Robotics-enabled logistics and assistive services for the transformable factory of the future (TAPAS)

Today’s automation and logistics paradigms make it difficult, time consuming, and costly to change the type of the product manufactured and to scale the production up and down in response to market volatility. Consequently, and with the increasing market uncertainties, it becomes more and more dif- ficult to justify new automation lines. To keep production in Europe instead of shifting it to low-wage countries, this project will break new ground in robot-based automation and logistics as the backbone of a transformable factory of the future, enabling an economic production regardless of changes in volumes and product type.
TAPAS pioneers the following tasks in real production environments: mobile robots with manipula- tion arms will make logistic tasks more flexible and more complete by not only transporting, but also collecting the parts needed and delivering them right to the place were needed. Since moving parts around the shop floor does not create value by itself, TAPAS robots go even beyond: they will auto- mate assistive tasks that naturally extend the logistic tasks, such as preparatory and post-processing works, e.g., pre-assembly or machine tending with inherent quality control. Through this additional creation of value and by a faster adaptation to changes with new levels of robustness, availability, and completeness of jobs TAPAS robots promise to yield an earlier return of investment.
To reach the objectives, the TAPAS consortium will iteratively test and validate the developments with two pilot installations of increasing complexity and scale. The drivers behind TAPAS are a robot manufacturer and a system integrator, providing both their production environments for intensive test- ing and validation, and a software technology provider. Teaming up with three excellent research partners they will develop logistic and assistive robotic solutions for transformable automation that are generally applicable and scalable.