Built-in reliability-oriented R-KQC intelligent identification based on SA-HHO and proactive reliability assurance strategy

Abstract

The integration of the built-in reliability (BIR) approach with reliability efforts from the design phase to the usage stage is crucial for ensuring the reliability of finished products. As an important carrier of product reliability, reliability-oriented key quality characteristics (R-KQCs) are present in all activities of the product life and are the core of BIR methods. Therefore, to improve the accuracy of identified R-KQCs from the big data of quality and reliability, a novel R-KQC intelligent identification method is proposed by adopting the simulated annealing-Harris hawk optimization (SA-HHO). First, the connotation of the BIR and R-KQC formation mechanism are introduced. Second, considering the large amounts of quality and reliability data, an identification method of R-KQCs is proposed based on the fuzzy PFMEA (Process Failure Mode and Effects Analysis) and SA-HHO algorithm. Third, on the basis of R-KQC identification, the assurance method of R-KQCs is proposed for proactive optimization of parameters and control of the process. Finally, an example of the shielding component reliability assurance is provided to verify the validity of the proposed method.