Abstract
A new generation of manufacturing systems is emerging through the adoption of new policies to overcome future crises highlighted by constant social, environmental, and economic concerns. The rise of so-called smart manufacturing is noticeable. However, new risks to humankind are being introduced, and, more than ever, science and technology are required to guarantee the future sustainability and resilience of our manufacturing systems. This research presents a Digital Twin approach resorting to simulation models with embedded intelligence to transform efficient manufacturing systems and react to complex and unpredictable circumstances. The methodology covers production scheduling incorporating flexible robots, internal logistics supervision contemplating planning and control of mobile robots, and capacity management. The method demonstrates the potential of integrating Additive Manufacturing technologies to quickly react to production needs. The developed strategy was enforced and assessed in an industrial experiment, exhibiting its robustness and promising application. The attained results were very encouraging, highlighting its potential extension to more complex industrial systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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Abstract

Abstract
The Portuguese footwear industry registered a strong performance over the last few years and the openness to adopt new technologies was a key factor. Among these, the implementation of innovative logistic systems for the transport and assignment of work-in-process in manufacturing processes was a key technology. By means of case research it was analyzed an internal logistic system, deployed in a Portuguese large footwear producer, which reveals some weaknesses at the physical and cyber levels. A lack of managing applications was detected at the factory and enterprise levels, which contribute to lower levels of visibility of production and productivity. This article presents the development of a Cyber-Physical Production System, in the context of the Horizon 2020 research and innovation program BEinCPPS, that comprises four application experiments. These experiments were successful and the results demonstrated a relevant increase of production efficiency and decrease of maintenance costs.

Abstract
This paper presents an integrated cognitive robotics system for industrial kitting operations in a modern factory setting. The robot system combines low-level robot control and execution monitoring with automated mission and task planning, and a logistics planner which communicates with the factory's manufacturing execution system. The system has been implemented and tested on a series of automotive kitting problems, where collections of parts are picked from a warehouse and delivered to the production line. The system has been empirically evaluated and the complete framework shown to be successful at assembling kits in a small factory environment.