At present, smart manufacturing computing framework has faced many challenges such as the lack of aneff ective framework of fusing computing historical heritages and resource scheduling strategy to guarantee the low latency requirement. In this paper, we propose a hybrid computing framework and design an intelligent resource scheduling strategy to fulfill the real real-time requirement in smart manufacturing with edge computing support. First, a four four-layer computing system in a smart manufacturing environment is provided to support the artificial intelligence( task operation with the network perspective. Then, a two two-phase algorithm for scheduling the computing resources in the edge layer is designed based on greedy and threshold strategies with latency constraints. Finally, a prototype platform was developed . We conducted experiments on the prototype to evaluate the performance of the proposed framework with a comparison of the traditionally traditionally-used method s. The proposed strategies have demonstrated the excellent real real-time, satisfaction degree and energy consumption performance of computing services in smart manufacturing with edge computing.
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