Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163057
Title: Start-up monitoring for intermittent manufacturing based on hierarchical stationarity analysis
Authors: Qin, Yan
Yin, Xunyuan
Keywords: Engineering::Chemical engineering
Issue Date: 2022
Source: Qin, Y. & Yin, X. (2022). Start-up monitoring for intermittent manufacturing based on hierarchical stationarity analysis. Chemical Engineering Research and Design, 185, 26-36. https://dx.doi.org/10.1016/j.cherd.2022.06.037
Project: RS15/ 21
NTU-SUG 
Journal: Chemical Engineering Research and Design
Abstract: Intermittent manufacturing is becoming increasingly popular due to its capability of coping with dynamic changes in market demands. The operation of the intermittent manufacturing equipment is subject to frequent restarts as the type of product being produced is switched, and it is challenging to achieve consistency in production during the start-up phase when restarts take place. Timely identification and monitoring of this phase is critical for avoiding the waste of materials and improving the product quality for intermittent manufacturing. In this work, a hierarchical stationarity analysis is proposed for the monitoring of the start-up phase process operation of intermittent manufacturing to extract two types of stationary information. First, consistently invariant process variations among batches are separated using a Kullback-Leibler divergence-based feature extraction method. In this way, process variations in each batch are divided into two subspaces – the stationary subspace and the remaining non-stationary subspace. Cointegration analysis is performed on the non-stationary subspace to capture the stationary information to find the long-term equilibrium during the start-up phase. Based on the divided subspaces, the start-up phase is identified, and process abnormalities can be online monitored. The efficacy of the proposed method is illustrated through a plastic molding process.
URI: https://hdl.handle.net/10356/163057
ISSN: 0263-8762
DOI: 10.1016/j.cherd.2022.06.037
Rights: © 2022 Institution of Chemical Engineers. All rights reserved. This paper was published by Elsevier Ltd. in Chemical Engineering Research and Design and is made available with permission of Institution of Chemical Engineers.
Fulltext Permission: embargo_20241007
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles
SCBE Journal Articles

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