The multi-objective optimization involves multiple, competing functionality requirements, which is mainly limited to downstream detailed design. Axiomatic design provides the theory to design a complex system top down and deals with multiple functional requirements (FR). It has demonstrated its strength in various types of design tasks. In fact, the objective function is a FR and those variables affecting the objective function are the design parameters (DPs). This paper presents an application of axiomatic design to multi-objective optimization. First, identify the relationship between FRs and DPs in terms of contribution of each DP to each FR by using orthogonal experiment and analysis of variance (ANOVA); then identify important design parameters to a FR and classify design variables into groups based on uncoupled design philosophy; and then establish the function dependence table, and sequentially optimize every objective function. An application in a disk brake design is used to demonstrate the use of the proposed method in dealing with real-world design problems. The results show that the proposed method provides a promising approach to optimize multiple, competing design objectives.