A high level e-maintenance architecture to support on-site teams

Emergent architectures and paradigms targeting reconfigurable manufacturing systems increasingly rely on intelligent modules to maximize the robustness and responsiveness of modern installations. Although intelligent behaviour significantly minimizes the occurrence of faults and breakdowns it does not exclude them nor can prevent equipment’s normal wear. Adequate maintenance is fundamental to extend equipments’ life cycle. It is of major importance the ability of each intelligent device to take an active role in maintenance support. Further this paradigm shift towards “embedded intelligence”, supported by cross platform technologies, induces relevant organizational and functional changes on local maintenance teams. On the one hand, the possibility of outsourcing maintenance activities, with the warranty of a timely response, through the use of pervasive networking technologies and, on the other hand, the optimization of local maintenance staff are some examples of how IT is changing the scenario in maintenance. The concept of e-maintenance is, in this context, emerging as a new discipline with defined socio-economic challenges. This paper proposes a high level maintenance architecture supporting maintenance teams’ management and offering contextualized operational support. All the functionalities hosted by the architecture are offered to the remaining system as network services. Any intelligent module, implementing the services’ interface, can report diagnostic, prognostic and maintenance recommendations that enable the core of the platform to decide on the best course of action.manufacturing systems, platform technologies, maintenance

A high level e-maintenance architecture to support on-site teams

Emergent architectures and paradigms targeting reconfigurable manufacturing systems increasingly rely on intelligent modules to maximize the robustness and responsiveness of modern installations. Although intelligent behaviour significantly minimizes the occurrence of faults and breakdowns it does not exclude them nor can prevent equipment’s normal wear. Adequate maintenance is fundamental to extend equipments’ life cycle. It is of major importance the ability of each intelligent device to take an active role in maintenance support. Further this paradigm shift towards “embedded intelligence”, supported by cross platform technologies, induces relevant organizational and functional changes on local maintenance teams. On the one hand, the possibility of outsourcing maintenance activities, with the warranty of a timely response, through the use of pervasive networking technologies and, on the other hand, the optimization of local maintenance staff are some examples of how IT is changing the scenario in maintenance. The concept of e-maintenance is, in this context, emerging as a new discipline with defined socio-economic challenges. This paper proposes a high level maintenance architecture supporting maintenance teams’ management and offering contextualized operational support. All the functionalities hosted by the architecture are offered to the remaining system as network services. Any intelligent module, implementing the services’ interface, can report diagnostic, prognostic and maintenance recommendations that enable the core of the platform to decide on the best course of action

Maintenance management and operational support as services in reconfigurable manufacturing systems

Emergent architectures and paradigms targeting reconfigurable manufacturing systems increasingly rely on intelligent models to maximize the robustness and responsiveness of modern installations. Although intelligent behaviour significantly minimizes the occurrence of faults and breakdowns it does not exclude them nor can prevent equipment’s normal wear. Adequate maintenance is fundamental to extend equipments’ life cycle. It is of major importance the ability of each intelligent device to take an active role in maintenance support. This paper proposes a maintenance architecture supporting maintenance teams’ management and offering contextualized operational support. All the functionalities hosted by the architecture are offered to the remaining system as network services. Any intelligent module, implementing the services’ interface, can report diagnostic, prognostic and maintenance recommendations that enable the core of the platform to decide on the best course of action

Sistema inteligente de gestão da manutenção e suporte operacional

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e ComputadoresActualmente, a área da manutenção tem assumido um papel cada vez mais relevante na produtividade e organização de uma empresa em questões de sustentabilidade, desempenho, qualidade e ambiente, tendo vindo a ser fundamental no aumento da competitividade e nas mudanças estratégicas face às inconstantes condições do mercado mundial. Graças às recentes evoluções tecnológicas e aos emergentes paradigmas, novas estratégias e métodos de manutenção são concebidos no contexto industrial. A aplicação da inteligência artificial e mecanismos de decisão nos sistemas de manutenção permitem detectar e prever a ocorrência de falhas nos processos de produção, evitando a quebra dos processos produtivos. No entanto, a falta de sistemas de suporte operacional evita o planeamento e uma maior capacidade de resposta dos operadores e técnicos nas operações de manutenção. Esta tese apresenta a concepção de um novo sistema inteligente de gestão de manutenção baseado no paradigma dos agentes e que oferece mecanismos e serviços de suporte operacional

TESTE DE DETERIORAÇÃO CONTROLADA EM SEMENTES DE QUATRO ESPÉCIES DE ORQUÍDEAS PARA AVALIAÇÃO DO COMPORTAMENTO FISIOLÓGICO

Uma alternativa para conservação de espécies é um banco de sementes, onde é possível conservar e propagar estas plantas, porém para isto é necessário se ter uma noção da qualidade das sementes estocadas. Uma alternativa é utilizar testes de vigor, entre eles a deterioração controlada. O objetivo deste trabalho foi avaliar o efeito da deterioração controlada sobre sementes de orquídeas e determinar qual o tempo de exposição destas a este tipo de tratamento. Sementes de Cattleya schilleriana, C. tigrina, C. crispata e C. labiata foram submetidas à deterioração de zero a 48h a 43 °C. As sementes de C. crispata não sofreram deterioração em qualquer momento. As outras três espécies apresentaram redução do índice de velocidade germinação e germinação. O tetrazólio foi menos afetado pela deterioração controlada. Este teste foi eficiente para controlar a qualidade de semente

The value of multiparametric prediction scores in heart failure varies with the type of follow‐up after discharge: a comparative analysis

© 2023 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Aims: Multiple prediction score models have been validated to predict major adverse events in patients with heart failure. However, these scores do not include variables related to the type of follow-up. This study aimed to evaluate the impact of a protocol-based follow-up programme of patients with heart failure regarding scores accuracy for predicting hospitalizations and mortality occurring during the first year after hospital discharge. Methods and results: Data from two heart failure populations were collected: one composed of patients included in a protocol-based follow-up programme after an index hospitalization for acute heart failure and a second one-the control group-composed of patients not included in a multidisciplinary HF management programme after discharge. For each patient, the risk of hospitalization and/or mortality within a period of 12 months after discharge was calculated using four different scores: BCN Bio-HF Calculator, COACH Risk Engine, MAGGIC Risk Calculator, and Seattle Heart Failure Model. The accuracy of each score was established using the area under the receiver operating characteristic curve (AUC), calibration graphs, and discordance calculation. AUC comparison was established by the DeLong method. The protocol-based follow-up programme group included 56 patients, and the control group, 106 patients, with no significant differences between groups (median age: 67 years vs. 68.4 years; male sex: 58% vs. 55%; median ejection fraction: 28.2% vs. 30.5%; functional class II: 60.7% vs. 56.2%, I: 30.4% vs. 31.9%; P = not significant). Hospitalization and mortality rates were significantly lower in the protocol-based follow-up programme group (21.4% vs. 54.7%; P < 0.001 and 5.4% vs. 17.9%; P < 0.001, respectively). When applied to the control group, COACH Risk Engine and BCN Bio-HF Calculator had, respectively, good (AUC: 0.835) and reasonable (AUC: 0.712) accuracy to predict hospitalization. There was a significant reduction of COACH Risk Engine accuracy (AUC: 0.572; P = 0.011) and a non-significant accuracy reduction of BCN Bio-HF Calculator (AUC: 0.536; P = 0.1) when applied to the protocol-based follow-up programme group. All scores showed good accuracy to predict 1 year mortality (AUC: 0.863, 0.87, 0.818, and 0.82, respectively) when applied to the control group. However, when applied to the protocol-based follow-up programme group, a significant predictive accuracy reduction of COACH Risk Engine, BCN Bio-HF Calculator, and MAGGIC Risk Calculator (AUC: 0.366, 0.642, and 0.277, P < 0.001, 0.002, and <0.001, respectively) was observed. Seattle Heart Failure Model had non-significant reduction in its acuity (AUC: 0.597; P = 0.24). Conclusions: The accuracy of the aforementioned scores to predict major events in patients with heart failure is significantly reduced when they are applied to patients included in a multidisciplinary heart failure management programme.This work was supported by national funds, Fundação para a Ciência e a Tecnologia, reference number UIDB/00306/2020.info:eu-repo/semantics/publishedVersio

Non‐invasive telemonitoring improves outcomes in heart failure with reduced ejection fraction : a study in high‐risk patients

© 2020 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of the European Society of Cardiology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Aims: Non-invasive telemonitoring (TM) in patients with heart failure (HF) and reduced left ventricular ejection fraction (HFrEF) may be useful in the early diagnosis of HF decompensation, allowing therapeutic optimization and avoiding re-hospitalization. We describe a TM programme in this population and evaluate its effectiveness during a 12 month period. Methods and results: We conducted a single-centre study of patients discharged from hospital after decompensated HF, allocated into three groups: prospective TM programme, prospective HF protocol follow-up programme (PFP) with no TM facilities, and retrospective propensity-matched usual care (UC). TM effectiveness was assessed by all-cause hospitalizations and mortality; HF-related hospitalization (HFH), days lost to unplanned hospital admissions/death, functional capacity and quality of life (New York Heart Association, Kansas City Cardiomyopathy Questionnaire, 6 min walk test, and plasma N-terminal pro-brain natriuretic peptide) were also evaluated. A total of 125 patients were included [65.9 ± 11.9 years, 32% female, left ventricular ejection fraction 27% (21-32)]. TM was similar to PFP regarding effectiveness; TM reduced all-cause hospitalization and mortality (HR 0.27; 95% CI 0.11-0.71; P < 0.01) and HFH (HR 0.29; 95% CI 0.10-0.89; P < 0.05) as compared with UC. TM reduced the average number of days lost due to unplanned hospital admissions or all-cause death as compared with PFP (5.6 vs. 12.4 days, P < 0.05) and UC (5.6 vs. 48.8 days, P < 0.01). Impact on quality of life was similar between TM and PFP (P = 0.36). Conclusions: In patients with HFrEF and recent HF hospitalization, non-invasive TM reduced 12 month all-cause hospitalization/mortality and HFH as compared with usual care. TM also reduced the number of days lost due to unplanned hospital admission/death as compared with either an optimized protocol-based follow-up programme or usual care.This work was supported by National Health System programme with specific budget attributed to non-invasive TM of HF patients. TM was performed in cooperation with Linde Healthcare®, which had no role in the data interpretation or writing of the report. The corresponding author had full access to all the data in the study and had the final responsibility for the decision to submit for publication.info:eu-repo/semantics/publishedVersio