Building an ontology and process architecture for engineering asset management

Historically, asset management focused primarily on the reliability and maintainability of assets; organisations have since then accepted the notion that a much larger array of processes govern the life and use of an asset. With this, asset management’s new paradigm seeks a holistic, multi-disciplinary approach to the management of physical assets. A growing number of organisations now seek to develop integrated asset management frameworks and bodies of knowledge. This research seeks to complement existing outputs of the mentioned organisations through the development of an asset management ontology. Ontologies define a common vocabulary for both researchers and practitioners who need to share information in a chosen domain. A by-product of ontology development is the realisation of a process architecture, of which there is also no evidence in published literature. To develop the ontology and subsequent asset management process architecture, a standard knowledge-engineering methodology is followed. This involves text analysis, definition and classification of terms and visualisation through an appropriate tool (in this case, the Protégé application was used). The result of this research is the first attempt at developing an asset management ontology and process architecture.

A review on degradation models in reliability analysis

With increasingly complex engineering assets and tight economic requirements, asset reliability becomes more crucial in Engineering Asset Management (EAM). Improving the reliability of systems has always been a major aim of EAM. Reliability assessment using degradation data has become a significant approach to evaluate the reliability and safety of critical systems. Degradation data often provide more information than failure time data for assessing reliability and predicting the remnant life of systems. In general, degradation is the reduction in performance, reliability, and life span of assets. Many failure mechanisms can be traced to an underlying degradation process. Degradation phenomenon is a kind of stochastic process; therefore, it could be modelled in several approaches. Degradation modelling techniques have generated a great amount of research in reliability field. While degradation models play a significant role in reliability analysis, there are few review papers on that. This paper presents a review of the existing literature on commonly used degradation models in reliability analysis. The current research and developments in degradation models are reviewed and summarised in this paper. This study synthesises these models and classifies them in certain groups. Additionally, it attempts to identify the merits, limitations, and applications of each model. It provides potential applications of these degradation models in asset health and reliability prediction.

A review on reliability models with covariates

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

Prognosis of bearing failure based on health state estimation

This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

Emailing experts and novices : effects of knowledge, copy type and testimonials on email advertising effectiveness

In this article we examine how consumer knowledge and two aspects of email ad design (copy type and testimonial type) influence attitudes and purchase intentions. Results from a field experiment reveal differences between experts and novices in their responses to email advertising. Specifically, experts report more favorable evaluations for email advertising than novices. Experts also demonstrate a preference for expert testimonials, when exposed to attribute copy. Yet when benefits-only ad copy was used, experts are most influenced by novice testimonials. In contrast, novice consumers show no copy-testimonial preference. Expert testimonials are also more effective than novice testimonials for expert and novice consumers. We discuss the results with respect to theoretical contributions and managerial implications.

Generalising unitary time evolution

In this third Quantum Interaction (QI) meeting it is time to examine our failures. One of the weakest elements of QI as a field, arises in its continuing lack of models displaying proper evolutionary dynamics. This paper presents an overview of the modern generalised approach to the derivation of time evolution equations in physics, showing how the notion of symmetry is essential to the extraction of operators in quantum theory. The form that symmetry might take in non-physical models is explored, with a number of viable avenues identified.

A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean

Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.

Increasing stochastic perturbations enhances acquisition and learning of complex sport movements

Traditionally, the aquisition of skills and sport movement has been characterised by numerous repetitions of presumed model movement pattern to be acquired by learners. This approach has been questioned by research identifying the presence of individualised movement patterns and the low probability of occurrence of two identical movements within and between individuals. In contrast, the differential learning approach claims advantage for incurring variability in the learning process by adding stochastic perturbations during practice. These ideas are exemplified by data from a high jump experiment which compared the effectiveness of classical and a differential training approach with pre-post test design. Results showed clear advantages for the group with additional stochastic perturbation during the aquisition phase in comparison to classically trained athletes. Analogies to similar phenomenological effects in the neurobiological literature are discussed.

Host searching behaviour of Diachasmimorpha kraussii (Fullaway) (Hymenoptera: Braconidae: Opiinae), a polyphagous parasitoid of Dacinae fruit flies (Diptera: Tephritidae)

Diachasmimorpha kraussii (Hymenoptera: Braconidae: Opiinae) is a koinobiont larval parasitoid of dacine fruit flies of the genus Bactrocera (Diptera: Tephritidae) in its native range (Australia, Papua New Guinea, Solomon Islands). The wasp is a potentially important control agent for pest fruit flies, having been considered for both classical and inundative biological control releases. I investigated the host searching, selection and utilisation mechanisms of the wasp against native host flies within its native range (Australia). Such studies are rare in opiine research where the majority of studies, because of the applied nature of the research, have been carried out using host flies and environments which are novel to the wasps. Diachasmimorpha kraussii oviposited equally into maggots of four fruit fly species, all of which coexist with the wasp in its native range (Australia), when tested in a choice trial using a uniform artificial diet media. While eggs laid into Bactrocera tryoni and B. jarvisi developed successfully through to adult wasps, eggs laid into B. cucumis and B. cacuminata were encapsulated. These results suggest that direct larval cues are not an important element in host selection by D. kraussii. Further exploring how D. kraussii locates suitable host larvae, I investigated the role of plant cues in host searching and selection. This was examined in a laboratory choice trial using uninfested fruit or fruit infested with either B. tryoni or B. jarvisi maggots. The results showed a consistent preference ranking among infested fruits by the wasp, with guava and peach most preferred, but with no response to uninfested fruits. Thus, it appears the wasp uses chemical cues emitted in response to fruit fly larval infestation for host location, but does not use cues from uninfested fruits. To further tease apart the role of (i) suitable and non-suitable maggots, (ii) infested and uninfested fruits of different plant species, and (iii) adult flies, in wasp host location and selection, I carried out a series of behavioural tests where I manipulated these attributes in a field cage. These trials confirmed that D. kraussii did not respond to cues in uninfested fruits, that there were consistent preferences by the wasps for different maggot infested fruits, that fruit preference did not vary depending on whether the maggots were physiologically suitable or not suitable for wasp offspring development, and finally, that adult flies appear to play a secondary role as indicators of larval infestation. To investigate wasp behaviour in an unrestrained environment, I concurrently observed diurnal foraging behaviours of both the wasp and one of its host fly in a small nectarine orchard. Wasp behaviour, both spatially and temporally, was not correlated with adult fruit fly behaviour or abundance. This study reinforced the point that infested fruit seems to be the primary cue used by foraging wasps. Wasp and fly feeding and mating was not observed in the orchard, implying these activities are occurring elsewhere. It is highly unlikely that these behaviours were happening within the orchard during the night as both insects are diurnal. As the final component of investigating host location, I carried out a habitat preference study for the wasp at the landscape scale. Using infested sentinel fruits, I tested the parasitism rate of B. tryoni in eucalyptus sclerophyll forest, rainforest and suburbia in South East Queensland. Although, rainforest is the likely endemic habitat of both B. tryoni and D. kraussii, B. tryoni abundance is significantly greater in suburban environments followed by eucalyptus sclerophyll forest. Parasitism rate was found to be higher in suburbia than in the eucalyptus sclerophyll forest, while no parasitism was recorded in the rainforest. This result suggests that wasps orient within the landscape towards areas of high host density and are not restricted by habitat types. Results from the different experiments suggest that host searching, selection and utilisation behaviour of D. kraussii are strongly influenced by cues associated with fruit fly larval feeding. Cues from uninfested fruits, the host larvae themselves, and the adult host flies play minimal roles. The discussion focuses on the fit of D. kraussii to Vinson’s classical parasitoid host location model and the implications of results for biological control, including recommendations for host and plant preference screening protocols and release regimes.

Wrapped fragments : Drapery, the eighteenth century portrait bust and the male subject

The depiction of drapery (generalised cloth as opposed to clothing) is a well-established convention of Neo-Classical sculpture and is often downplayed by art historians as of purely rhetorical value. It can be argued however that sculpted drapery has served a spectrum of expressive ends, the variety and complexity of which are well illustrated by a study of its use in portrait sculpture. For the Neo-Classical portrait bust, drapery had substantial iconographic and political meaning, signifying the new Enlightenment notions of masculine authority. Within the portrait bust, drapery also served highly strategic aesthetic purposes, alleviating the abruptness of the truncated format and the compromising visual consequences of the “cropped” body. With reference to Joseph Nollekens’ portraits of English statesman Charles James Fox and the author’s own sculptural practice, this paper analyses the Neo-Classical use of drapery to propose that rendered fabric, far from mere stylistic flourish, is a highly charged visual signifier with much scope for exploration in contemporary sculptural practice.

Performance of public private partnerships : an evolutionary perspective

PPPs are held to be a powerful way of mobilising private finance and resources to deliver public infrastructure. Theoretically, research into procurement has begun to acknowledge difficulties with the classification and assessment of different types of procurement, particularly those which do not sufficiently acknowledge variety within specific types of procurement methods. This paper advances a theoretical framework based on an evolutionary economic conceptualisation of a routine, which can accommodate the variety evident in procurement projects, in particular PPPs. The paper tests how the various elements of a PPP, as advanced in the theoretical framework, affect performance across 10 case studies. It concludes, that a limited number of elements of a PPP affect their performance, and provides strong evidence for the theoretical model advanced in this paper.

A differential kinetic spectrophotometric method for determination of three sulphanilamide artificial sweeteners with the aid of chemometrics

A simple and sensitive spectrophotometric method for the simultaneous determination of acesulfame-K, sodium cyclamate and saccharin sodium sweeteners in foodstuff samples has been researched and developed. This analytical method relies on the different kinetic rates of the analytes in their oxidative reaction with KMnO4 to produce the green manganate product in an alkaline solution. As the kinetic rates of acesulfame-K, sodium cyclamate and saccharin sodium were similar and their kinetic data seriously overlapped, chemometrics methods, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the kinetic data. The results showed that the PLS prediction model performed somewhat better. The proposed method was then applied for the determination of the three sweeteners in foodstuff samples, and the results compared well with those obtained by the reference HPLC method.

Multicomponent kinetic spectrophotometric determination of pefloxacin and norfloxacin in pharmaceutical preparations and human plasma samples with the aid of chemometrics

A spectrophotometric method for the simultaneous determination of the important pharmaceuticals, pefloxacin and its structurally similar metabolite, norfloxacin, is described for the first time. The analysis is based on the monitoring of a kinetic spectrophotometric reaction of the two analytes with potassium permanganate as the oxidant. The measurement of the reaction process followed the absorbance decrease of potassium permanganate at 526 nm, and the accompanying increase of the product, potassium manganate, at 608 nm. It was essential to use multivariate calibrations to overcome severe spectral overlaps and similarities in reaction kinetics. Calibration curves for the individual analytes showed linear relationships over the concentration ranges of 1.0–11.5 mg L−1 at 526 and 608 nm for pefloxacin, and 0.15–1.8 mg L−1 at 526 and 608 nm for norfloxacin. Various multivariate calibration models were applied, at the two analytical wavelengths, for the simultaneous prediction of the two analytes including classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), radial basis function-artificial neural network (RBF-ANN) and principal component-radial basis function-artificial neural network (PC-RBF-ANN). PLS and PC-RBF-ANN calibrations with the data collected at 526 nm, were the preferred methods—%RPET not, vert, similar 5, and LODs for pefloxacin and norfloxacin of 0.36 and 0.06 mg L−1, respectively. Then, the proposed method was applied successfully for the simultaneous determination of pefloxacin and norfloxacin present in pharmaceutical and human plasma samples. The results compared well with those from the alternative analysis by HPLC.

Mining trading partners’ preferences for efficient multi-issue bargaining in E‑business

Classical negotiation models are weak in supporting real-world business negotiations because these models often assume that the preference information of each negotiator is made public. Although parametric learning methods have been proposed for acquiring the preference information of negotiation opponents, these methods suffer from the strong assumptions about the specific utility function and negotiation mechanism employed by the opponents. Consequently, it is difficult to apply these learning methods to the heterogeneous negotiation agents participating in e‑marketplaces. This paper illustrates the design, development, and evaluation of a nonparametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. According to our empirical testing, the novel knowledge discovery method can speed up the negotiation processes while maintaining negotiation effectiveness. To the best of our knowledge, this is the first nonparametric negotiation knowledge discovery method developed and evaluated in the context of multi-issue bargaining over e‑marketplaces.

Creating an asset registry for railway electrical traction equipment with open standards

An asset registry arguably forms the core system that needs to be in place before other systems can operate or interoperate. Most systems have rudimentary asset registry functionality that store assets, relationships, or characteristics, and this leads to different asset management systems storing similar sets of data in multiple locations in an organisation. As organisations have been slowly moving their information architecture toward a service-oriented architecture, they have also been consolidating their multiple data stores, to form a “single point of truth”. As part of a strategy to integrate several asset management systems in an Australian railway organisation, a case study for developing a consolidated asset registry was conducted. A decision was made to use the MIMOSA OSA-EAI CRIS data model as well as the OSA-EAI Reference Data in building the platform due to the standard’s relative maturity and completeness. A pilot study of electrical traction equipment was selected, and the data sources feeding into the asset registry were primarily diagrammatic based. This paper presents the pitfalls encountered, approaches taken, and lessons learned during the development of the asset registry.