Literature on job shop scheduling has primarily focused on the development of predictive schedules that generate an allocation sequence of jobs on machines. However, in practice, frequent deviations from a predictive schedule occur when the job shop experiences either external (e.g. unexpected arrival of urgent jobs) or internal disturbances (e.g. machine breakdowns) and renders the schedules inefficient. The reactive repair of the original schedule is a better alternative to total rescheduling, as the latter is not only time consuming but also leads to shop floor nervousness. Most of the existing schedule repair heuristics handle singular disruptions only. In this paper, the typical job shop disruptions are studied and their repair processes are decomposed into four generic repair steps, which are achieved using the proposed modified AOR (mAOR) heuristic. An extensive simulation study has also been conducted to evaluate the performance of the mAOR schedule repair heuristic, and the results indicate that the mAOR heuristic is effective in repairing job shop schedules when faced with disruptions.