demand growth. This monograph addresses the characteristics of users of emergency health services with an aim to identify those that appear to contribute to demand growth. This study utilises data on patients treated by Emergency Departments (ED) and Queensland Ambulance Service (QAS) across Queensland. ED data was derived from the Emergency Department Information System (EDIS) for the period 2001-02 through to 2010-11. Ambulance data was extracted from the QAS’ Ambulance Information Management System (AIMS) and electronic Ambulance Report Form (eARF) for the period 2001-02 through to 2009-10. Due to discrepancies and comparability issues for ED data, this monograph compares data from the 2003-04 time period with 2010-11 data for 21 of the reporting EDs. Also a snapshot of users for the 2010-11 financial year for 31 reporting EDs is used to describe the characteristics of users and to compare those characteristics with population demographics. For QAS data, the 2002-03 and 2009-10 time periods were selected for detailed analyses to identify trends. • Demand for emergency health care services is increasing, representing both increased population and increased relative utilisation. Per capita demand for ED attention has increased by 2% per annum over the last decade and for ambulance attention by 3.7% per annum. • The growth in ED demand is prominent in more urgent triage categories with actual decline in less urgent patients. An estimated 55% of patients attend hospital EDs outside of normal working hours. There is no evidence that patients presenting out of hours are significantly different to those presenting within working hours; they have similar triage assessments and outcomes. • Patients suffering from injuries and poisoning comprise 28% of the ED workload (an increase of 65% in the study period), whilst declines of 32% in cardiovascular and circulatory conditions, and musculoskeletal problems have been observed. • 25.6% of patients attending EDs are admitted to hospital. 19% of admitted patients and 7% of patients who die in the ED are triage category 4 or 5 on arrival. • The average age of ED patients is 35.6 years. Demand has grown in all age groups and amongst both men and women. Men have higher utilisation rates for ED in all age groups. The only group where the growth rate in women has exceeded men is in the 20-29 age group; this growth is particularly in the injury and poisoning categories. • Considerable attention has been paid publicly to ED performance criteria. It is worth noting that 50% of all patients were treated within 33 minutes of arrival. • Patients from lower socioeconomic areas appear to have higher utilisation rates and the utilisation rate for indigenous people appears to exceed those of European and other backgrounds. The utilisation rates for immigrant people is generally less than that of Australian born however it has not been possible to eliminate the confounding impact of different age and socioeconomic profiles. • Demand for ambulance service is also increasing at a rate that exceeds population growth. Utilisation rates have increased by an average of 5% per annum in Queensland compared to 3.6% nationally, and the utilisation rate in Queensland is 27% higher than the national average. • The growth in ambulance utilisation has also been amongst the more urgent categories of dispatch and utilisation rates are higher in rural and regional areas than in the metropolitan area. The demand for ambulance increases with age but the growth in demand for ambulance service has been more prominent in younger age groups. These findings contribute significantly to an understanding of the growth in demand for emergency health. It shows that the growth is amongst patients in genuine need of emergency healthcare and public rhetoric that the congestion of emergency health services is due to inappropriate attendees is unable to be substantiated. The consistency of the growth in demand over the last decade reflects not only the changing demographics of the Australian population but also the changes in health status, standards of acute health care and other social factors. The growth is also amongst patients with acute injury and poisoning which is inconsistent with rates of chronic disease as a fundamental driver. We have also interviewed patients in regard to their decision making choices for acute health care and the factors that influence these decisions and this will be the subject of a third Monograph and publications.

Managing the production of a Cochrane systematic review

Undertaking a Cochrane systematic review can be an incredibly rewarding experience. It is however a challenging and time-consuming task. The Cochrane Handbook for Systematic Reviews of Interventions1 provides an essential resource to help reviewers navigate the often complex methodological issues of systematic review research. Additional guidelines have been developed for those undertaking reviews of public health topics,2 and Cochrane Centres throughout the world offer invaluable training opportunities. This emphasis on training and methodological rigour has helped Cochrane reviews become one of the most respected sources of synthesized research available. Even with the assistance available, however, many authors with good intentions register titles and prepare protocols but fail to publish the completed review. Data extracted from Cochrane’s Information Management System (Archie) in June 2010 showed that there were 1,301 titles registered more than two years ago that have not been published as a full review.3 Of these registered titles, 697 have had protocols published (25 are no longer active) while 604 have not even progressed to this stage (154 are no longer active). There are also 146 protocols that have been published for more than two years without being converted into completed reviews. These registered titles and protocols that have not yet progressed to a completed review represent a significant amount of time and energy invested by review authors, Cochrane editorial staff and, in some cases, external referees...

Whole life cycle costing for Malaysia high-rise residential building : a needs?

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.

The smart skies project : enabling technologies for future airspace environments

This paper summarises the achievements of the Smart Skies Project, a three-year, multi-award winning international project that researched, developed and extensively flight tested four enabling aviation technologies: an electrooptical mid-air collision avoidance system, a static obstacle avoidance system, a mobile ground-based air traffic surveillance system, and a global automated airspace separation management system. The project included the development of manned and unmanned flight test aircraft, which were used to characterise the performance of the prototype systems for a range of realistic scenarios under a variety of environmental conditions. In addition to the collection of invaluable flight data, the project achieved world-firsts in the demonstration of future automated collision avoidance and separation management concepts. This paper summarises these outcomes, the overall objectives of the project, the research and the development of the prototype systems, the engineering of the flight test systems, and the results obtained from flight-testing.

Context-aware device self-configuration using self-organizing maps

Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.

Real-time risk monitoring in business processes : a sensor-based approach

This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.

Assessing the Impact of Sensor Accuracy and Sensor Choice on Air Traffic Conflict Risk Estimation using Risk-Ratio Concepts

One of the primary desired capabilities of any future air traffic separation management system is the ability to provide early conflict detection and resolution effectively and efficiently. In this paper, we consider the risk of conflict as a primary measurement to be used for early conflict detection. This paper focuses on developing a novel approach to assess the impact of different measurement uncertainty models on the estimated risk of conflict. The measurement uncertainty model can be used to represent different sensor accuracy and sensor choices. Our study demonstrates the value of modelling measurement uncertainty in the conflict risk estimation problem and presents techniques providing a means of assessing sensor requirements to achieve desired conflict detection performance.

The growing demand for emergency healthcare

Emergency health is a critical component of health systems; one increasingly congested from growing demand and blocked access to care. The Emergency Health Services Queensland (EHSQ) study aimed to identify the factors driving increased demand for emergency healthcare. This study examined data on patients treated by the ambulance service and Emergency Departments across Queensland. Data was derived from the Queensland Ambulance Service’s (QAS) Ambulance Information Management System and electronic Ambulance Report Form and from the Emergency Department Information System (EDIS). Data was obtained for the period 2001-02 through to 2009-10. A snapshot of users for the 2009-10 year was used to describe the characteristics of users and comparisons made with the year 2003-04 to identify trends. Per capita demand for EDs has increased by 2% per annum over the decade and for ambulance by 3.7% per annum. The growth in ED demand is most significant in more urgent triage categories with decline in less urgent patients. The growth is most prominent amongst patients suffering injuries and poisoning, amongst both men and women and across all age groups. Patients from lower socioeconomic areas appear to have higher utilisation rates and the utilisation rate for indigenous people exceeds those of other backgrounds. The utilisation rates for immigrant people is less than Australian born however it has not been possible to eliminate the confounding impact of age and socioeconomic profiles. These findings contribute to an understanding of the growth in demand for emergency health. It is evident that the growth is amongst patients in genuine need of emergency healthcare and public rhetoric that congested emergency health services is due to inappropriate attendees is unsustainable. The growth in demand over the last decade reflects not only on changing demographics of the Australian population but also changes in health status, standards of acute health care and other social factors.