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Much research has been accomplished in the last several years in trying to describe the dynamics of a complex design process in a quantitative, meaningful manner. Such methodologies have recently been implemented in an academic setting, where there is a need for instructors developing their own design projects to have a meaningful method of quantifying the relative difficulty and feasibility of completion of such project in a limited time academic term. Upper year projects (2 nd , 3 rd , and 4 th year) are often quite complex, multidisciplinary, and consist of many tasks with complex relationships which must be performed concurrently. One useful method that describes task relationships is the Design Structure Matrix (DSM), which along with its extension, the Work Transformation Matrix (WTM), have proven useful in predicting convergence of design iteration, as well as identifying particularly slow tasks. But design environments are uncertain and can undermine the stability of a design process. Also, even though familiarity with a design project allows the determination of a better dynamic model for the process than for a new project, even this model is not absolute and will contain uncertainties. Therefore, methodologies are needed to determine how resources can be reallocated to expedite slowly converging tasks with uncertainties present. In this paper, closed-loop control will be implemented to quantify and guide the reallocation of resources of a design process containing many coupled, concurrent design tasks to expedite particularly slow ones, as well as a methodology to overcome the uncertain nature of the design process model.

Implementing Closed-Loop Control in an Engineering Design Process in the Presence of Uncertainties