Special Session 2

SPECIAL SESSION #2

Digitalisation of Measurements for Industrial Processes: Enabling Smart and Sustainable Manufacturing

Francesco Pilati

Department of Industrial Engineering - University of Trento

• francesco.pilati@unitn.it

Francesca Calabrese

Department of Industrial Engineering - University of Trento

• francesca.calabrese@unitn.it

Francesco Picriello

University of Sannio

• fpicariello@unisannio.it

The digitalisation of industrial processes through advanced measurement systems is pivotal for achieving smarter, more efficient, and sustainable manufacturing in the Industry 4.0 and Industry 5.0 paradigms. Measurements are no longer mere tools for monitoring but are now integral to optimizing and automating complex industrial workflows.

This special session focuses on the role of digitalised measurements in driving innovation within industrial processes. Topics include industrial and virtual sensors, IoT-enabled measurement systems, wireless sensor networks, and the integration of measurement data into smart manufacturing ecosystems. The session will also explore the application of digitalisation to foster circular and sustainable industrial practices, including the use of advanced localization technologies and artificial intelligence (AI) and machine learning (ML) techniques for process optimization.

Key areas of interest include:

• IoT-based measurement applications in industrial processes
• Virtual sensors and digital twins for process optimization
• Sensors for sustainable manufacturing and circular approaches
• Wearables and sensor networks for human-centric industrial processes
• Digitalisation of ergonomic indices to improve workplace safety
• Artificial intelligence (AI) and machine learning (ML) applications for the digital transformation of industrial processes

This session invites submissions addressing innovative solutions, case studies, and theoretical advancements in the use of measurements for the digitalisation of industrial processes. By fostering interdisciplinary collaboration, the session aims to highlight the transformative impact of metrology on the future of manufacturing and industrial ecosystems.

Francesco Pilati
Associate Professor at the Department of Industrial Engineering - University of Trento and local coordinator for the scientific field ING-IND/17 Industrial plants and Logistic systems. Chair of the research group in Industrial plants, Production systems and Logistics of the University of Trento.
Coordinator of the Master degree programme in Management and Industrial Systems Engineering of the University of Trento.
Invited lecturer at the University of Vienna (Austria) for the Faculty of Business, Economics and Statistics for Advanced Operations Management course.
Visiting Scholar at the School of Industrial Engineering & Management, Oklahoma State University (Stillwater, Oklahoma, USA) for a semester within the Ph.D. program.
From 2016 to October 2019 Post-doctoral research fellow at the Department of Industrial Engineering of the University of Bologna, research group in Industrial Mechanical Plants.
National scientific habilitation for the position of Associate Professor, academic recruitment field 09/B2 - Industrial mechanical systems engineering, obtained in 2018.
PhD in Mechatronic Engineering and Product Mechanical Innovation - Curriculum in Industrial Plants and Logistics at the University of Padua obtained in 2016 with a thesis entitled "Multi-objective models and methods for design and management of sustainable logistic systems".
Main research activities deal with the development and application to different topics of techniques and tools such as multi-objective optimisation and environmental impact assessment. These techniques are used to integrate environmental sustainability aspects with technical-economic criteria for the design and management of distribution networks, warehousing systems, manufacturing and assembly lines as well as energy production plants. Finally, the research activity is completed with experimental and prototyping activities developed in laboratory concerning hardware/software architectures to digitize manual production processes through depth cameras.

Francesca Calabrese is currently an Assistant Professor in the Department of Industrial Engineering at the University of Trento. She earned her B.Sc. (2015) and M.Sc. (2017, cum laude) in Management Engineering from the University of Bologna. Following this, she joined the research activities at the Department of Industrial Engineering at the University of Bologna. In 2020, she was a visiting scholar at the Department of Industrial Systems Engineering and Management at the National University of Singapore (NUS) for a quarter within the Ph.D. program. In 2021, she received her Ph.D. in Mechanics and Advanced Engineering Science from the University of Bologna. In June 2023, she obtained the National Scientific Habilitation for the position of Associate Professor, academic recruitment field 09/B2 - Industrial Mechanical Systems. Her research interests include condition-based maintenance, predictive maintenance of industrial machinery, edge-cloud solutions for real-time monitoring and sensor data analysis, deep learning models for pattern recognition and future health state prediction, high-variety management in manufacturing, and human factors in logistics and warehouse operations. She has authored and co-authored several scientific papers published in international journals and conference proceedings and serves as a reviewer for various international journals and conferences.

Francesco Picariello received the B.Sc. ('09) and M.Sc. ('12) (cum laude) degree in electronic engineering from the University of Salerno, Faculty of Engineering. Then, he joined the research activities carried out at the Laboratory of Signal Processing and Measurement Information of the University of Sannio, Benevento, Italy. He received the IEEE Instrumentation and Measurement Society Graduate Fellowship Award in 2015 for the project titled "Assurance of traceability for smartphone-based kinetic measurements". He received the Ph.D. in Information Engineering from the University of Sannio in 2016 and the National Academic Qualification as Associate Professor in June 2020. He is currently working in the Department of Engineering at the University of Sannio as an Assistant Professor. His research interests include electrical and electronic instrumentation, data acquisition systems (DAQ) based on compressive sampling (CS), biomedical instrumentation, embedded systems, distributed measurement systems, including wireless sensor networks (WSNs), and Internet-of-Things (IoT) systems. He has authored and co-authored more than 100 scientific papers published in international journals and conference proceedings. He is a reviewer of international journals and conferences.