Implementing Value-Driven Design in Modelica for a racing solar boat
Joshua Sutherland, Alejandro Salado, Kazuya OIZUMI, Kazuhiro AOYAMA
15th Annual Conference on Systems Engineering Research
Los Angeles, California
Research has shown that current design approaches, such as requirement-based design or Cost As Independent Variable (CAIV), may fundamentally yield suboptimal designs. In response to the need for better systems, new design techniques that are based on optimization and decision-making have been proposed. In this paper, we show how Modelica can be used to implement and operationalize Value-Driven Design (VDD) in concept selection. Modelica’s object-oriented strengths are employed to model design alternatives and its capability to execute Monte Carlo simulation enables the introduction of uncertainty in models and assessment. The proposed approach has been applied to the conceptual design of an unmanned, autonomous solar powered boat, which is aimed at racing in a student competition. Value has been defined as a function of the probability to win the said race, which expands usual examples of value functions to non-monetary ones. This paper describes the approach as well as the benefits, limitations, and obstacles encountered during its implementation.