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Statistical parametric and non-parametric control charts for monitoring residential water consumption
The adoption of strategies for monitoring water consumption is essential for water resources management, contributing to the promotion of the sustainability in the water sector. Statistical process control (SPC) charts, which are widely used in the industrial sector, are statistical methods develope...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439885/ https://www.ncbi.nlm.nih.gov/pubmed/37598231 http://dx.doi.org/10.1038/s41598-023-40584-w |
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author | Bogo, Allyson Belli Henning, Elisa Kalbusch, Andreza |
author_facet | Bogo, Allyson Belli Henning, Elisa Kalbusch, Andreza |
author_sort | Bogo, Allyson Belli |
collection | PubMed |
description | The adoption of strategies for monitoring water consumption is essential for water resources management, contributing to the promotion of the sustainability in the water sector. Statistical process control (SPC) charts, which are widely used in the industrial sector, are statistical methods developed to improve the quality of products and processes. The application of this method has reached other areas over the last decades and has recently been identified as an option for environmental monitoring. In this context, the application of SPC charts emerges as an option for water consumption monitoring, whether in a building or an urban scale. Thus, this article aims to analyze the application of statistical process control charts in the monitoring of water consumption of two housing compounds in Joinville, southern Brazil. The methodological procedures include the use of the Shewhart and the EWMA control charts in addition to the non-parametric alternative, the EWMA-SN, assessing the effectiveness of these techniques in detecting water leaks in residential apartment buildings. The data sets, obtained through a telemetry metering system from the water utility, represent a period of 243 days. The results show that control charts are a powerful tool in identifying changes in water consumption patterns, with the EWMA chart flagging the leaks sooner. |
format | Online Article Text |
id | pubmed-10439885 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104398852023-08-21 Statistical parametric and non-parametric control charts for monitoring residential water consumption Bogo, Allyson Belli Henning, Elisa Kalbusch, Andreza Sci Rep Article The adoption of strategies for monitoring water consumption is essential for water resources management, contributing to the promotion of the sustainability in the water sector. Statistical process control (SPC) charts, which are widely used in the industrial sector, are statistical methods developed to improve the quality of products and processes. The application of this method has reached other areas over the last decades and has recently been identified as an option for environmental monitoring. In this context, the application of SPC charts emerges as an option for water consumption monitoring, whether in a building or an urban scale. Thus, this article aims to analyze the application of statistical process control charts in the monitoring of water consumption of two housing compounds in Joinville, southern Brazil. The methodological procedures include the use of the Shewhart and the EWMA control charts in addition to the non-parametric alternative, the EWMA-SN, assessing the effectiveness of these techniques in detecting water leaks in residential apartment buildings. The data sets, obtained through a telemetry metering system from the water utility, represent a period of 243 days. The results show that control charts are a powerful tool in identifying changes in water consumption patterns, with the EWMA chart flagging the leaks sooner. Nature Publishing Group UK 2023-08-19 /pmc/articles/PMC10439885/ /pubmed/37598231 http://dx.doi.org/10.1038/s41598-023-40584-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bogo, Allyson Belli Henning, Elisa Kalbusch, Andreza Statistical parametric and non-parametric control charts for monitoring residential water consumption |
title | Statistical parametric and non-parametric control charts for monitoring residential water consumption |
title_full | Statistical parametric and non-parametric control charts for monitoring residential water consumption |
title_fullStr | Statistical parametric and non-parametric control charts for monitoring residential water consumption |
title_full_unstemmed | Statistical parametric and non-parametric control charts for monitoring residential water consumption |
title_short | Statistical parametric and non-parametric control charts for monitoring residential water consumption |
title_sort | statistical parametric and non-parametric control charts for monitoring residential water consumption |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439885/ https://www.ncbi.nlm.nih.gov/pubmed/37598231 http://dx.doi.org/10.1038/s41598-023-40584-w |
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