Miguel Vieira

About

Miguel Vieira is a researcher at the forefront of intelligent manufacturing and automation, with a primary focus on production planning, scheduling, and human–robot collaboration. His most significant contribution is the development of the Recursive Optimisation-Simulation Approach (ROSA), a novel two-level methodology that integrates optimization and simulation to provide effective decision-support for complex assembly lines. This work, published in 2021, has garnered 54 citations, underscoring its impact on the field. Vieira’s earlier research (2018) further advanced decision-support for automated assembly lines managed by mobile robotic resources, achieving 9 citations. Additionally, he has explored emerging technologies like Visible Light Positioning (VLP) for indoor localization in mobile robotics (2016, 3 citations), demonstrating versatility. His work is particularly notable for bridging theoretical optimization with practical industrial applications, offering tangible solutions for real-world manufacturing challenges. Vieira’s contributions are essential reading for students and researchers interested in simulation-based optimization, robotics, and the future of collaborative assembly systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line

   54 citations · 2021
2. 2
   Simulation-Optimization Approach for the Decision-Support on the Planning and Scheduling of Automated Assembly Lines

   9 citations · 2018
3. 3
   A Validation Framework for Visible Light Positioning in Mobile Robotics

   3 citations · 2016

Key Collaborators

Contact & Links