Faculty Research Spotlight
Jesus Jimenez, Ingram School of Engineering
Digital Twins Improve Health, Safety, and Productivity of Workers
"The digital twins for human operators will help design jobs that require higher operator pace as well as higher occupational safety and ergonomics.”
My research focuses on simulation modeling and data-intensive analysis targeting the manufacturing and supply chain industries. An area of increasing interest for my research group is the development of digital twins to enable testing and optimization capabilities
of production systems. Digital twins are unique computer representations of machines, facilities, and material handling devices, which mimic the behavior of a real system. The digital twins under development in our lab, however, seek to represent human operators and manual labor.
Manufacturing operators often suffer work-related injuries caused by highly repetitive and non-ergonomic motion, such as bending, reaching overhead, pushing, and pulling. The digital twins for human operators will help design jobs that require higher operator pace as well as higher occupational safety and ergonomics. Furthermore, by using tools such as Virtual and Augmented Reality, we can use the digital twin to generate holographic representations of the operators. The operators can then visualize these holograms and receive feedback about how to perform their work better and safer.
Here are the steps for building digital twins:
- We set up a physical simulation for basic manual manufacturing and material handling moves, such as lifting, pushing, pulling, and gripping. During the simulation, we use motion capture cameras to record these basic moves. We also use biometrical sensors to capture operator health data such as heart and respiration rates.
- We analyze motion and biometrical data to detect patterns in bad moves and discover how the operator develops fatigue.
- We use a significant amount of data collected during the physical simulation experiments to train artificial intelligence (AI) models. The application of AI can help detect when an operator gets tired as a result of repetitive moves.
- We use Augmented Reality to build the holographic representation of the operators and give feedback about their jobs.
It is expected that our research will help to address the following big issues:
- • Need for less repetitive human manufacturing and material handling activities
- • Use of technology to help workers improve their safety and health
- • Need for labor in manufacturing material handling industries
I would like to thank Drs. Francis Mendez, David Wierschem, Semih Aslan, George Koutitas, Damian Valles, and Rachel Koldenhoven for all their support in this project. We would also like to thank Toyota Material Handling North America University Research Program for supporting the research project “Using Industry 4.0 Digital Twins to Model Human Labor in Smart Material Handling Systems.”
Please visit the Center for High Performance System’s website for updates on this and other research projects.