David Sanderson

University of Nottingham, Imperial College London

Papers

13

Total Citations

276

H-Index

9

About

David Sanderson is a leading researcher in advanced manufacturing systems, with expertise spanning digital twins, artificial intelligence, reconfigurable manufacturing, and aerospace assembly. His most influential work, "A Framework for Manufacturing System Reconfiguration and Optimisation Utilising Digital Twins and Modular Artificial Intelligence" (2023, 130 citations), has established him as a pioneering voice in applying modular AI and digital twin technologies to dynamic, multi-system industrial environments — moving well beyond the traditional single-system paradigm. This contribution has resonated strongly across the manufacturing research community, reflecting its practical and conceptual significance. Sanderson has also made notable strides in aerospace manufacturing, particularly through his work on Measurement Assisted Assembly (43 citations), which advocates a paradigm shift toward more efficient, cost-effective high-complexity product assembly. His research consistently bridges theoretical frameworks with real-world application, evidenced by contributions to plug-and-produce manufacturing software, robotic energy optimization, and self-configuring production platforms. His involvement in the five-year Evolvable Assembly Systems project further demonstrates his commitment to validating flexible manufacturing visions at scale. With a growing body of work extending into self-learning robotic decision-making, Sanderson continues to shape the future of intelligent, adaptive manufacturing.

Research Focus

Key Achievements

9
H-Index
13
Papers
276
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence
130 citations · 2023
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: University of Nottingham, Imperial College London

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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