معرفی
Aitor Iriondo Pascual is a researcher at the University of Skövde's School of Engineering Science, specializing in digital human modeling (DHM) and simulation-based multi-objective optimization (MBOO) for ergonomics and productivity in manufacturing systems. His work bridges industrial engineering with human factors research, focusing on automating ergonomic assessments using motion capture technology and machine learning algorithms.
- PhD in User-Centered Product Design (University of Skövde, 2023)
- Active in Virtual Production Development (VPD) and Synergy Virtual Ergonomics (SVE) research profiles
- Collaborator in international projects like MOSIM and VIVA
- Key contributor to DHM toolchain development with IPS IMMA and LUA scripting
His research interests center on:
- Integrating motion capture with DHM for objective ergonomic evaluations
- Automated hand posture classification using random forest algorithms
- Concurrent optimization of productivity and worker well-being in factory layout design
- Standardization of 3D body shape prediction models for virtual simulations
- Machine learning applications in biomechanical exposure assessments
- Digital twin development for sustainable manufacturing systems
Recent publications demonstrate his expertise in combining genetic algorithms with DHM tools for occupant packaging design and logistics area optimization. He has also developed open-source statistical body shape prediction models shared under MIT License on GitHub.
Key collaborators include:
- Prof. Lars Hanson (ergonomics)
- Dr. Dan Högberg (simulation methods)
- Dr. Anna Syberfeldt (optimization frameworks)
- Dr. Erik Brolin (DHM tools)
His methodological innovations include:
- Automating REBA/RULA assessments via motion capture data
- Developing Pugh's method implementation for DHM concept evaluation
- Creating cross-disciplinary optimization frameworks for production systems