Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports
This study proposes a practical method for the early detection of failure signs in a rotating biological contactor (RBC) system that has been in long-term operation at a municipal solid waste landfill. Seventeen years of inspection logs, recorded between 2006 and 2023, were digitized and analyzed wi...
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MDPI AG
2025-06-01
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| author | Hiroyuki Ishimori Yugo Isobe Tomonori Ishigaki Masato Yamada |
| author_facet | Hiroyuki Ishimori Yugo Isobe Tomonori Ishigaki Masato Yamada |
| author_sort | Hiroyuki Ishimori |
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| description | This study proposes a practical method for the early detection of failure signs in a rotating biological contactor (RBC) system that has been in long-term operation at a municipal solid waste landfill. Seventeen years of inspection logs, recorded between 2006 and 2023, were digitized and analyzed with a focus on abnormal noise, electric current values, operational status, and failure history. The analysis revealed that frequent occurrences of abnormal noise and sudden fluctuations in current tend to precede equipment failures. Based on these findings, we developed a scoring model for the predictive maintenance of RBCs. Traditionally, determining the score required professional knowledge such as performing a sensitivity analysis. However, by utilizing AI (ChatGPT o4), we were able to obtain recommended values for these parameters. This means that operators can now build and adjust a scoring model for predictive maintenance of RBCs according to their specific on-site conditions. On the other hand, sudden increases in current and abnormal noises were previously considered strong indicators of failure prediction. These parameters will depend on factors such as the sensitivity of electrical current meters and surrounding noise. Therefore, depending on the specific environmental conditions at the site, the scoring model developed in this study may have limited predictive accuracy. |
| format | Article |
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| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-bfe82ca61a504b799c9f838019052ff22025-08-20T02:35:47ZengMDPI AGApplied Sciences2076-34172025-06-011513695010.3390/app15136950Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection ReportsHiroyuki Ishimori0Yugo Isobe1Tomonori Ishigaki2Masato Yamada3Material Cycles Division, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba 305-8506, Ibaraki, JapanMaterial Cycles and Waste Management Group, Center for Environmental Science in Saitama (CESS), 914 Kamitanadare, Kazo 347-0115, Saitama, JapanMaterial Cycles Division, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba 305-8506, Ibaraki, JapanMaterial Cycles Division, National Institute for Environmental Studies (NIES), 16-2 Onogawa, Tsukuba 305-8506, Ibaraki, JapanThis study proposes a practical method for the early detection of failure signs in a rotating biological contactor (RBC) system that has been in long-term operation at a municipal solid waste landfill. Seventeen years of inspection logs, recorded between 2006 and 2023, were digitized and analyzed with a focus on abnormal noise, electric current values, operational status, and failure history. The analysis revealed that frequent occurrences of abnormal noise and sudden fluctuations in current tend to precede equipment failures. Based on these findings, we developed a scoring model for the predictive maintenance of RBCs. Traditionally, determining the score required professional knowledge such as performing a sensitivity analysis. However, by utilizing AI (ChatGPT o4), we were able to obtain recommended values for these parameters. This means that operators can now build and adjust a scoring model for predictive maintenance of RBCs according to their specific on-site conditions. On the other hand, sudden increases in current and abnormal noises were previously considered strong indicators of failure prediction. These parameters will depend on factors such as the sensitivity of electrical current meters and surrounding noise. Therefore, depending on the specific environmental conditions at the site, the scoring model developed in this study may have limited predictive accuracy.https://www.mdpi.com/2076-3417/15/13/6950waste landfillleachate treatment facilityrotating biological contactorspreventive maintenancedaily inspection reportsartificial intelligence |
| spellingShingle | Hiroyuki Ishimori Yugo Isobe Tomonori Ishigaki Masato Yamada Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports Applied Sciences waste landfill leachate treatment facility rotating biological contactors preventive maintenance daily inspection reports artificial intelligence |
| title | Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports |
| title_full | Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports |
| title_fullStr | Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports |
| title_full_unstemmed | Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports |
| title_short | Empirical Study on Failure Prediction of Rotating Biological Contactors Available for Landfill Site Operators: Scoring Analysis Based on 17-Year Daily Inspection Reports |
| title_sort | empirical study on failure prediction of rotating biological contactors available for landfill site operators scoring analysis based on 17 year daily inspection reports |
| topic | waste landfill leachate treatment facility rotating biological contactors preventive maintenance daily inspection reports artificial intelligence |
| url | https://www.mdpi.com/2076-3417/15/13/6950 |
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