Design and Implementation of an Intelligent Classification and Reliability Prediction Tool based on Cloud Platform
Jieyu Chen, Qiuxiang Wang, Yadong Ling, Shizhang Liang, Li Meixian · 2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT) · 2021
Reliability prediction is of great importance for electronic products design, and an indispensable technique to ensure that electronic components, equipment and the overall system meet their required reliability targets as well. Present methods, handbooks, standards and software tools of reliability prediction were studied and compared. For industrial and commercial electronic equipment applications, the development and demand of reliability prediction tools were analyzed in this paper. Using new-generation information technologies such as cloud computing and machine learning, a lightweight component reliability prediction tool was designed based on the Spring Cloud microservice architecture. In addition, the naive Bayesian algorithm was adopted to achieve intelligent components classification, which enhances prediction efficiency significantly. An example was offered, which verified the effectiveness of the cloud-based reliability prediction tool. Its characteristics of low-cost, rapidly-deployed and easy-to-use were shown, which differ it from traditional prediction tools, and make it suitable for commercial companies and electronic products.