In order to realize the fact that operational tasks can be decomposed flexibly with new tasks random adding, role-based approaches for operational tasks model and the flexibility decomposition are proposed. Firstly, aiming at the shortcomings of previous task decomposition methods, operational role concepts are introduced to design a computing framework of task flexibility decomposition. Within the framework, task structure matrixes are constructed for tasks decomposition with the mapping relations of information interaction and action process among tasks. On basis of this, via giving operational decomposition granularity, a flexibility approach of operational task decomposition is put forward with three parts about task decomposition granularity adjustment, tasks module partition with different operational role patterns and task decomposition scheme evaluation. Finally, as an application case shown, it is validated that the proposed approaches for tasks modeling and decomposition are available. By comparing with previous decomposition approaches, the proposed approach, within three types of operational roles, has strong environmental adaptability and scheme diversity, which can restrain calculation complexity increment for realizing task flexible decomposition effectively. In order to realize the fact that operational tasks can be decomposed flexibly with new tasks random adding, role-based approaches for operational tasks model and the flexibility decomposition are proposed. Firstly, aiming at the shortcomings of previous task decomposition methods, operational role concepts are introduced to design a computing framework of task flexible decomposition. Within the framework, task structure matrixes are constructed for tasks decomposition with the mapping relationship of information interaction and action process among tasks. On basis of this, via giving operational decomposition granularity, a flexibility approach of operational task decomposition is put forward with three parts about task decomposition granularity adjustment, tasks module partition with different operational role patterns and task decomposition scheme evaluation. Finally, as an application case shown, it is validated that the proposed approaches for tasks modeling and decomposition are available. With comparing with previous decomposition approaches, the proposed approach, within three types of operational roles, has strong environmental adaptability and scheme diversity, which can restrain calculation complexity increment for realizing task flexible decomposition effectively.