Project diagnostics : assessing the condition of projects and identifying poor health combing forces

In many cases, construction projects do not achieve the objectives that the project participants set for them. If participants could better understand how their project is performing overall, at various stages of its delivery, then the opportunities to achieve project success would almost certainly be greater. This paper documents a method of assessing the status of a project, at a point in its design or construction phase, or after completion. The status is assessed in terms of up to seven (7) key success factors. Any evidence of less than adequate performance in these performance areas is scrutinised to seek out the root causes of why this situation is happening. Using these identified root causes of under performance, general suggestions can then be made as to how to return the project to good health. A software package that assists in assessing the status of the project has been developed. The package is currently being calibrated before commercial release.

Project Diagnostics : Providing Successful Project Outcomes

Project Diagnostics is a tool for construction industry stakeholders wishing to improve project delivery and outcomes. This software identifies areas of poor project health, then establishes probable root causes and provides suggested remedial measures. Its focus is to act as an advanced warning system for construction projects that are failing to meet predetermined objectives based on the critical success factors (CSFs) of cost, time, quality, safety, relationships, environment and stakeholder value.

Interview with Dr. Young-Ki Paik, President of the Human Proteome Organization (HUPO): Pharmacoproteomics and the approaching wave of “Proteomics Diagnostics”

Dr. Young-Ki Paik directs the Yonsei Proteome Research Center in Seoul, Korea and was elected as the President of the Human Proteome Organization (HUPO) in 2009. In the December 2009 issue of the Current Pharmacogenomics and Personalized Medicine (CPPM), Dr. Paik explains the new field of pharmacoproteomics and the approaching wave of “proteomics diagnostics” in relation to personalized medicine, HUPO’s role in advancing proteomics technology applications, the HUPO Proteomics Standards Initiative, and the future impact of proteomics on medicine, science, and society. Additionally, he comments that (1) there is a need for launching a Gene-Centric Human Proteome Project (GCHPP) through which all representative proteins encoded by the genes can be identified and quantified in a specific cell and tissue and, (2) that the innovation frameworks within the diagnostics industry hitherto borrowed from the genetics age may require reevaluation in the case of proteomics, in order to facilitate the uptake of pharmacoproteomics innovations. He stresses the importance of biological/clinical plausibility driving the evolution of biotechnologies such as proteomics,instead of an isolated singular focus on the technology per se. Dr. Paik earned his Ph.D. in biochemistry from the University of Missouri-Columbia and carried out postdoctoral work at the Gladstone Foundation Laboratories of Cardiovascular Disease, University of California at San Francisco. In 2005, his research team at Yonsei University first identified and characterized the chemical structure of C. elegans dauer pheromone (daumone) which controls the aging process of this nematode. He is interviewed by a multidisciplinary team specializing in knowledge translation, technology regulation, health systems governance, and innovation analysis.

Incorporating interdependence in risk likelihood analysis to enhance diagnostics in condition monitoring

This research is aimed at addressing problems in the field of asset management relating to risk analysis and decision making based on data from a Supervisory Control and Data Acquisition (SCADA) system. It is apparent that determining risk likelihood in risk analysis is difficult, especially when historical information is unreliable. This relates to a problem in SCADA data analysis because of nested data. A further problem is in providing beneficial information from a SCADA system to a managerial level information system (e.g. Enterprise Resource Planning/ERP). A Hierarchical Model is developed to address the problems. The model is composed of three different Analyses: Hierarchical Analysis, Failure Mode and Effect Analysis, and Interdependence Analysis. The significant contributions from the model include: (a) a new risk analysis model, namely an Interdependence Risk Analysis Model which does not rely on the existence of historical information because it utilises Interdependence Relationships to determine the risk likelihood, (b) improvement of the SCADA data analysis problem by addressing the nested data problem through the Hierarchical Analysis, and (c) presentation of a framework to provide beneficial information from SCADA systems to ERP systems. The case study of a Water Treatment Plant is utilised for model validation.

Taxonomy and diagnostics of fruit fly infesting Opiine Braconids in Australia and the South Pacific

Opiine wasps (Hymenoptera: Braconidae: Opiinae) are parasitoids of dacine fruit flies (Diptera: Tephritidae: Dacinae), the primary horticultural pests of Australia and the South Pacific. Effective use of opiines for biological control of fruit flies is limited by poor taxonomy and identification difficulties. To overcome these problems, this thesis had two aims: (i) to carry out traditional taxonomic research on the fruit fly infesting opine braconids of Australia and the South Pacific; and (ii) to transfer the results of the taxonomic research into user friendly diagnostic tools. Curated wasp material was borrowed from all major Australian museum collections holding specimens. This was supplemented by a large body of material gathered as part of a major fruit fly project in Papua New Guinea: nearly 4000 specimens were examined and identified. Each wasp species was illustrated using traditional scientific drawings, full colour photomicroscopy and scanning electron microscopy. An electronic identification key was developed using Lucid software and diagnostic images were loaded on the web-based Pest and Diseases Image Library (PaDIL). A taxonomic synopsis and distribution and host records for each of the 15 species of dacine-parasitising opiine braconids found in the South Pacific is presented. Biosteres illusorius Fischer (1971) was formally transferred to the genus Fopius and a new species, Fopius ferrari Carmichael and Wharton (2005), was described. Other species dealt with were Diachasmimorpha hageni (Fullaway, 1952), D. kraussii (Fullaway, 1951), D. longicaudata (Ashmead, 1905), D. tryoni (Cameron, 1911), Fopius arisanus (Sonan, 1932), F. deeralensis (Fullaway, 1950), F. schlingeri Wharton (1999), Opius froggatti Fullaway (195), Psyttalia fijiensis (Fullaway, 1936), P. muesebecki (Fischer, 1963), P. novaguineensis (Szépliget, 1900i) and Utetes perkinsi (Fullaway, 1950). This taxonomic component of the thesis has been formally published in the scientific literature. An interactive diagnostics package (“OpiineID”) was developed, the centre of which is a Lucid based multi-access key. Because the diagnostics package is computer based, without the space limitations of the journal publication, there is no pictorial limit in OpiineID and so it is comprehensively illustrated with SEM photographs, full colour photographs, line drawings and fully rendered illustrations. The identification key is only one small component of OpiineID and the key is supported by fact sheets with morphological descriptions, host associations, geographical information and images. Each species contained within the OpiineID package has also been uploaded onto the PaDIL website (www.padil.gov.au). Because the identification of fruit fly parasitoids is largely of concern to fruit fly workers, rather than braconid specialists, this thesis deals directly with an area of growing importance to many areas of pure and applied biology; the nexus between taxonomy and diagnostics. The Discussion chapter focuses on this area, particularly the opportunities offered by new communication and information tools as new ways delivering the outputs of taxonomic science.

Fault diagnostics and supervised testing : How fault diagnostic tools can be proactive?

The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.

Analysis of conical-cylinder shells fundamental characteristics for structural health diagnostics

This paper describes the formulation for the free vibration of joined conical-cylindrical shells with uniform thickness using the transfer of influence coefficient for identification of structural characteristics. These characteristics are importance for structural health monitoring to develop model. This method was developed based on successive transmission of dynamic influence coefficients, which were defined as the relationships between the displacement and the force vectors at arbitrary nodal circles of the system. The two edges of the shell having arbitrary boundary conditions are supported by several elastic springs with meridional/axial, circumferential, radial and rotational stiffness, respectively. The governing equations of vibration of a conical shell, including a cylindrical shell, are written as a coupled set of first order differential equations by using the transfer matrix of the shell. Once the transfer matrix of a single component has been determined, the entire structure matrix is obtained by the product of each component matrix and the joining matrix. The natural frequencies and the modes of vibration were calculated numerically for joined conical-cylindrical shells. The validity of the present method is demonstrated through simple numerical examples, and through comparison with the results of previous researchers.

Beyond barcoding : a mitochondrial genomics approach to molecular phylogenetics and diagnostics of blowflies (Diptera: Calliphoridae)

Members of the Calliphoridae (blowflies) are significant for medical and veterinary management, due to the ability of some species to consume living flesh as larvae, and for forensic investigations due to the ability of others to develop in corpses. Due to the difficulty of accurately identifying larval blowflies to species there is a need for DNA-based diagnostics for this family, however the widely used DNA-barcoding marker, cox1, has been shown to fail for several groups within this family. Additionally, many phylogenetic relationships within the Calliphoridae are still unresolved, particularly deeper level relationships. Sequencing whole mt genomes has been demonstrated both as an effective method for identifying the most informative diagnostic markers and for resolving phylogenetic relationships. Twenty-seven complete, or nearly so, mt genomes were sequenced representing 13 species, seven genera and four calliphorid subfamilies and a member of the related family Tachinidae. PCR and sequencing primers developed for sequencing one calliphorid species could be reused to sequence related species within the same superfamily with success rates ranging from 61% to 100%, demonstrating the speed and efficiency with which an mt genome dataset can be assembled. Comparison of molecular divergences for each of the 13 protein-coding genes and 2 ribosomal RNA genes, at a range of taxonomic scales identified novel targets for developing as diagnostic markers which were 117–200% more variable than the markers which have been used previously in calliphorids. Phylogenetic analysis of whole mt genome sequences resulted in much stronger support for family and subfamily-level relationships. The Calliphoridae are polyphyletic, with the Polleninae more closely related to the Tachinidae, and the Sarcophagidae are the sister group of the remaining calliphorids. Within the Calliphoridae, there was strong support for the monophyly of the Chrysomyinae and Luciliinae and for the sister-grouping of Luciliinae with Calliphorinae. Relationships within Chrysomya were not well resolved. Whole mt genome data, supported the previously demonstrated paraphyly of Lucilia cuprina with respect to L. sericata and allowed us to conclude that it is due to hybrid introgression prior to the last common ancestor of modern sericata populations, rather than due to recent hybridisation, nuclear pseudogenes or incomplete lineage sorting.

A new procedure for using envelope analysis for rolling element bearing diagnostics in variable operating conditions

In the field of rolling element bearing diagnostics envelope analysis, and in particular the squared envelope spectrum, have gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of squared envelope spectrum has been extended to cases in which small speed fluctuations occur, maintaining the effectiveness and efficiency that characterize this successful technique. However, the constraint on speed has to be removed completely, making envelope analysis suitable also for speed and load transients, to implement an algorithm valid for all the industrial application. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This paper is aimed at providing and testing a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Bearing Fault Diagnostics Using the Spectral Pattern Recognition

In the field of diagnostics of rolling element bearings, the development of sophisticated techniques, such as Spectral Kurtosis and 2nd Order Cyclostationarity, extended the capability of expert users to identify not only the presence, but also the location of the damage in the bearing. Most of the signal-analysis methods, as the ones previously mentioned, result in a spectrum-like diagram that presents line frequencies or peaks in the neighbourhood of some theoretical characteristic frequencies, in case of damage. These frequencies depend only on damage position, bearing geometry and rotational speed. The major improvement in this field would be the development of algorithms with high degree of automation. This paper aims at this important objective, by discussing for the first time how these peaks can draw away from the theoretical expected frequencies as a function of different working conditions, i.e. speed, torque and lubrication. After providing a brief description of the peak-patterns associated with each type of damage, this paper shows the typical magnitudes of the deviations from the theoretical expected frequencies. The last part of the study presents some remarks about increasing the reliability of the automatic algorithm. The research is based on experimental data obtained by using artificially damaged bearings installed in a gearbox.