Traditional methods in engineering design involve producing solutions at a single level. However, in complex engineering design problems, such as concurrent product and materials design, various levels of model complexity are considered. A design process in which design problems are defined and analyzed at various levels of design complexity is referred to as multilevel design. One example of multilevel design is the design of a material, product, assembly, and system. Dividing a design problem into multiple levels increases the possibility for introducing and propagating uncertainty. Design solutions that perform predictably in the presence of uncertainty are robust designs. Robust design concepts that were originally developed for designs at a single level can be applied to a multilevel design process. The Inductive Design Exploration Method (IDEM) is an existing design method used to produce robust multilevel design solutions. In this thesis, the strategy presented in IDEM is incorporated into design templates in order to extend its overall usefulness. Design templates are generic, reusable, modules that provide the theoretical and computational framework for solving design problems. Information collected, stored, and analyzed from design templates is leveraged for a variety of design problems. In this thesis, the possibilities of a template-based approach to multilevel design are explored. Two example problems, which employ the developed multilevel robust design template, are considered. Multilevel design templates are created for the design of a cantilever beam and its associated material and the design of a blast resistant panel. The design templates developed for example problems can be extended to facilitate a generic, modular, template-based approach to multilevel robust design.

Materials have traditionally been selected for the design of a product; however, advances in the understanding of material processing along with simulation and computation techniques are now making it possible to systematically design materials by tailoring the properties of the material to achieve the desired product performance. Material design offers the potential to increase design freedom and enable improved product performance; however, this increase in design freedom brings with it significant complexity in predictive models used for design, as well as many new design variables to consider. Material selection, on the other hand, is a well-established method for identifying the best materials for a product and does not require the complex models needed for material design. But material selection inherently limits the design of products by only considering existing materials. To balance increasing design costs with potentially improved product performance, designers must have a method for assessing the value of material design in the context of product design. In this thesis, the Design Space Expansion Strategy (DSES) and the Value of Design Space Expansion (VDSE) metric are proposed for supporting a designer s decision between material selection and material design in the context of product design. The strategy consists of formulating and solving two compromise Decision Support Problems (cDSP). The first cDSP is formulated and solved using a selected baseline material. The second cDSP is formulated and solved in an expanded material design space defined by material property variables in addition to other system variables. The two design solutions are then compared using the VDSE metric to quantify the value of expanding the material design space. This strategy is demonstrated in this thesis with an example of blast resistant panel design and is validated by application of the validation square, a framework for the validating design methods.