Processes simulator

Industrial 4.0 processes VR simulation

Responsibles:

Amundarain, Aiert

Borro, Diego

Participants:

Ottogalli, Kiara

ABSTRACT

A new framework to model industrial processes that involve I4.0 features was developed. This framework is flexible enough to be adapted to different industrial domains, such as energy, manufacturing, or aeronautics, for several purposes that include prototyping, design, process engineering, or decision-making. It is prepared for multiple I4.0 technologies including Virtual Reality (VR), Augmented Reality (AR), Human-Robot Collaboration (HRC), Motion Capture (MoCap), Digital Twin (DT), and Reinforcement Learning (RL), without losing generality. The framework supports the interaction among multiple actors, such as humans and automated devices. It also considers different types of tasks to model processes, including assembly, disassembly, and logistics. It comprises two modules, the process definition and the simulator with an embedded process controller, which communicate through an interface. The proposed framework has been applied to the development of four industrial scenarios: an aircraft Final Assembly Line (FAL) simulator, a guidance tool for high-voltage cell security, an application for machine-tool usage training, and a DT of a robotic Non-Destructive Testing (NDT) system. For the former, a comprehensive study of the productivity and ergonomics of several strategies with different automation levels was made. This study includes the VR simulation of 13 fully automated and 10 semi-automated basic scenarios for cabin and cargo assembly of sidewall panels, hatracks, and linings. The data collected during these simulations served to create 81 whole aircraft new assembly combinations of these parts and evaluate them in terms of 5 Key Performance Indicators (KPIs): assembly time, worker cost, investment, Return of Investment (ROI), and ergonomics. As many I4.0 processes include smart robotics, a workflow for integrating RL technologies to the framework was created. With this workflow, a robotic task can be formalized as a RL problem by leveraging the Markov Decision Process (MDP) theoretical background. Then, a RL method can be chosen to train an agent in the virtual environment. Finally, the model obtained by this training is used to perform the autonomous robotic tasks inside the simulator with the embedded process controller. Two use examples of this workflow are presented: an agent for robotic reaching task and an agent for the assembly planning of an aircraft part.

PAPERS

Journals:

    • Ottogalli, K., Rosquete, D., Amundarain, A., Aguinaga, I., and Borro, D., “Flexible Framework to Model Industry 4.0 Processes for Virtual Simulators”, Applied Sciences, Special Issue on New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes: Volume II, Vol 9, No., 23, 4983. November 2019. (pdf).

    • Ottogalli, K., Rosquete, D., Rojo, J., Amundarain, A., Rodríguez, J.M., and Borro, D., “Virtual reality simulation of human-robot coexistence for an aircraft final assembly line: process evaluation and ergonomics assessment”, International Journal of Computer Integrated Manufacturing, Vol. 34, No. 9, pp. 975-995. September 2021. (pdf).

Conferences

    • Ottogalli, K., Rosquete, D., Amundarain, A., and Borro, D., “SIMFAL - Assembly Planning and Simulation of an Aircraft Final Assembly Line”, Invited Speaker in the XXVIII Congreso Español de Informática Gráfica (CEIG'18). Madrid, Spain. June 27-29, 2018.

    • Ottogalli, K., Rosquete, D., Amundarain, A., and Borro, D., “Framework for the Simulation of an Aircraft Final Assembly Line”, in Proceedings of EASN-CEAS International Workshop on Manufacturing for Growth & Innovation 2018. Glasglow, UK. September 04-07, 2018.

    • Ottogalli, K., Rosquete, D., Rojo, J., Amundarain, A., Rodríguez J.M., and Borro, D., “SIMFAL - Assembly Planning and Simulation of an Aircraft Final Assembly Line”, Invited Speaker in Workshop “Assisting human operators in the industry 4.0: challenges and perspectives” in IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2018). Torino, Italy. September 04-07, 2018.

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