Abstract
Aiming at the multi-level hierarchy framework of robotic manufacturing systems, how to realize a comprehensive energy-efficient optimization of the whole system is crucial to realize the sustainability of manufacturing. In this paper, the production-process oriented physical energy consumption model and digital model of industrial robots together with their interaction mechanisms are studied. Then, the concurrent assessment and evolution prediction approaches of robotic manufacturing systems are presented, as well as the collaborative optimization method based on knowledge evolution. Finally, a case study is implemented to verify the effectiveness of the proposed method.
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