Abstract: To address the practical needs of cost reduction and efficiency improvement in workshop operations under the digital backdrop, random disturbance events occurring during the assembly process may pose numerous risks and losses to the factory. In response to disruptions such as emergency order insertion and machine failures encountered in the production of a digital workshop, a rolling time window is employed to select scheduling strategies based on the varying production states of the workpieces. During rescheduling, the focus is on minimizing the maximum completion time of the preliminary scheduling plan, reducing penalty costs, and achieving the minimum average equipment load. The stability and robustness of the rescheduling plan are evaluated from three aspects: equipment deviation, process deviation, and minimum delay time, thereby establishing a multi-objective rescheduling model under uncertain disturbance events.Taking a digital workshop for automobile seats as an example, this study addresses random disturbance events in workshop production by integrating a hybrid tabu search genetic algorithm to validate the feasibility of the proposed scheduling process and model. The results demonstrate that under time window constraints, the newly generated scheduling plan exhibits excellent stability and robustness in handling uncertain disturbance events in digital workshops, thereby expanding the new approaches for digital workshops to manage such uncertainties.