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Tangbin Xia
Researcher at Shanghai Jiao Tong University
Publications - 106
Citations - 1992
Tangbin Xia is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 18, co-authored 69 publications receiving 1077 citations. Previous affiliations of Tangbin Xia include Georgia Institute of Technology & University of Michigan.
Papers
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Recent advances in prognostics and health management for advanced manufacturing paradigms
TL;DR: This paper addresses recent advances in PHM for advanced manufacturing paradigms to forecast health trends, avoid production breakdowns, reduce maintenance cost and achieve rapid decision-making.
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An ensemble framework based on convolutional bi-directional LSTM with multiple time windows for remaining useful life estimation
TL;DR: An ensemble framework based on convolutional bi-directional long short-term memory with multiple time windows (MTW CNN-BLSTM Ensemble) for accurately predicting RUL and can achieve the minimum prediction error and provide stable support for equipment health management is proposed.
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Production-driven opportunistic maintenance for batch production based on MAM-APB scheduling
TL;DR: A novel production-driven opportunistic maintenance strategy is developed by considering both machine degradation and characteristics of batch production and advance-postpone balancing (APB) utilizes set-up times as opportunities to make real-time schedules for system-level maintenance.
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Dynamic maintenance decision-making for series–parallel manufacturing system based on MAM–MTW methodology
TL;DR: A novel dynamic maintenance strategy is developed to incorporate both the single-machine optimization and the whole-system schedule for series–parallel system to make a cost-effective system schedule by dynamically utilizing maintenance opportunities.
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Hidden Markov model with auto-correlated observations for remaining useful life prediction and optimal maintenance policy
TL;DR: A hidden Markov model with auto-correlated observations (HMM-AO) is developed to handle the degradation modeling of manufacturing systems and two remaining useful life prediction methods based on the HMM- aO model are developed.