Digital twin and blockchain-enabled trusted optimal-state synchronized control approach for distributed smart manufacturing system in social manufacturing

Abstract

The interaction between customer demands and manufacturing paradigms is becoming increasingly apparent. As the demand for personalized products grows, the manufacturing industry is evolving towards a socialized manufacturing paradigm. This shift makes the manufacturing system more unstable and complex, necessitating organization of production through a socialized resource service platform. Unlike traditional systems, emerging distributed smart manufacturing system (DSMS) face challenges of trusted collaborative operation and real-time optimal-state control in dynamic operational environments. To overcome these challenges, we propose a trusted optimal-state synchronized control (OSsC) approach suitable for DSMS to ensure optimal operation under dynamic customer demands. This paper introduces a digital twin and blockchain-based trusted optimal-state control framework for reliable decision-making, integrating OSsC approach into a trusted virtual layer to achieve real-time optimal target setting. We also propose a blockchain-based mechanism for trusted synchronized operation in open production logistics, enhancing cross-domain trust and intelligent selection of units under dynamic interruptions. Furthermore, we apply the analytical target cascading method for multi-objective synchronized optimization decision model in complex systems. A case study in the air conditioning manufacturing industry demonstrates the effectiveness of the framework, mechanism, and algorithm in enhancing reliability and reducing costs in dynamic environments, providing valuable insights for the optimization design and reliable operation of future manufacturing systems.