Digital printing systems allow for the production of a large variety of different products. Making production plans for all these different products is challenging. One of the challenging aspects of making these production plans is choosing the right sequence of machines, to produce the desired intent. This is challenging due to three aspects: the large number of interdependent variables in the problem instances, the variability of machines, and the search for the best solution from a large set of valid solutions. In this thesis, we implement and evaluate the use of a domain-specific language (DSL) called RSX (Routing Space eXploration), to assist in choosing a sequence of machines. We do this together with an industrial partner. For RSX we use a model-driven approach, and it can be used to model the devices, production steps, and product properties of the digital printing domain. It transforms those into a constraint model described in the MiniZinc language, which is used as input for a constraint solver. We present the implementation of the RSX language and MiniZinc constraint model, and we evaluate the language coverage, accuracy, and performance. From these evaluations, we conclude that RSX can be used to model a number of cases, which were characteristic in the context of our industrial partner. Furthermore, we conclude that RSX can compile and solve the evaluated cases in the order of a few seconds and that the implementation is accurate, such that it can be used as a proof of concept.

For the past 10 weeks, we have been tasked with improving the performance of the transaction monitoring system of bunq, an internationally active mobile bank. bunq has requested that we improve this system by automating the training of the machine learning model, providing better input data for this model and creating additional machine learning models. During this project, we have been working at the offices of bunq on this system. This thesis will give an overview of our research, software design process and implementation.