Optimal burn-in strategy for high reliable products using convolutional neural network

• Main Authors: Lyu, Yi, Gao, Junyan, Chen, Ci, Jiang, Yijie, Li, Huachuan, Chen, Kairui, Zhang, Yun
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Burn-in; Deep Learning
• Online Access: https://hdl.handle.net/10356/145919
• Institution: Nanyang Technological University

Burn-in test is widely used to improve the product reliability from the customer's perspective by identifying and screening out defective individuals before they are marketed. For those high reliable products whose failures are caused by gradual degradation, burn-in test not only could pick out...