Advances in predictive maintenance and fault detection for Industry 4.0


Rosario Rosario Morello

Rosario Morello

University Mediterranea of Reggio Calabria, Italy

Zheng Zheng Liu

Zheng Liu

The University of British Columbia, Canada

Rossi Felice Vincenzo Rossi

Felice Vincenzo Rossi

University Mediterranea of Reggio Calabria, Italy


This Special Session intends to encourage submission of original research papers concerning the predictive maintenance, non-invasive diagnostic techniques, and status monitoring applications. Nowadays, transducers and measurement instrumentation are widely used for monitoring status and faults of components and systems. The fault detection and predictive maintenance represent interesting research fields in Industry 4.0 context, nevertheless several perspectives and open research problems have to be investigated such as data processing, sensor failure and reliability, interface and signal treatment standards, fault-tolerance, maintenance, calibration and traceability issues.
Therefore, this Special Session aims to collect manuscripts that will give significant contributions in the field of instrumentation and systems maintenance, fault detection and data processing addressed to reliable and non-invasive diagnosis or monitoring applications. Further topics concern the definition of procedures for maintenance and calibration, reliability and failure assessment.


Main topics include:

  • Predictive maintenance
  • Fault detection
  • Non-invasive sensor-based diagnostic techniques
  • Virtual twins for fault detection
  • Non-invasive monitoring of system performances
  • Sensor array for health status monitoring
  • Sensor data fusion
  • Fault-tolerance and reliability
  • Maintenance and calibration
  • Failure assessment
  • Virtual twins
  • Standards for transducers and sensors

The Special Session aims to provide an overview of advances and the latest novel and emergent technologies, implementations and applications concerning predictive maintenance and fault diagnosis by using transducers and sensors, sensor networks and sensing systems.


Rosario Morello was born in Reggio Calabria, Italy, in 1978. He received the M.Sc. Degree (cum laude) in Electronic Engineering and the Ph.D. Degree in Electrical and Automation Engineering from the University Mediterranea of Reggio Calabria, Italy, in 2002 and 2006, respectively. Since 2005, he has been temporary Professor of Electrical and Electronic Measurements at the Department DIIES of the same University. At the moment, he is Associate Professor and Scientific Director of the Advanced Thermography Center at Dept. DIIES, University Mediterranea of Reggio Calabria, Italy. His main research interests include advanced thermography, the design and characterization of distributed and intelligent measurement systems, wireless sensor network, decision-making problems and measurement uncertainty, process quality assurance, instrumentation reliability and calibration, biomedical applications and statistical signal processing, non-invasive systems, diagnostic algorithms, measurement instrumentation and methodologies related to Industry 4.0. Prof. Morello is a member of the Italian Group of Electrical and Electronic Measurements (GMEE).

Zheng Liu received a Doctorate in engineering from Kyoto University, Kyoto, Japan, in 2000 and a Ph.D. degree from the University of Ottawa, Canada, in 2007. From 2000 to 2001, he was a Research Fellow at Nanyang Technological University, Singapore. He then joined the Institute for Aerospace Research (IAR), National Research Council Canada, Ottawa, ON, Canada, as a Governmental Laboratory Visiting Fellow nominated by NSERC. After being with IAR for 5years, he transferred to the NRC Institute for Research in Construction, where he was a Research Officer. From 2012 to 2015, he worked as a full Professor at Toyota Technological Institute, Nagoya, Japan. He is currently a full professor at the School of Engineering at the University of British Columbia, Okanagan. His research interests include image/data fusion, computer vision, pattern recognition, industrial Internet of Things, digital twin, predictive maintenance, and non-destructive inspection and evaluation. He is a fellow of SPIE and a senior member of IEEE. He holds a Professional Engineer license in British Columbia and Ontario. Dr. Liu serves on the editorial board for journals: IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Mechatronics, IEEE Journal of RFID, Information Fusion, and Machine Vision and Applications.

Felice Vincenzo Rossi was born in Reggio Calabria, Italy, in 1999. He received a bachelor’s Degree (cum laude) in Information Engineering from the University Mediterranea of Reggio Calabria, Italy, in 2021. He’s attending the second year of Master Degree in Electronic Engineering at the Department DIIES of the same University. At the moment, he is conductiong the Thesis working on the use of thermography for detecting blood fingerprints in fabrics. His research interest include the use of thermography in forensic investigation, virtual twins, and predicitive maintenance of systemts and devices by using thermal imaging.


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