Risk-Informed Design Verification and Validation Planning Methods for Optimal Product Reliability Improvement

Abstract

This chapter proposes four types of mathematical optimization modeling approaches to optimize the product design Verification and Validation (V&V) planning during the New Product Development (NPD) process. These four optimization models provide four risk mitigation strategies from perspectives of cost efficiency to the optimal selection of a set of V&V activities for maximizing the overall system reliability improvement. The proposed approaches not only incorporate the critical product development constraints in V&V planning, such as the cost, time, reliability improvement, and sequencing and effectiveness of V&V activities, but also consider the decay of the improvement effectiveness when tackling the V&V activities’ selecting and sequencing challenges. In addition, the concepts of set covering, set partition, and set packing are applied to assure that different levels of critical failure modes can be covered in different ways according to different risk mitigation requirements by the end of V&V execution. The application of the proposed optimization models and comparisons with existing methods for product V&V planning are illustrated through the product development of a power generation system within a diesel engine.