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@article{Chioua:2015:10.1016/j.conengprac.2015.10.011,
author = {Chioua, M and Bauer, M and Chen, S-L and Schlake, JC and Sand, G and Schmidt, W and Thornhill, NF},
doi = {10.1016/j.conengprac.2015.10.011},
journal = {Control Engineering Practice},
pages = {149--158},
title = {Plant-wide root cause identification using plant key performance indicators (KPIs) with application to a paper machine},
url = {http://dx.doi.org/10.1016/j.conengprac.2015.10.011},
volume = {49},
year = {2015}
}

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TY  - JOUR
AB  - Previously, plant-wide disturbance analysis has looked into the propagation of faults through an industrial production process by investigating process measurements. However, the extent of the analysis has mostly been limited to a section of a plant. In this work, we propose a top-down approach which investigates measurements of the complete plant and identifies a section where the disturbance originates. Root cause analysis is carried out thereafter to pinpoint the faulty asset. The proposed approach has three novel elements: Using key performance indicators (KPI) as reference and starting point of the analysis, restricting measurements to a measurement type (e.g. flow) thus focusing on a section and applying the novel method of contribution plots of spectral PCA T2 statistic to find the contribution of each measurement towards the disturbance observed in the KPI. The approach is described and carried out on a paper machine where a quality KPI showed an established oscillation.
AU  - Chioua,M
AU  - Bauer,M
AU  - Chen,S-L
AU  - Schlake,JC
AU  - Sand,G
AU  - Schmidt,W
AU  - Thornhill,NF
DO  - 10.1016/j.conengprac.2015.10.011
EP  - 158
PY  - 2015///
SN  - 1873-6939
SP  - 149
TI  - Plant-wide root cause identification using plant key performance indicators (KPIs) with application to a paper machine
T2  - Control Engineering Practice
UR  - http://dx.doi.org/10.1016/j.conengprac.2015.10.011
VL  - 49
ER  -

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