Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry

Precise determination of muon and electromagnetic shower contents from shower universality property

We consider two new aspects of Extensive Air Shower development universality allowing to make accurate estimation of muon and electromagnetic (EM) shower contents in two independent ways. In the first case, to get muon (or EM) signal in water Cherenkov tanks or in scintillator detectors it is enough to know the vertical depth of shower maximum and the total signal in the ground detector. In the second case, the EM signal can be calculated from the primary particle energy and the zenith angle. In both cases the parametrizations of muon and EM signals are almost independent on primary particle nature, energy and zenith angle. Implications of the considered properties for mass composition and hadronic interaction studies are briefly discussed. The present study is performed on 28000 of proton, oxygen and iron showers, generated with CORSIKA 6.735 for $E^{-1}$ spectrum in the energy range log(E/eV)=18.5-20.0 and uniformly distributed in cos^2(theta) in zenith angle interval theta=0-65 degrees for QGSJET II/Fluka interaction models.Comment: Submitted to Phys. Rev.

A new multiparametric topological method for determining the primary cosmic ray mass composition in the knee energy region

The determination of the primary cosmic ray mass composition from the characteristics of extensive air showers (EAS), obtained at an observation level in the lower half of the atmosphere, is still an open problem. In this work we propose a new method of the Multiparametric Topological Analysis and show its applicability for the determination of the mass composition of the primary cosmic rays at the PeV energy region.Comment: 8 pages, 4 figures, talk given at Vulcano 2004 Workshop 'Frontier Objects in Physics and Astrophysics', Vulcano, Italy, 24-29.05.04, to be published in the Proceedings of the Worksho

Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry

A cost-benefit approach for the evaluation of prognostics-updated maintenance strategies in complex dynamic systems

The implementation of maintenance strategies which integrate online condition data has the potential to increase availability and reduce maintenance costs. Prognostics techniques enable the implementation of these strategies through up-to-date remaining useful life estimations. However, a cost-benefit assessment is necessary to verify the scale of potential benefits of condition-based maintenance strategies and prognostics for a given application. The majority of prognostics applications focus on the evaluation of a specific failure mode of an asset. However, industrial systems are comprised of different assets with multiple failure modes, which in turn, work in cooperation to perform a system level function. Besides, these systems include time-dependent events and conditional triggering events which cause further effects on the system. In this context not only are the system-level prognostics predictions challenging, but also the cost-benefit analysis of condition-based maintenance policies. In this work we combine asset prognostics predictions with temporal logic so as to obtain an up-to-date system level health estimation. We use asset level and system level prognostics estimations to evaluate the cost-effectiveness of alternative maintenance policies. The application of the proposed approach enables the adoption of conscious trade-off decisions between alternative maintenance strategies for complex systems. The benefits of the proposed approach are discussed with a case study from the power industry

Metric documentation of cultural heritage: Research directions from the Italian gamher project

GAMHer is a collaborative project that aims at exploiting and validating Geomatics algorithms, methodologies and procedures in the framework of new European regulations, which require a more extensive and productive use of digital information, as requested by the Digital Agenda for Europe as one of the seven pillars of the Europe 2020 Strategy. To this aim, GAMHer focuses on the need of a certified accuracy for surveying and monitoring projects with photogrammetry and laser scanning technologies, especially when used in a multiscale approach for landscape and built heritage documentation, conservation, and management. The approach used follows a multi-LoD (level of detail) transition that exploits GIS systems at the landscape scale, BIM technology and "point cloud based" 3d modelling for the scale of the building, and an innovative BIM/GIS integrated approach to foster innovation, promote users' collaboration and encourage communication between users. The outcomes of GAMHer are not intended to be used only by a community of Geomatics specialists, but also by a heterogeneous user community that exploit images and laser scans in their professional activities

Role of PET/CT in the detection of liver metastases from colorectal cancer

The aim of this study was to compare the diagnostic accuracy of 2-[fluorine-18] fluoro-2-deoxy-D-glucose positron emission tomography (F-18-FDG-PET) and computed tomography (CT) with PET/CT in the detection of liver metastases during tumour staging in patients suffering from colorectal carcinoma for the purposes of correct surgical planning and follow-up. A total of 467 patients underwent a PET/CT scan using an iodinated contrast medium. We compared images obtained by the single PET scan, the single CT scan and by the fusion of the two procedures (PET/CT). The final diagnosis was obtained by histological examination and/or by the follow-up of all patients, including those who did not undergo surgery or biopsy. The PET scan had 94.05% sensitivity, 91.60% specificity and 93.36% accuracy; the CT scan had 91.07% sensitivity, 95.42% specificity and 92.29% accuracy. The combined procedures (PET/CT) had the following values: sensitivity 97.92%, specificity 97.71% and accuracy 97.86%. This study indicates that PET/CT is very useful in staging and restaging patients suffering from colorectal cancer. It was particularly useful when recurrences could not be visualised either clinically or by imaging despite increasing tumour markers, as it guaranteed an earlier diagnosis. PET/CT not only provides high diagnostic performance in terms of sensitivity and specificity, enabling modification of patient treatment, but it is also a unique, high-profile procedure that can produce cost savings