It is common for materials processing operations to have adjustable features that may be used to improve the quality of the final product when variability in operating conditions is encountered. This paper considers the polymer sheeting die design problem where variability in operating temperature or material properties, for example, requires that the die be designed to perform well under multiple operating conditions. An optimization procedure is presented where the design variables parametrize both stationary and adjustable model variables. In this approach, adjustable features of the die cavity are modified in an optimal manner consistent with the overall design objectives. The computational design approach incorporates finite element simulations based on the Generalized Hele-Shaw approximation to evaluate the die’s performance measures, and includes a gradient-based optimization algorithm and analytical design sensitivities to update the die’s geometry. Examples are provided to illustrate the design methodology where die cavities are designed to accommodate multiple materials, multiple flow rates, and various temperatures. This paper demonstrates that improved tooling designs may be computed with an optimization-based process design approach that incorporates the effect of adjustable features.