We present an industrial case on workforce allocation and scheduling in the aircraft manufacturing industry, where available teams need to be assigned to logistical operations. This application presents several challenges, such as the scale of the problem, the need for fair workload distribution, and the need for methods to mitigate unforeseen disruptions due to technical malfunctions or incompatible weather conditions. We compare different Constraint Programming (CP) models for the allocation and scheduling problems, with extra focus on modeling the workload balancing component. Additionally, we investigate automatic rescheduling methods for restoring feasibility after a disruption invalidates the precomputed schedule. Our results show that by using appropriate modeling techniques, the problem can be solved in reasonable time, thereby producing fair schedules. Additionally, we show how invalidated schedules can be restored efficiently to help human operators in resolving disruptions to the schedule.