There is extensive literature about drones in a logistics context, and numerous applications have been implemented, but there is one unique use case that hasn't gotten momentum so far, yet offers significant potential. Our paper focuses on this opportunity, which is deploying drones to support the monitoring of intralogistical processes, i.e. Multi Moment Analysis (MMA). This way the observation and measurement of manufacturing processes could be automated to a large extent, making it faster, more reliable and cheaper, therefore offering benefits to both the logistics company performing the MMA and the customer. Our paper describes the architecture of a system needed to perform MMAs using drones, focusing on two key components: the indoor localization sub-system and a real-time closed-loop control algorithm, that enables the drone to track the monitored object. In order to test our algorithm, we built a simulator in MS Excel, where a drone is tracking an object moving along a straight line and a curve. The results of our experiments indicate that the drone was able to stay well within 1 meter of the object, despite the introduced uncertainty in their motion, therefore our algorithm appears to be validated and ready to be tested in a physical environment.