A predictive risk evaluation framework for modular product concept selection in new product design environment

The purpose of this research is to help product managers in an original equipment manufacturer at early stages of new product design (NPD) to choose the best design concept for subsequent development and commercialisation that is associated with least risk to the enterprise. The product considered in this research is modular and repairable in nature. Considerations such as the availability of different module instances for different modules and the respective mean time to repair reflect the modularity and reparability aspect of the product considered in this research. In order to develop a comprehensive risk evaluation framework, generic and high-level risk characteristics pertaining to multiple functional agencies involved in NPD are considered. These risk characteristics represent relevant technical and commercial risk parameters corresponding to the six different functional agencies, i.e. design, supply chain, manufacturing, marketing, quality assurance, and after-sales support. Bayesian network methodology is adopted to map the relationship among various risk parameters denoted by parent and root nodes. Thereafter, a new measure, i.e. Overall Enterprise Risk Index is devised that weighs all possible design concepts in terms of an aggregate risk number. The proposed methodology is illustrated using a real-life case of ROPS canopy of heavy construction machinery.