Recently, we proposed the Selection-Integrated Optimization (SIO) methodology for designing adaptive systems. In this paper, we investigate the applicability of the SIO methodology in the field of product family optimization. A typical product family consists of multiple products that share common features embodied in a, so-called, platform, defined in terms of platform design variables. Different products in the family are developed by customizing specific non-platform features of the platform, defined in terms of non-platform design variables. In the optimization of such product families, the specific values - as well as the choice -of the platform and non-platform design variables are critical. Often, the product family optimization follows a two-step process that can be a significant source of sub-optimality. It is this very issue that we address in this paper. Specifically, the Selection-Integrated Optimization (SIO) methodology integrates two key processes that are typically treated separately: (1) the selection of the platform and non-platform design variables, and (2) the optimization of the product family, thereby eliminating a significant source of sub-optimality. We facilitate the integration of these two key processes with the help of a Variable-Segregating Mapping-Function (VSMF). In this paper, we illustrate the application of the SIO methodology in the design of an electric motor product family. The paper also further explores the general effectiveness of the SIO methodology by performing a number of parametric studies - illustrating its numerical robustness.