A Research on the Adaptive Dynamic Scheduling Based on Scenario Deduction

Aiming at the uncertainty of the intelligent manufacturing system, this paper reveals the evolution mechanism of the manufacturing system and its internal and external environment from a data-driven perspective. And it proposes an adaptive dynamic scheduling method based on scenario deduction, which provides the basis for the intelligent manufacturing support in an uncertain environment. Firstly, the paper uses the ontology to describe the scenario status, production activities, market environment and production subject of manufacturing system. And then builds the scenario deduction model based on the dynamic fuzzy cognitive map, establishing the data-driven manufacturing scenario network structure. Through the dynamic fuzzy cognitive map, it presents the market and production scenario evolution and accordingly guides the adaptive choice of dynamic scheduling strategy in uncertain production environment. The results show that the scenario deduction model is basically consistent with the manufacturing system evolution process in terms of time inference and demand prediction, and it verifies the adaptability and effectiveness of the proposed dynamic dispatching method through examples.