Results 21 to 30 of about 1,558,454 (317)
Quality-Analysis-Based Process Monitoring for Multi-Phase Multi-Mode Batch Processes
, 2021 In batch processing, not only the characteristics of different phases are different, but also there may be different characteristics between batches. These characteristics of different phases and batches will have different effects on the final product ...
Hao Yu, Xin Huang, Luping Zhao
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Remote Monitoring the Parameters of Interest in the 18O Isotope Separation Technological Process
, 2023 This manuscript presents the remote monitoring of the main parameters in the 18O isotope separation technological process. It proposes to monitor the operation of the five cracking reactors in the isotope production system, respectively, the temperature ...
Vlad Muresan +3 more
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IEEE Access, 2018 Faults and malfunctions on complex chemical production systems generate alarm cascades that hinder the work of the operators and make fault diagnosis a complex and challenging task.
Gyula Dorgo, Kristof Varga, Janos Abonyi
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Incorporating spatial context into remaining-time predictive process monitoring [PDF]
, 2021 Predictive business process monitoring aims to accurately predict a variable of interest (e.g. remaining time) or the future state of the process instance (e.g. outcome or next step).
Ogunbiyi, Niyi +2 more
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Multilayer Network-Based Production Flow Analysis
Complexity, 2018 A multilayer network model for the exploratory analysis of production technologies is proposed. To represent the relationship between products, parts, machines, resources, operators, and skills, standardized production and product-relevant data are ...
Tamás Ruppert +2 more
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Sensors, 2019 AC arc faults are one of the most important causes of residential electrical wiring fires, which may produce extremely high temperatures and easily ignite surrounding combustible materials.
Kai Yang +4 more
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, 2022 Traditional multivariate statistical methods, which are often used to monitor stationary processes, are not applicable to nonstationary processes. Cointegration analysis (CA) is considered an effective method to deal with nonstationary variables.
Jingzhi Rao +4 more
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A review of kernel methods for feature extraction in nonlinear process monitoring [PDF]
, 2019 Kernel methods are a class of learning machines for the fast recognition of nonlinear patterns in any data set. In this paper, the applications of kernel methods for feature extraction in industrial process monitoring are systematically reviewed.
Lao, L. +14 more
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, 2020 Modern industrial units collect large amounts of process data based on which advanced process monitoring algorithms continuously assess the status of operations.
Rato, Tiago J. +7 more
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, 2023 Advances in additive manufacturing (AM) processes have increased the number of relevant applications in various industries. To keep up with this development, the process stability of AM processes should be monitored, which is conducted through the ...
Moath Alatefi +3 more
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