This paper presents a model-based approach for the multi-objective design of optimized diagnosis functions for high lift actuation systems. These systems are used to augment lift at low speed during takeoff and landing, and are safety critical. This demands requirements to the detection of failures and the isolation of root causes in order to provide a high availability at low risk. Dedicated functions cover the determination of features, the detection of symptoms and the isolation of root causes by means of inference and resolution. The aim of the design approach is to provide these functions in an optimal manner with respect to multiple objectives. In order to be clear and traceable the approach consists of separate consecutive steps. These are arranged by using systems engineering principles. With respect to requirements, models of different levels of detail are developed and used to design stepwise all required functions. This is done by evaluating cause-effect matrices, temporal information about the appearance of effects, and a configuration graph. This contains relationships between sensors and symptoms and provides cost criteria for a final assessment. There, solutions of Pareto optimal diagnosis functions with respect to the design objectives are identified. A radial visualization method is used to display all optimal solutions and assist in the identification of a single solution. This solution has to be detailed in further steps. In summary, a clear support of the design process for diagnosis functions by multi-objective and multi-step optimization with practical application is presented.