Data-driven Manufacturing Service Optimization Model in Smart Factory

Intelligent manufacturing has globally become one of the important development trends in the manufacturing industry. The development of emerging technologies provides support for the realization of intelligent manufacturing and also brings challenges. While realizing the efficient use of big data and customized manufacturing, cloud computing and cloud manufacturing ignore the complicated production process and limit the supply of quality manufacturing services. In this scenario, a manufacturing service optimization model consisting of manufacturing resource agents is proposed. The resource agent is the intelligent package of each manufacturing unit of the enterprise, with powerful data analysis and service management capabilities. The model uses industrial big data as the driving force to continuously improve the capacity of manufacturing resources and optimize the resource allocation in the manufacturing service call chain, ultimately improving the quality of manufacturing services. Finally, the effectiveness and practicability of the proposed model is verified by a typical case of the manufacturing process of the cylinder product.