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

An RFID application for the process mapping automation

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A decentralized application for the traceability process in the pharma industry

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Dynamic failure rate model of an electric motor comparing the Military Standard and Svenska Kullagerfabriken (SKF) methods

Abstract Electric motors are industrial systems' components widely diffused enabling all productive processes and safety equipment. They are affected by aging effect with a contribution based on the environmental condition on which they work. In order to design efficient maintenance plans, the behaviour of their main components, such as bearings and winding, has to be predicted. Therefore, a model-based methodology is applied aiming at codifying the failure rate of an electric engine, taking into account the thermal aging and relevant environment boundary conditions in which bearings and winding operate. The winding failure mode is coded by means of the Military standard technique while the bearings one is simulated comparing the Military Standard and the Svenska Kullagerfabriken (SKF) techniques. While the former predicts more conservative behaviours, the latter, taking into account lubrication conditions, dynamic loads and a better knowledge of materials quality, enables to capture the evolution of the operative conditions. The proposed reliability model can capture both the deterministic and stochastic behaviour of the electric motor: it belongs to the field of hybrid automaton application; the model is coded by means of the emerging software framework called SHYFTOO. The proposed model and the Monte Carlo simulation process that performs its evolution can support the development of a new class of electric motors: a cyber-physical oriented electric motor

Performance assessment of domestic photovoltaic power plant with a storage system

Grid-connected low voltage photovoltaic power plants cover the majority of the power capacity installed in Italy. They offer an important contribution to the power demand of the utilities connected but, due to the nature of the solar resource, the night time consumption can be satisfied only withdrawing the energy by the national grid, at the price of the energy distributor. Thanks to the improvement of storage technologies and the decreasing of costs, the installation of a system of battery looks a promising solution. In this paper, a model-based approach to analyze and discuss the performance of a domestic photovoltaic power plant with a storage system is presented

On the use of dynamic reliability for an accurate modelling of renewable power plants

Renewable energies are a key element of the modern sustainable development. They play a key role in contributing to the reduction of the impact of fossil sources and to the energy supply in remote areas where the electrical grid cannot be reached. Due to the intermittent nature of the primary renewable resource, the feasibility assessment, the performance evaluation and the lifecycle management of a renewable power plant are very complex activities. In order to achieve a more accurate system modelling, improve the productivity prediction and better plan the lifecycle management activities, the modelling of a renewable plant may consider not only the physical process of energy transformation, but also the stochastic variability of the primary resource and the degradation mechanisms that affect the aging of the plant components resulting, eventually, in the failure of the system. This paper presents a modelling approach which integrates both the deterministic and the stochastic nature of renewable power plants using a novel methodology inspired from reliability engineering: the Stochastic Hybrid Fault Tree Automaton. The main steps for the design of a renewable power plant are discussed and implemented to estimate the energy production of a real photovoltaic power plant by means of a Monte Carlo simulation process. The proposed approach, modelling the failure behavior of the system, helps also with the evaluation of other key performance indicators like the power plant and the service availability

Cooperative Binding of the Cationic Porphyrin Tris-T4 Enhances Catalytic Activity of 20S Proteasome Unveiling a Complex Distribution of Functional States

The present study provides new evidence that cationic porphyrins may be considered as tunable platforms to interfere with the structural "key code" present on the 20S proteasome α-rings and, by consequence, with its catalytic activity. Here, we describe the functional and conformational effects on the 20S proteasome induced by the cooperative binding of the tri-cationic 5-(phenyl)-10,15,20-(tri N-methyl-4-pyridyl) porphyrin (Tris-T4). Our integrated kinetic, NMR, and in silico analysis allowed us to disclose a complex effect on the 20S catalytic activity depending on substrate/porphyrin concentration. The analysis of the kinetic data shows that Tris-T4 shifts the relative populations of the multiple interconverting 20S proteasome conformations leading to an increase in substrate hydrolysis by an allosteric pathway. Based on our Tris-T4/h20S interaction model, Tris-T4 is able to affect gating dynamics and substrate hydrolysis by binding to an array of negatively charged and hydrophobic residues present on the protein surface involved in the 20S molecular activation by the regulatory proteins (RPs). Accordingly, despite the fact that Tris-T4 also binds to the α3ΔN mutant, allosteric modulation is not observed since the molecular mechanism connecting gate dynamics with substrate hydrolysis is impaired. We envisage that the dynamic view of the 20S conformational equilibria, activated through cooperative Tris-T4 binding, may work as a simplified model for a better understanding of the intricate network of 20S conformational/functional states that may be mobilized by exogenous ligands, paving the way for the development of a new generation of proteasome allosteric modulators

Risk factors associated with adverse fetal outcomes in pregnancies affected by Coronavirus disease 2019 (COVID-19): a secondary analysis of the WAPM study on COVID-19.

Objectives To evaluate the strength of association between maternal and pregnancy characteristics and the risk of adverse perinatal outcomes in pregnancies with laboratory confirmed COVID-19. Methods Secondary analysis of a multinational, cohort study on all consecutive pregnant women with laboratory-confirmed COVID-19 from February 1, 2020 to April 30, 2020 from 73 centers from 22 different countries. A confirmed case of COVID-19 was defined as a positive result on real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of nasal and pharyngeal swab specimens. The primary outcome was a composite adverse fetal outcome, defined as the presence of either abortion (pregnancy loss before 22 weeks of gestations), stillbirth (intrauterine fetal death after 22 weeks of gestation), neonatal death (death of a live-born infant within the first 28 days of life), and perinatal death (either stillbirth or neonatal death). Logistic regression analysis was performed to evaluate parameters independently associated with the primary outcome. Logistic regression was reported as odds ratio (OR) with 95% confidence interval (CI). Results Mean gestational age at diagnosis was 30.6+/-9.5 weeks, with 8.0% of women being diagnosed in the first, 22.2% in the second and 69.8% in the third trimester of pregnancy. There were six miscarriage (2.3%), six intrauterine device (IUD) (2.3) and 5 (2.0%) neonatal deaths, with an overall rate of perinatal death of 4.2% (11/265), thus resulting into 17 cases experiencing and 226 not experiencing composite adverse fetal outcome. Neither stillbirths nor neonatal deaths had congenital anomalies found at antenatal or postnatal evaluation. Furthermore, none of the cases experiencing IUD had signs of impending demise at arterial or venous Doppler. Neonatal deaths were all considered as prematurity-related adverse events. Of the 250 live-born neonates, one (0.4%) was found positive at RT-PCR pharyngeal swabs performed after delivery. The mother was tested positive during the third trimester of pregnancy. The newborn was asymptomatic and had negative RT-PCR test after 14 days of life. At logistic regression analysis, gestational age at diagnosis (OR: 0.85, 95% CI 0.8-0.9 per week increase; pPeer reviewe

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks