Design for workshare: A framework to identify and evaluate distributed work risk

Global companies realize the importance of collaborative design, or workshare, to develop products not only to target particular markets, but to sell to the entire world. This paradigm enables diverse customer values to be integrated into products and exploits the economy of scale across distributed resources, but it also introduces challenges in workshare management. Industry benchmarks have shown that informal metrics drive workshare decisions. Seeing the opportunity, this dissertation develops an analytical risk framework to manage global product development.; The proposed risk framework is based on the risk of rework due to the deployment of work tasks among distributed teams and is divided into two levels. Component Risk is defined as the risk of rework for a component based on the distribution of its product development work, whereas System Risk refers to the risk of rework for a subsystem when the design of coupled systems, either functionally or physically, are distributed. This framework assumes programs with more distributed, highly-correlated work generate higher risk. To confirm the risk results, this study has sought statistical evidence to show that workshare programs generate higher risk of rework due to the distribution of work.; This dissertation has applied the framework to a hair dryer and a global vehicle program as case studies. More than illustrating the steps, the cases test the applicability of the risk formulation algorithm in simple and complex designs. Both studies show reasonable risk assessments; the vehicle study, in particular, gathered useful feedbacks from the potential users and prompted a number of opportunities to explore the behavior of the framework.; This dissertation is a pioneer in collaborative product development research. The risk framework provides a structured approach to quantify workshare risk, and to identify risk operations in order to evaluate workshare scenarios. The framework only uses existing data and does not invent any new metric for risk assessment. Most important, the risk formulation is a robust algorithm, adoptable to other product life-cycle management applications such as supplier relationships. As a conclusion, this dissertation presents a few research opportunities to refine the framework and to extend it to other product development markets.