Francesco Lambiase

Nome: Francesco Cognome: Lambiase Qualifica: Professore associato Settore Scientifico Disciplinare: ING-IND/16 (Tecnologie E Sistemi Di Lavorazione) Struttura di afferenza: Dipartimento di Ingegneria industriale e dell'informazione e di economia Email: francesco.lambiaseunivaq.it Telefono Ufficio: +39 0862434343 Pubblicazioni: https://ricerca.univaq.it/cris/rp/rp04015

Curriculum scientifico

versione stampabile (pdf)

Francesco Lambiase is Lab manager of TECNO, a research laboratory at the University of L'Aquila (DIIIE, ING-IND/16). Since 2003 he has conducted research and development activities in the field of advanced manufacturing processes, with expertise spanning materials characterization, innovative joining technologies, additive manufacturing, numerical modeling and AI-based process optimization. Research output: 100+ Publications on Peer Reviewed International Journals · 5,200+ citations · 46 H-Index · Google Scholar.

Scientific research activities are developed in collaboration with industrial partners in the aerospace, automotive, plastics & recycling, additive manufacturing, circular economy and e-mobility sectors, in the context of nationally and EU-funded research projects.

SPECIAL AWARDS

The research activity focuses on the development of experimental methodologies for the mechanical and thermal characterization of metals, polymers, composites, powders, and components produced by additive manufacturing. A key objective is the design and validation of non-standard test protocols capable of capturing the behavior of materials under conditions representative of real industrial applications, including extreme temperatures, dynamic loading and multiaxial stress states.

Attention is devoted to the characterization of thermoplastic and composite materials for joining and structural applications, including the study of viscoelastic behavior, thermal transitions, and the influence of manufacturing history on mechanical properties. Full-field strain measurement via Digital Image Correlation (DIC) is routinely applied to validate numerical models and study local deformation mechanisms.

A dedicated research line concerns the development of in-process thermal monitoring methodologies using high-sensitivity infrared imaging, applied to joining, forming and additive manufacturing processes to correlate thermal fields with joint quality and process outcomes.

Rheological characterization of polymer melts — including melt flow index and capillary rheometry — supports both recycling process development and additive manufacturing parameter optimization.

3D surface metrology and scanning electron microscopy are applied to the characterization of joint interfaces, fracture surfaces, and additive manufacturing component microstructures.

The research focuses on the development and characterization of joining processes for dissimilar material assemblies, addressing the structural integration of metal–polymer, metal–composite and metal–metal hybrid structures. This field is driven by lightweighting demands in aerospace and automotive applications, where conventional welding and adhesive bonding approaches present fundamental limitations.

Electrically Assisted Joining — patented technology

The original contribution in this field is the development of Electrically Assisted Joining (EAJ), a family of processes protected by 5 granted Italian patents (2018–2021, with 2 European extensions). The technology exploits resistive heating generated by electrical current flow to enable the joining of dissimilar materials — including metal–metal couples with different melting points, metal–polymer and metal–composite hybrid structures, and polymer matrix composites — without the need for adhesives or mechanical fasteners. Processes have been developed and validated on aerospace-grade aluminum alloys, titanium, polyamide, PEEK and CFRP laminates.

Research activities in joining processes

Prior to and alongside the development of EAJ, the research group has investigated several process families for dissimilar material joining:

•  Friction Assisted Joining (FAJ): thermomechanical solid-state process studied through experimental campaigns on metal–polymer and metal–composite joints. An instrumented prototype machine was designed and built to measure process forces and temperatures in real time, enabling process window characterization and predictive model development.

•  Laser Direct Joining: investigation of the thermo-physical mechanisms governing metal–polymer bond formation under laser irradiation. Experimental analysis and numerical modeling of joint morphology, interfacial temperature and mechanical performance. AI-based models developed for process parameter optimization.

•  Friction Spot Welding and Friction Stir Spot Welding: experimental study of process conditions and their influence on joint microstructure and mechanical properties. Instrumented test equipment developed; numerical modeling and machine learning applied to process optimization.

•  Mechanical Clinching: investigation of clinching applicability to high-performance materials and hybrid joints. Experimental analysis of joint geometry, failure modes and strength; development of predictive numerical models and AI-based optimization approaches.

Research on additive manufacturing processes covers process development, parameter optimization and component qualification for a range of deposition technologies. A central focus is the extension of FFF/FDM processes to high-performance thermoplastics — including PEEK, PEI and PAEK — for structural and functional applications in aerospace and biomedical sectors.

The research investigates the relationships between process parameters, thermal history and the resulting mechanical and microstructural properties of printed components. This includes the study of inter-layer adhesion, anisotropy, residual stresses and porosity in high-temperature polymer systems, as well as the development of non-destructive characterization methodologies specific to AM components.

A dedicated research line addresses laser-based post-processing of FDM surfaces to improve surface finish and adhesion properties for subsequent joining operations.

The ongoing project PROMETHEUS (FIS3 Advanced Grant, € 1.89M) develops a multi-physics, AI-based optimization framework for Selective Laser Melting processes, targeting aerospace and biomedical applications.

Research on Binder Jetting characterization has been conducted in direct collaboration with industrial partners, with results published in peer-reviewed journals.

This research line addresses the development of processes for the thermomechanical recycling of high-performance thermoplastics and the recovery of critical raw materials from end-of-life products, in the context of EU sustainability requirements and the Critical Raw Materials Act.

Research activities include the design and optimization of recycling process parameters for technopolymers such as PEEK, PAEK, ULTEM and polyamide-based composites, and the characterization of mechanical and thermal property degradation as a function of recycling cycles. The objective is to establish qualification criteria for the reuse of recycled-content materials in structural applications.

Ongoing projects address the automated recovery of MPC/MPS from end-of-life smartphones and LCD screens (Project I-RECOVER, MASE, € 2M) and the development of AI-based sorting and recognition systems for automated disassembly lines (Project WEEKO Factory 2.0, MISE, € 4.1M). Laser and abrasive waterjet processes are being studied as enabling technologies for non-destructive component separation.

A further activity concerns the recovery and valorization of graphite powder from machining waste.

Research on surface engineering investigates laser-based surface treatment techniques — including structuring, texturing, cleaning and ablation — applied to metals, polymers and composites prior to joining operations. The objective is to modify surface topography, chemistry and wettability to enhance adhesion at dissimilar material interfaces.

The influence of surface pre-treatment on the mechanical performance of hybrid joints is studied through a combination of surface characterization techniques (profilometry, SEM, contact angle measurement) and mechanical testing. Functionalized surfaces are evaluated in the context of FAJ, Laser Direct Joining and adhesive bonding configurations.

Research on flexible forming processes includes the development and simulation of incremental forming for polymeric and thermoplastic composite components, and laser forming of thin metallic sheets. Both process families are studied through experimental campaigns supported by numerical simulation, with the aim of developing predictive models linking process parameters to the final geometry and residual stress state of formed components.

A cross-cutting research activity concerns the development of numerical models and AI-based methodologies for the analysis, design and optimization of manufacturing processes. The approach combines physics-based finite element modeling with machine learning techniques, leveraging the experimental data generated by the laboratory's instrumented equipment.

FEM models are developed and calibrated for forming processes (hydroforming, gas forming, incremental forming), joining processes and additive manufacturing, with constitutive model validation through DIC-based strain field measurements. The models are used both for process understanding and for virtual process design.

Machine learning applications include the development of predictive models for joint quality and defect detection, computer vision systems for in-line process monitoring, and digital twin frameworks for manufacturing process simulation and optimization. Models are trained on experimental data acquired from real industrial processes, ensuring physical consistency and applicability to actual production conditions.

Earlier contributions include the development of genetic algorithm-based automatic design methodologies for plastic deformation processes (hot rolling, roll drawing, tube drawing), and the application of neural networks and regression models to forming process parameter optimization.

Francesco Lambiase is inventor of 5 granted Italian patents on Electrically Assisted Joining processes for dissimilar material assemblies, with 2 European extensions:

The following projects have been conducted with Francesco Lambiase as Scientific Responsible for the University of L’Aquila:

2025 — FIS3 Advanced Grant · Italian National Science Fund

Project PROMETHEUS — PRocess Optimization through Multi-physics and Experimental THEoretical Unified System. AI-based optimization of Selective Laser Melting processes for aerospace and biomedical applications. Competitive national selection; awarded to established researchers leading frontier, high-interdisciplinary-impact research.

2025–2026 — Project I-RECOVER · MASE

Intelligent RECOVER of MPC/MPS from end-of-life smartphones and LCD screens via an innovative automated disassembly line. Ministry of Environment and Energy Security (MASE) — RepowerEU Mission 7, Investment 8. Principal activities: development of thermomechanical laser and waterjet processes for critical raw material recovery.

2024–2026 — Project MaTIS4T · MISE

Materials and Innovative Sustainable Technologies for Transportation. MISE — Accordi per l’Innovazione, Filiera Automotive (F/340037/01/X59). Principal activities: development and testing of new materials for structural self-health monitoring (reinforced plastics and composites); development of thermoforming simulation models for composite materials.

2024–2026 — Project WEEKO Factory 2.0 · MISE

Plastic material recycling and AI system development for process control and feature recognition. MISE — Accordi per l’Innovazione (F/350327/01/X60). Principal activities: recycling process development, AI-based in-process control, critical material recovery.

2023–2024 — Project PAT-BOOSTER STRUCTURAL

Hybrid STRUCTURe by joining dissimilAr-metaLs. INVITALIA — C18H23000740002. Development of structural joining solutions for dissimilar metal assemblies.

Current courses at the University of L’Aquila:

•  "Additive Manufacturing" — Master’s Degree in Mechanical and Management Engineering

•  "Advanced Characterization of Additive Manufacturing Components" — PhD program in Industrial and Information Engineering and Economics

•  "Industrial Technologies" — Bachelor’s Degree in Management Engineering

•  "Advanced Technologies" — Bachelor’s Degree in Industrial, Management and Biomedical Engineering

•  "Simulation of Plastic Deformation Manufacturing Processes" — Master’s Degree in Mechanical and Management Engineering

•  Since 2023: Representative of the University of L’Aquila on the Administrative Board of CIRTIBS (Centro Interuniversitario di Ricerca sulle Tecnologie Innovative per Beni Strumentali)

•  Since 2021: Member of the Orientation and Tutoring Committee (COeT), DIIIE, University of L’Aquila

•  Since 2020: Delegate for Internationalization, Management Engineering degree program

•  Since 2020: Member of the Academic Area Council (C.A.D.) in Mechanical Engineering and Industrial Engineering

•  Since 2018: Member of the PhD College — "Industrial and Information Engineering and Economics", University of L’Aquila

•  Ordinary member of AITEM — Associazione Italiana Tecnologia Meccanica