This paper addresses the scenario where the manufacturing of a product with assigned quality specifications is transferred from a plant A to a plant B, which uses the same manufacturing process as plant A, but may differ for scale, configuration, actual operating conditions, measurement system arrangement, or simply location. The issue arises on whether the process data already available for plant A can be exploited to build a process monitoring model enabling to monitor the operation of plant B until enough data have been collected in this plant to design a monitoring model based entirely on the incoming data. This paper presents a general framework to tackle this problem (which we refer to as a model transfer problem), and three possible latent variable approaches within this framework are proposed and evaluated. One approach makes use of measurements coming from plant A only, whereas the other two integrate plant A data and plant B data into a single adaptive monitoring model. The proposed approaches are tested on an industrial spray-drying process, where plant A is a pilot unit and plant B is a production unit. It is shown that all proposed model transfer approaches guarantee very satisfactory monitoring performance in plant B, with quick fault detection, limited number of false alarms or undetected faults, and limited (or no) need of plant B data to accomplish the model transfer. We believe that these strategies can provide a valuable contribution to the practical implementation of quality-by-design methodologies and continuous quality assurance programs in product manufacturing.