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In order to determine target market and price, and design products/components for a family of front-loading washing machines, the coordination for decision-making from the corporate level down to the product and ultimately component levels is required. However, existing design research for many products focuses on analyzing single or multiple disciplines, even though optimizing local performance does not guarantee minimizing total cost at the product line level or maximizing value at the company level. In this work, we apply a multi-level value-driven design (VDD) approach to optimize a family of front-loading washing machines using a discipline-based decomposition. The VDD solutions obtained using discipline-based decomposition (DD) are compared with those obtained using product-based decomposition (PD). Consequently, the multi-level VDD approach based on DD for the washer family provides better performance for attributes than PD, but we observed that DD for the washer family does not guarantee maximizing the value function compared to PD because of the larger numbers of subsystems and consistency-related variables. Ongoing and future work to address this problem are discussed.

Companies usually launch families of products into the market to provide value to different segments based on different customer needs; however, most of the research on Value-Driven Design (VDD) in the literature has focused on modeling value functions and optimizing the design of single products, not families of products. In order to increase profit and minimize total cost for product design and manufacturing, VDD should be applicable to product family design. In this work, we propose a multi-level VDD approach for product family design by extending multidisciplinary design optimization methods. The multi-level VDD is applied to a family of front-loading washing machines to validate the effectiveness of the proposed approach. With this example, we demonstrate that design problems that optimize traditional objective functions (e.g., cost, performance) at each level do not necessarily maximize value when compared to an appropriate VDD formulation. On the other hand, when the value function is set as an objective function throughout the organization (company, product family, and product level), we find that the VDD formulation provides the best value. Future work based on these promising findings is also discussed.