Digital manufacturing significantly reduces the expense and time required to produce custom products. Utilizing this technology, a customized product can be quickly manufactured. But the timescale and expense of the engineering design workflows used to develop these customized products have not been adapted from the workflows used in mass production due to the development of high fidelity models. But with digital manufacturing the economies of scale are eliminated such that producing many unique designs or many of the same designs result in the same manufacturing cost. Developing a design workflow that utilizes the developed and validated high fidelity models of the already produced design can reduce the amount of time and expense developing a slightly varied customized design. Reduced order modeling enables this reuse and magnification of existing high fidelity models by creating a computationally inexpensive representation of a model from high fidelity data. This thesis explores the integration of reduced order modeling and detailed analysis into the engineering design workflow developing a customized design using digital manufacturing. Specifically detailed analysis is coupled with proper orthogonal decomposition to enable the exploration of the design space while simultaneously shaping the model representing the design. This revised workflow is examined using the design of a laboratory scale overhead mixing impeller. The case study presented here is compared with the design of the Kar Dynamic Mixer developed by the Dow Chemical Company. The result of which is a customized design for a refined set of operating conditions with improved performance.