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Docente
Alexandre Daniel Batista Martins

Alexandre Daniel Batista Martins
p59***@ulusofona.pt
1818-2BD6-9240
0000-0001-9947-0894

Resume

Alexandre D. B. MArtins has a formation background in Mechanical Engineering. Alexandre Completed a master's degree in Industrial Engineering and Management, where had the opportunity to deepen and acquire broadband Industrial Engineering knowledge. At the moment he is doing the Ph.D. in the same area, focusing on metrology as a support tool for maintaining conditions. At a professional level, Alexandre is working at Lusófuna University as a Teacher and Researcher, been membership of CISE - Electromechatronic Systems Research Center, and EIGeS - Research Centre In Industrial Engineering, Management, and Sustainability, as a Ph.D. researcher.

Graus

  • Licenciatura
    Mechanical Engineering
  • Mestrado
    Industrial Engineering and Management
  • Doutoramento
    Industrial Engineering and Management

Publicações

Journal article

  • 2023-03-11, Predicting the Health Status of a Pulp Press Based on Deep Neural Networks and Hidden Markov Models, Energies
  • 2023-02-21, Online Monitoring of Sensor Calibration Status to Support Condition-Based Maintenance, Sensors
  • 2022-12-12, Automatic Risk Assessment for an Industrial Asset Using Unsupervised and Supervised Learning, Energies
  • 2021-08, Maintenance Prediction through Sensing Using Hidden Markov Models—A Case Study, Applied Sciences
  • 2020-09-17, Calibration and Certification of Industrial Sensors – a Global Review, WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL

Book chapter

  • 2022, Data Analysis for Predictive Maintenance Using Time Series and Deep Learning Models—A Case Study in a Pulp Paper Industry, Springer International Publishing

Conference paper

  • 2021-11, Previsão e Diagnóstico de Avarias de uma Prensa Industrial, com Análise FMECA e Redes Neuronais, 16º Congresso Nacional de Manutenção - APMI, Novembro.
  • 2021-11, Monitorização online para diagnóstico do estado de equipamentos através de Modelos Ocultos de Markov, 16º Congresso Nacional de Manutenção - APMI
  • 2021-10, Data Analysis for Predictive Maintenance Using Time Series and Deep Learning Models – A Case Study in a Pulp Paper Industry, TEPEN 2021 & IncoME-VI
  • 2019-11, Laboratório de Metrologia no apoio à Manutenção de Condição, 15º Congresso Nacional de Manutenção
  • 2019-11, Análise Multivariada de Óleos Lubrificantes, 15º Congresso Nacional de Manutenção - APMI

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