Optimal resource allocation for dynamic product development process via convex optimization

Resource allocation is an essential aspect of successful Product Development (PD). In this paper, we formulate the dynamic resource allocation problem of the PD process as a convex optimization problem. Specially, we build and solve two variants of this problem: the budget-constrained problem and the performance-constrained problem. We use convex optimization as a framework to optimally solve large problem instances at a relatively small computational cost. The solutions to both problems exhibit similar trends regarding resource allocation decisions and performance evolution. Furthermore, we show that the product architecture affects resource allocation, which in turn affects the performance of the PD process. By introducing centrality metrics for measuring the location of the modules and design rules within the product architecture, we find that resource allocation decisions correlate to their metrics. These results provide simple, but powerful, managerial guidelines for efficiently designing and managing the PD process. Finally, for validating the model and its results, we introduce and solve two design case studies for a mechanical manipulator and for an automotive appearance design process.