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Found 4 papers, 0 papers with code
An Interdisciplinary Outlook on Large Language Models for Scientific Research
In this paper, we describe the capabilities and constraints of Large Language Models (LLMs) within disparate academic disciplines, aiming to delineate their strengths and limitations with precision.
Stochastic Deep Koopman Model for Quality Propagation Analysis in Multistage Manufacturing Systems
This study introduces a stochastic deep Koopman (SDK) framework to model the complex behavior of MMSs.
Shapley-based Explainable AI for Clustering Applications in Fault Diagnosis and Prognosis
The rules, limited to 1-2 terms utilizing original feature scales, describe 12 out of the 16 derived equipment failure clusters with precision exceeding 0. 85, showcasing the promising utility of the explainable clustering framework for intelligent manufacturing applications.
Fault Prognosis of Turbofan Engines: Eventual Failure Prediction and Remaining Useful Life Estimation
In the era of industrial big data, prognostics and health management is essential to improve the prediction of future failures to minimize inventory, maintenance, and human costs.
