Reverse engineering, defined as extracting information about a product from the product itself, is a common industry practice for gaining insight into innovative products. Both the original designer and those reverse engineering the original design can benefit from estimating the time and barrier to reverse engineer a product. This thesis presents a set of metrics and parameters that can be used to calculate the barrier to reverse engineer any product as well as the time required to do so. To the original designer, these numerical representations of the barrier and time can be used to strategically identify and improve product characteristics so as to increase the difficulty and time to reverse engineer them. One method for increasing the time and barrier to reverse engineer a product – presented in this thesis – is to treat material microstructures (crystallographic grain size, orientation, and distribution) as continuous design variables that can be manipulated to identify unusual material properties and to design devices with unexpected mechanical performance. A practical approach, carefully tied to proven manufacturing strategies, is used to tailor material microstructures by strategically orienting and laminating thin anisotropic metallic sheets. This approach, coupled with numerical optimization, manipulates material microstructures to obtain desired material properties at designer-specified locations (heterogeneously) or across the entire part (homogeneously). As the metrics and parameters characterizing the reverse engineering time and barrier are also quantitative in nature, they can also be used in conjunction with numerical optimization techniques, thereby enabling products to be developed with a maximum reverse engineering barrier and time – at a minimum development cost. On the other hand, these quantitative measures enable competitors who reverse engineer original designs to focus their efforts on products that will result in the greatest return on investment. While many products were analyzed in an empirical study demonstrating that the characterization of the time to reverse engineer a product has an average error of 12.2%, we present the results of three different products. Two additional examples are also presented showing how microstructure manipulation leads to product hardware with unexpected mechanical performance effectively increasing reverse engineering time and barrier.