Design for Reliability Through Text Mining and Optimal Product Verification and Validation Planning

Abstract

Failure mode and effects analysis (FMEA) has been widely used in product design process as a reliability analysis technique. Design FMEA (DFMEA), which is used in the product development phase to identify and mitigate product risk, is one of the three application scenarios of FMEA. During the DFMEA process, verification and validation (V&V) activities are proposed to mitigate the risk of the identified potential failure modes. The V&V activities can be further planned and implemented to improve the product reliability under development. However, the DFMEA report usually contains rich text descriptions of potential failure modes and causes, and it is difficult and nonintuitive to fully understand these information for design improvements. In addition, it is also very challenging to optimize the planning of V&V activities by selecting a set of V&V activities to achieve expected reliability improvement effectiveness with the minimum resource consumption requirement. To address these two challenges, this article first proposes a method of applying text mining to the DFMEA report to obtain two types of hidden reliability information, including the classifications of failure modes/causes and the correlation between keywords. Then, a mathematical model is proposed to optimize the product V&V planning by selecting an optimal set of V&V activities. The application of the above proposed methods is illustrated through the product development of a diesel engine power generation system.