A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing

D Wu, S Liu, L Zhang, J Terpenny, RX Gao… - Journal of Manufacturing …, 2017 - Elsevier
Small-and medium-sized manufacturers, as well as large original equipment manufacturers
(OEMs), have faced an increasing need for the development of intelligent manufacturing …

[HTML][HTML] Knowledge-based problem solving in physical product development––A methodological review

P Burggräf, J Wagner, T Weißer - Expert Systems with Applications: X, 2020 - Elsevier
The manufacturing of products at low maturity levels (referred to as physical product
development) requires knowledge intensive nonconformance problem solving, yet …

Data-driven anomaly recognition for unsupervised model-free fault detection in artificial pancreas

L Meneghetti, M Terzi, S Del Favero… - … on Control Systems …, 2018 - ieeexplore.ieee.org
The last decade has seen tremendous improvements in technologies for Type 1 Diabetes
(T1D) management, in particular the so-called artificial pancreas (AP), a wearable closed …

A novel decentralized process monitoring scheme using a modified multiblock PCA algorithm

C Tong, X Yan - IEEE Transactions on Automation Science and …, 2015 - ieeexplore.ieee.org
Decentralized process monitoring based on purely data-based methods has recently gained
considerable attention in multivariate statistical process monitoring circle. Although the …

Fault diagnosis method of joint fisher discriminant analysis based on the local and global manifold learning and its kernel version

J Feng, J Wang, H Zhang, Z Han - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Though Fisher discriminant analysis (FDA) is an outstanding method of fault diagnosis, it is
usually difficult to extract the discriminant information in a complex industrial environment …

A quality-relevant sequential phase partition approach for regression modeling and quality prediction analysis in manufacturing processes

C Zhao - IEEE Transactions on Automation Science and …, 2013 - ieeexplore.ieee.org
Competition and demand for consistent and high-quality product have spurred the
development of quality prediction methods for industrial manufacturing processes …

[PDF][PDF] 基于相关向量机的故障诊断方法研究

陈康, 熊建斌, 苏乃权, 王颀, 余得**, **春林 - 机床与液压, 2022 - qikan.cmes.org
相关向量机(RVM) 是目前最受关注的新一代模式识别技术之一, 阐述了基于相关向量机的故障
诊断方法, 应用前景等. 介绍相关向量机的分类, 回归模型及其国内外研究进展; 对RVM …

Fault diagnosis in multistation assembly systems using spatially correlated bayesian learning algorithm

K Bastani, B Barazandeh… - Journal of …, 2018 - asmedigitalcollection.asme.org
The problem of fault diagnosis for dimensional integrity in multistation assembly systems is
addressed in this paper. Fault diagnosis under this context is to identify the process errors …

PEN: Process estimator neural network for root cause analysis using graph convolution

V Leonhardt, F Claus, C Garth - Journal of Manufacturing Systems, 2022 - Elsevier
Root cause analysis in modern multistage assembly lines is a challenging, yet widely used
technique to increase the product quality. Improvements–due to Industry 4.0–aim for near …

Diesel engine fault diagnosis using intrinsic time-scale decomposition and multistage Adaboost relevance vector machine

Y Liu, J Zhang, K Qin, Y Xu - Proceedings of the Institution of …, 2018 - journals.sagepub.com
Diesel engine is the most widely used power source of machines. However, faults occur
frequently and often cause terrible accidents and serious economic losses. Therefore, diesel …