Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension
Several sugar mills operate as waste-to-energy plants. The shredder is the initial high-energy machine in the production chain and prepares sugarcane. Its hammers, essential spare parts, require continuous replacement. Then, the search for intelligent strategies to extend the lifetime of these hamme...
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MDPI AG
2024-11-01
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| author | Diego Rodriguez-Obando Javier Rosero-García Esteban Rosero |
| author_facet | Diego Rodriguez-Obando Javier Rosero-García Esteban Rosero |
| author_sort | Diego Rodriguez-Obando |
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| description | Several sugar mills operate as waste-to-energy plants. The shredder is the initial high-energy machine in the production chain and prepares sugarcane. Its hammers, essential spare parts, require continuous replacement. Then, the search for intelligent strategies to extend the lifetime of these hammers is fundamental. This paper presents (a) a dynamic data-driven model for estimating the deterioration and predicting remaining life of the sugarcane shredder hammers during operation, for which the real data of the entering sugarcane flow and the power required to prepare the sugarcane are analyzed, and (b) a management architecture intended for online decision-making assistance to extend the hammers’ life by making a trade-off between the desired lifetime, along with a nominal shredder work satisfaction criterion. The deterioration model is validated with real data achieving an accuracy of 84.41%. The remaining life prognostic is within a confidence zone calculated from the historical sugarcane flow, with a probability close to 99%, fitting a lognormal probability distribution. A numerical example is also provided to illustrate a closed loop control, where the proposed architecture is used to extend the useful life of the hammers during operation, adjusting the incoming sugarcane flow while maintaining the nominal work satisfaction of the shredder. |
| format | Article |
| id | doaj-art-e491382ef48644c3937ab8b374bddd7e |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Mathematics |
| spelling | doaj-art-e491382ef48644c3937ab8b374bddd7e2024-11-26T18:11:39ZengMDPI AGMathematics2227-73902024-11-011222350710.3390/math12223507Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime ExtensionDiego Rodriguez-Obando0Javier Rosero-García1Esteban Rosero2EM&D Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, ColombiaEM&D Research Group, Department of Electrical and Electronic Engineering, Faculty of Engineering, Universidad Nacional de Colombia, Bogotá 111321, ColombiaIndustrial Control Research Group, School of Electrical and Electronic Engineering, Faculty of Engineering, Universidad del Valle, Cali 760032, ColombiaSeveral sugar mills operate as waste-to-energy plants. The shredder is the initial high-energy machine in the production chain and prepares sugarcane. Its hammers, essential spare parts, require continuous replacement. Then, the search for intelligent strategies to extend the lifetime of these hammers is fundamental. This paper presents (a) a dynamic data-driven model for estimating the deterioration and predicting remaining life of the sugarcane shredder hammers during operation, for which the real data of the entering sugarcane flow and the power required to prepare the sugarcane are analyzed, and (b) a management architecture intended for online decision-making assistance to extend the hammers’ life by making a trade-off between the desired lifetime, along with a nominal shredder work satisfaction criterion. The deterioration model is validated with real data achieving an accuracy of 84.41%. The remaining life prognostic is within a confidence zone calculated from the historical sugarcane flow, with a probability close to 99%, fitting a lognormal probability distribution. A numerical example is also provided to illustrate a closed loop control, where the proposed architecture is used to extend the useful life of the hammers during operation, adjusting the incoming sugarcane flow while maintaining the nominal work satisfaction of the shredder.https://www.mdpi.com/2227-7390/12/22/3507data-driven methoddeterioration modelextension of lifetimemaintenancemanagement of lifetimeprognostics and health management (PHM) |
| spellingShingle | Diego Rodriguez-Obando Javier Rosero-García Esteban Rosero Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension Mathematics data-driven method deterioration model extension of lifetime maintenance management of lifetime prognostics and health management (PHM) |
| title | Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension |
| title_full | Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension |
| title_fullStr | Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension |
| title_full_unstemmed | Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension |
| title_short | Dynamic Data-Driven Deterioration Model for Sugarcane Shredder Hammers Oriented to Lifetime Extension |
| title_sort | dynamic data driven deterioration model for sugarcane shredder hammers oriented to lifetime extension |
| topic | data-driven method deterioration model extension of lifetime maintenance management of lifetime prognostics and health management (PHM) |
| url | https://www.mdpi.com/2227-7390/12/22/3507 |
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