A Multi-Objective Evolutionary Algorithm (MOEA) is proposed for the identification of association rules describing functional dependencies in Complex Technical Infrastructures (CTIs). The algorithm uses novelty search to explore the solution space. It has been applied to a real large-scale database of alarms collected in the CTI of CERN (European Organization for Nuclear Research). The obtained results show its effectiveness in identifying rare functional dependencies not found using standard algorithms of Association Rule Mining (ARM) algorithms.