Modern software systems are developed using multiple models to represent different properties of the system. Since these models contain dependent information, keeping them consistent is crucial for producing correctly operating software. This process can be automated with model transformations, and has been researched mainly for binary transformations that define consistency preservation for pairs of metamodels. If more than two metamodels are involved, the combination of several binary transformations leads to problems such as interoperability issues and occurring trade-off decisions. Therefore, we investigate these problems in multi-model consistency preservation in our thesis. We first analyze the interoperability of binary transformations that have been independently developed and derive patterns for non-intrusive transformation interoperability. Furthermore, we introduce an approach for decomposing consistency relations and concept metamodels that make relations explicit. This is supposed to reduce the necessity for trade-off decisions regarding challenges such as compatibility of dependent transformations and modularity of used metamodels and transformations, as well as comprehensibility and evolvability. The proposed benefit of our approach is that independently developed binary transformations can be combined, omitting interoperability issues without the necessity to know about each other, to achieve multi-model consistency. We will evaluate our approach with case studies from component-based and object-oriented software, as well as with industrial case studies for embedded automotive software and production systems.