Transformable Adaptative Lines Optimized System

Recent trends in production and market dynamics are reshaping the European manufacturing industry.Mass customization and personalization demands drive production operations towards high product variability, smaller batch sizes, reduced inventory, and shorter lead times. A growing need for industries to assemble many similar products in small quantities (high-mix low-volume demand) requires assembly lines to adapt to handle diverse products with different processing requirements. Manufacturing companies need to balance workers’ well-being with shortened lead times to enhance responsiveness to market demands.

TALOS specifically addresses the challenges faced by today’s manufacturers. The solution transforms traditional assembly lines involving many manual operations into Dynamic Multiproduct Parallel Assembly Lines, composed of reconfigurable modules.

Through TALOS, every workstation of the traditional line is replaced with a mobile workbench moved by an Autonomous Mobile Robot, creating an easily reconfigurable system that allows companies to dynamically manage the production of fragmented batches. The Fleet Management System of the mobile robots is integrated with an algorithmic system that optimises the planning of processes and the robot/workbench movements. Through artificial intelligence, TALOS enhances an agile and adaptive approach.

TALOS enables the creation of a work environment in which it is no longer the worker who must adapt to the needs of the assembly line, but the flexible element is inherent in the technological set-up. This innovative approach can relieve operators from the micro-planning work and the wearisome chasing of fast and extremely changeable production needs, thus reducing work-related stress and improving ergonomics.

With this project, EUREKA SYSTEM and ELIF LAB, address Challenge 9 ‘Enhanced digital planning to optimize the execution of the tasks of production operators’, combining expertise in industrial automation and artificial intelligence for a paradigm shift in manufacturing. They will be mentored by INEGI to facilitate their digital transformation integrating their building block 14 ‘Data operationalization methodologies’.