Chiara Beghetti

Ph.D. candidate in Ingegneria Gestionale E Della Produzione , 39th cycle (2023-2026)
Department of Management and Production Engineering (DIGEP)

Docente esterno e/o collaboratore didattico
Department of Management and Production Engineering (DIGEP)

Profile

PhD

Research topic

Multi-axis Systems implementing laser-based Advanced Manufacturing processes

Tutors

Research interests

Additive manufacturing and reverse engineering
Advanced manufacturing technologies and systems

Biography

Chiara Beghetti is currently a PhD candidate at the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino (PoliTo).
She obtained her bachelor's degree in Mechanical Engineering in September 2020 and completed her master's degree in Mechanical Engineering, with a focus on Mechanical Production, in April 2023, both at PoliTo.
From September 2017 to April 2022, she was a member of the PoliTo Sailing Team, where she worked as a CAD modeler, structural engineer, area manager, and project manager.
She conducted her master’s thesis at the Integrated Additive Manufacturing (IAM) interdepartmental center of Politecnico di Torino, focusing on Reverse Engineering (RE) technologies, including structured light, photogrammetry, and laser triangulation, as well as Additive Manufacturing (AM) techniques such as Fusion Deposition Modeling (FDM) and Selective Laser Sintering (SLS). Her research aimed to develop a novel design and production methodology for custom active orthoses, with the objective of facilitating their wider adoption as assistive devices for Activities of Daily Living (ADLs).
Following her graduation, she continued her work at the IAM center as a research fellow from May 2023 to February 2024, focusing on polymeric and metallic AM for biomedical applications, which she continues to investigate.
In March 2024 she began her PhD fellowship at DIGEP, Polito. She studies robotic multi-process systems employing laser-based advanced manufacturing techniques, including AM, welding, and heat treatments. Her work involves combining numerical tools with Design of Experiments (DoE) methodologies to define optimal strategies for the implementation of multi-process systems and to establish operational guidelines.

Teaching

Teachings

Bachelor of Science