Existing research on the design and analysis of front-loading washing machines has primarily focused on maximizing performance of a single product based on specific disciplinary analyses (e.g., vibration, dynamics). This design approach does not necessarily guarantee low costs, high sales, and maximum profit. Moreover, in order to target a variety of different customer needs, washing machines should be thought of and designed as a product family. In this paper, we suggest a value-driven design approach for a family of front-loading washing machines to identify promising solutions based on stakeholder's preference. To create a value function, the sales volume for front-loading washers is estimated based on sales rank data, and then the net present value (NPV) is formulated by using the estimated sales volume and a demand sensitivity curve derived from the literature and publicly available data. The result shows that we can determine product family design candidates that maximize NPV, performance, and commonality of scalable and platform (i.e., shared) variables in the washer family. We also investigate the effectiveness of reducing the complexity of the value function based on rank ordering and parametric studies of the attributes used to compute NPV.