Dynamic production system diagnosis and prognosis using model-based data-driven method
作者：
Highlights：
• A data-driven stochastic manufacturing system model is proposed.
• Real-time system performance identification method is developed.
• Prediction method for future potential system performance is developed.
摘要
•A data-driven stochastic manufacturing system model is proposed.•Real-time system performance identification method is developed.•Prediction method for future potential system performance is developed.
论文关键词：Data-driven modeling,Production system diagnosis and prognosis,Permanent production loss,Disruption event
论文评审过程：Received 16 March 2016, Revised 12 March 2017, Accepted 13 March 2017, Available online 16 March 2017, Version of Record 23 March 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.03.025
