Research lab: Quality control and Optical Metrology Lab
Largo Lucio Lazzarino 56122, Pisa
Department of Industrial and Civil engineering (DICI)

Francesco Lupi

MEng Engineering; Ph.D Student in Smart Industry
Bio:

Born on February 9th, 1995 in Empoli (FI), Italy, Francesco Lupi received his undergraduate degree in Management/Industrial Engineering with honors (110/110) at the University of Pisa (PI), Italy, in 2017 and his graduate degree in Management/Industrial Engineering with honors (110/110) cum laude at the University of Pisa (PI), Italy in 2020. He is currently pursuing a Ph.D. in the Smart Industry program. He has authored national and international scientific papers with over 120 citations, and his current h-index in Scopus is 5. He is involved in several industrial research project in the Manufacturing domain.

Interests:

Flexible, Reconfigurable and Autonomous Visual inspection Systems, Sustainable Manufacturing, Industry 5.0, CAD, Photogrammetry, Quality Management, Education Theory and Constructive Alignment

Research Topic:

My PhD research project originated from the following research question: “How can we translate the well-known concept of reconfigurable and autonomous manufacturing, which has been explored in smart manufacturing over the last two decades, into the specific domain of Visual Inspection Systems (VIS)?”. In this context, the ultimate goal was to propose a new technological framework and open new business model avenues, such as configure-to-order, rather than the classical engineer-to-order solutions associated with monolithic and rigid VIS. These traditional approaches often necessitate high capital investments and substantial human intervention from both hardware and software perspectives to reprogram the VIS. The primary objective of my Ph.D career in its initial years was to study the current state-of-the-art of VIS, identify gaps in the existing landscape (e.g., outdated and highly customized yet rigid solutions not adaptable to variable production and more flexible demands), and leverage advancements in Industry 4.0 technology to establish a new wave of flexible VIS capable of handling variable production with minimal setup time and modular architecture, both in hardware and software, ultimately achieving reconfigurable VIS. As a further ambitious step during the final year, I endeavored to define a framework for more advanced VIS, termed autonomous, which retain and inherit the aforementioned features of flexibility and reconfigurability but are also capable of reasoning and making decisions autonomously regarding the selection of the best vision inspection algorithm and parameters, starting from annotated CAD models. This entails integrating CAD model design and inspection concurrently using the model-based definition (MBD) philosophy from the early product development stages. Concurrently, in line with the human-centricity emphasized in the latest Industry 5.0 concepts, I aim to incorporate concepts related to user graphical interface ergonomics and human decision-making or higher-value tasks into the loop of autonomous VIS. This entails relieving humans from low-level coding tasks or manual handling of hardware components, now controlled numerically (e.g., cameras, lights), allowing operators to focus more on process optimization and supervision. During my last year of the Ph.D, I developed a prototypical system to demonstrate feasibility for SMEs and to advance this promising and novel topic in the industrial landscape during my Erasmus+ traineeship period abroad. Currently, I am undertaking a stage with an SME in the local (Tuscany) manufacturing area to implement some of the topics theorized in the latest frameworks, primarily focusing on human interaction.

Other Activities:

During my bachelor and master courses, I have collaborated extensively with industrial SMEs companies in the Tuscany area, particularly in the fields of CAD modeling. I was awarded a grant to conduct my Master's thesis abroad at the University of Hawaii at Manoa, U.S., where I spent three months working on photogrammetry and 3D reconstruction. After working one year as a quality management consultant at Consorzio QUINN I won the PhD Smart Industry grant at the University of Pisa. During my PhD I received the fellowship for teaching support in Manufacturing Processes at the University of Pisa courses led by Prof. Ing. Michele Lanzetta, for two consecutive years and I was involved in various European projects, including MAESTRO, TET, and MARBLETECH, as a member of the University of Pisa team. In the final year of my PhD, I had the privilege of participating in the 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023) in Lisbon, where I presented the manifesto of my PhD project, and I was honored with the Best Student Paper Award. Additionally, I was granted an Erasmus+ fellowship for a seven-month period abroad at University Nova de Lisboa, FCT NOVA, Lisbon, Portugal.