Zhang Ding

TL;DR: A digital twin-driven manufacturing cyber-physical system (MCPS) for parallel controlling of smart workshop under mass individualization paradigm is presented and addresses a bi-level online intelligence in proactive decision making for the organization and operation of manufacturing resources.

TL;DR: The digital twin merges physics-based system modeling and distributed real-time process data to generate an authoritative digital design of the system at pre-production phase and a digital twin-based analytical decoupling framework is developed to provide engineering analysis capabilities and support the decision-making over the system designing and solution evaluation.

TL;DR: A novel digital twin-driven approach to achieving improved system performance while minimizing the overheads of the reconfiguration process by automating and rapidly optimizing it is proposed.

TL;DR: A novel iterative bi-level hybrid intelligence model named ManuChain is proposed to get rid of unbalance/inconsistency between holistic planning and local execution in individualized manufacturing systems and realize both lower-level crowd self-organizing intelligence and upper-level holistic optimization intelligence.

TL;DR: Two key enabling technologies for enabling the customized and software-defined design of flow-type smart manufacturing systems are presented, including the generalized encapsulation of the quad-play CMCO model and the digital twin technique.