Loredana Necșoi (Proistosescu)

Mrs. Loredana Necșoi (Proistosescu)


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 February 2026 in Sustainability
Verified
Journal Article
Open access
PDF file
ENEduard Laurenţiu Niţu
Eduard Laurenţiu Niţu
AGAna Cornelia Gavriluță
Ana Cornelia Gavriluță
Nadia Ionescu (Belu)Nadia Ionescu (Belu)
Nadia Ionescu (Belu)
L(Loredana Necșoi (Proistosescu)
Loredana Necșoi (Proistosescu)
JSJérémie Schutz
Jérémie Schutz
As the Industry 5.0 transition unfolds, engineering education must evolve to integrate Lean manufacturing with advanced digital tools and sustainable, human-centred practices. This study presents the design and implementation of a Lean Learning Factory (LLF) that addresses this challenge by combining traditional Lean methods with technologies such as simulation, robotics, and virtual reality in a modular educational environment. At the University Centre Pitești, six hands-on projects were implemented to guide students through key concepts, including production system layout, digital assistance, sustainability, and human–robot collaboration. Through experiential learning, students engage in iterative design, data analysis, and practical validation using real equipment and software platforms. The results indicate that the LLF effectively supports the development of technical, digital, transversal, and human-centred competencies aligned with EUR-ACE® standards. Students acquire skills in process optimisation, ergonomics, and sustainable production, while also reflecting on the ethical and social implications of automation. The study concludes that the LLF model provides a scalable and adaptable framework for engineering education. It fosters competence-based learning and prepares students for the demands of Industry 5.0. This paper contributes a replicable educational approach that blends Lean efficiency, digital transformation, and human-centred values into a cohesive learning ecosystem.

4 June 2026 in Advances in Science and Technology
Verified
Conference Paper
Closed access
PDF file
L(Loredana Necșoi (Proistosescu)
Loredana Necșoi (Proistosescu)
ENEduard Laurenţiu Niţu
Eduard Laurenţiu Niţu
AGAna Cornelia Gavriluță
Ana Cornelia Gavriluță
Robotic arms significantly help automate production processes, which is why they are important for Industry 4.0. Depending on production requirements, each operation is matched to a type of robotic arm, as they have specific and unique characteristics. A well-defined classification of robotic arms is fundamental to ensure proper selection, use, and maintenance according to the particular operations performed. This paper presents a classification of the main robotic arms used in logistics and production processes. It also summarizes the main research on the use of robotic arms in logistics and manufacturing.