Research issues in the domain of A.I. for design can be organized in three categories: decision making, representation and knowledge handling. In the area of knowledge handling, this paper addresses issues concerning the management of design experience to guide a priori the generation of candidate solutions. The approach is based on keeping the trace of a previous design experience as a hierarchical knowledge base. A level in the hierarchy can be viewed as a level of granularity of the description of the design process. A general framework for defining a partial order function between the granularity levels in the knowledge bases of design expertise is proposed. It is then possible to compute the sets of the elements belonging to smaller granularity levels, which are linked to any component of the hierarchy. Thus, it makes it possible to compute the level in the hierarchy that can be reused without modification for the design of a new product. Computation of the appropriate level is mainly based on matching the data corresponding to the new requirements with these sets. The approach has been tested by using a multiple expert systems structure based on using interactively two systems, an expert system development tool for design, KAUS, and an expert system development tool for diagnosing engineering processes, SUPER. The intrinsic properties of SUPER have also been used for improving the design procedure when qualitative and quantitative knowledge is involved.