Papers

2

Total Citations

16

H-Index

2

About

Nathalie Grangeon is a leading researcher in the field of industrial engineering, with a primary focus on the optimization of robotic assembly lines. Her work addresses the complex challenge of balancing assembly operations and robot allocation within straight-line workstations—a problem known as the Robotic Assembly Line Balancing Problem (RALBP). Grangeon has made significant contributions by investigating sequence-dependent setup times, a critical factor that adds realism and complexity to these optimization models. Her 2022 paper, "Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach," has garnered 13 citations, highlighting its impact on advancing algorithmic solutions for RALBP-2, where minimizing cycle time is paramount. Additionally, her 2020 work, "A MIN-MAX PATH APPROACH FOR BALANCING ROBOTIC ASSEMBLY LINES WITH SEQUENCE-DEPENDENT SETUP TIMES," introduced a novel min-max path approach, further solidifying her reputation for developing efficient, practical methods. Grangeon’s research is instrumental for engineers and researchers seeking to enhance productivity in automated manufacturing, offering robust frameworks that bridge theoretical optimization with real-world industrial constraints.

Research Focus

Key Achievements

2
H-Index
2
Papers
16
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Investigating two variants of the sequence-dependent robotic assembly line balancing problem by means of a split-based approach
13 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Centre National de la Recherche Scientifique, Université Clermont Auvergne

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago